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How To Redefine The Future Of Fraud Prevention

How To Redefine The Future Of Fraud Prevention

Bottom Line: Redefining the future of fraud prevention starts by turning trust into an accelerator across every aspect of customer lifecycles, basing transactions on identity trust that leads to less friction and improved customer experiences.

Start By Turning Trust Into A Sales & Customer Experience Accelerator

AI and machine learning are proving to be very effective at finding anomalies in transactions and scoring, which are potentially the most fraudulent. Any suspicious transaction attempt leads to more work for buying customers to prove they are trustworthy. For banks, e-commerce sites, financial institutes, restaurants, retailers and many other online businesses, this regularly causes them to lose customers when a legitimate purchase is being made, and trusted customer is asked to verify their identity. Or worse, a false positive that turns away a good customer all together damages both that experience and brand reputation.

There’s a better way to solve the dilemma of deciding which transactions to accept or not. And it needs to start with finding a new way to establish identity trust so businesses can deliver better user experiences. Kount’s approach of using their Real-Time Identity Trust Network to calculate Identity Trust Levels in milliseconds reduces friction, blocks fraud, and delivers an improved user experience. Kount is capitalizing on their database that includes more than a decade of trust and fraud signals built across industries, geographies, and 32 billion annual interactions, combined with expertise in AI and machine learning to turn trust into a sales and customer experience multiplier.

How Real-Time AI Linking Leads To Real-Time Identity Trust Decisions

Design In Identity Trust So It’s The Foundation of Customer Experience

From an engineering and product design standpoint, the majority of fraud prevention providers are looking to make incremental gains in risk scoring to improve customer experiences. None, with the exception of Kount, are looking at the problem from a completely different perspective, which is how to quantify and scale identity trust. Kount’s engineering, product development, and product management teams are concentrating on how to use their AI and machine learning expertise to quantify real-time identity trust scores that drive better customer experiences across the spectrum of trust. The graphic below illustrates how Kount defines more personalized user experiences, which is indispensable in turning trust into an accelerator.

An Overview of Kount’s Technology Stack

How To Redefine The Future Of Fraud Prevention

Realize Trust Is the Most Powerful Revenue Multiplier There Is

Based on my conversations with several fraud prevention providers, they all agree that trust is the most powerful accelerator there is to reducing false positives, friction in transactions, and improving customer experiences. They all agree trust is the most powerful revenue multiplier they can deliver to their customers, helping them reduce fraud and increase sales. The challenge they all face is quantifying identity trust across the wide spectrum of transactions their customers need to fulfill every day.

Kount has taken a unique approach to identity trust that puts the customer at the center of the transactions, not just their transactions’ risk score. By capitalizing on the insights gained from their Identity Trust Global Network, Kount can use AI and machine learning algorithms to deliver personalized responses to transaction requests in milliseconds. Using both unsupervised and supervised machine learning algorithms and techniques, Kount can learn from every customer interaction, gaining new insights into how to fine-tune identity trust for every customer’s transaction.

In choosing to go in the direction of identity trust in its product strategy, Kount put user experiences at the core of their platform strategy. By combining adaptive fraud protection, personalized user experience, and advanced analytics, Kount can create a continuously learning system with the goal of fine-tuning identity trust for every transaction their customers receive. The following graphic explains their approach for bringing identity trust into the center of their platform:

Putting Customers & Their Experiences First Is Integral To Succeeding With Identity Trust

How To Redefine The Future Of Fraud Prevention

 

Improving customer experiences needs to be the cornerstone that drives all fraud prevention product and services road maps in 2020 and beyond. And while all fraud prevention providers are looking at how to reduce friction and improve customer experiences with fraud scoring AI-based techniques, their architectures and approaches aren’t going in the direction of identity trust. Kount’s approach is, and it’s noteworthy because it puts customer experiences at the center of their platform. How to redefine the future of fraud prevention needs to start by turning trust into a sales and customer experience accelerator, followed by designing in identity trust. Hence, it’s the foundation of all customer experiences. By combining the power of networked data and adaptive AI and machine learning, more digital businesses can turn trust into a revenue and customer experience multiplier.

Top 10 Cybersecurity Companies To Watch In 2020

Worldwide spending on information security and risk management systems will reach $131B in 2020, increasing to $174B in 2022 approximately $50B will be dedicated to protecting the endpoint according to Gartner’s latest Information Security and Risk Management forecast. Cloud Security platform and application sales are predicted to grow from $636M in 2020 to $1.63B in 2023, attaining a 36.8% Compound Annual Growth Rate (CAGR) and leading all categories of Information & Security Risk Management systems. Application Security is forecast to grow from $3.4B in 2020 to $4.5B in 2023, attaining a 9.7% CAGR. Security Services is projected to be a $66.9B market this year, increasing from $62B in 2019. AI, Machine Learning And The Race To Improve Cybersecurity The majority of Information Security teams’ cybersecurity analysts are overwhelmed today analyzing security logs, thwarting breach attempts, investigating potential fraud incidents and more. 69% of senior executives believe AI and machine learning are necessary to respond to cyberattacks according to the Capgemini study, Reinventing Cybersecurity with Artificial Intelligence. The following graphic compares the percentage of organizations by industry who are relying on AI to improve their cybersecurity. 80% of telecommunications executives believe their organization would not be able to respond to cyberattacks without AI, with the average being 69% of all enterprises across seven industries. Top 10 Cybersecurity Companies To Watch In 2020 STATISTA The bottom line is all organizations have an urgent need to improve endpoint security and resilience, protect privileged access credentials, reduce fraudulent transactions, and secure every mobile device applying Zero Trust principles. Many are relying on AI and machine learning to determine if login and resource requests are legitimate or not based on past behavioral and system use patterns. Several of the top ten companies to watch take into account a diverse series of indicators to determine if a login attempt, transaction, or system resource request is legitimate or not. They’re able to assign a single score to a specific event and predict if it’s legitimate or not. Kount’s Omniscore is an example of how AI and ML are providing fraud analysts with insights needed to reduce false positives and improve customer buying experiences while thwarting fraud. The following are the top ten cybersecurity companies to watch in 2020: Absolute – Absolute serves as the industry benchmark for endpoint resilience, visibility and control. Embedded in over a half-billion devices, the company enables more than 12,000 customers with self-healing endpoint security, always-connected visibility into their devices, data, users, and applications – whether endpoints are on or off the corporate network – and the ultimate level of control and confidence required for the modern enterprise. To thwart attackers, organizations continue to layer on security controls — Gartner estimates that more than $174B will be spent on security by 2022, and of that approximately $50B will be dedicated protecting the endpoint. Absolute’s Endpoint Security Trends Report finds that in spite of the astronomical investments being made, 100 percent of endpoint controls eventually fail and more than one in three endpoints are unprotected at any given time. All of this has IT and security administrators grappling with increasing complexity and risk levels, while also facing mounting pressure to ensure endpoint controls maintain integrity, availability and functionality at all times, and deliver their intended value. Organizations need complete visibility and real-time insights in order to pinpoint the dark endpoints, identify what’s broken and where gaps exist, as well as respond and take action quickly. Absolute mitigates this universal law of security decay and empowers organizations to build an enterprise security approach that is intelligent, adaptive and self-healing. Rather than perpetuating a false sense of security, Absolute provides a single source of truth and the diamond image of resilience for endpoints. Centrify - Centrify is redefining the legacy approach to Privileged Access Management (PAM) with an Identity-Centric approach based on Zero Trust principles. Centrify’s 15-year history began in Active Directory (AD) bridging, and it was the first vendor to join UNIX and Linux systems with Active Directory, allowing for easy management of privileged identities across a heterogeneous environment. It then extended these capabilities to systems being hosted in IaaS environments like AWS and Microsoft Azure, and offered the industry’s first PAM-as-a-Service, which continues to be the only offering in the market with a true multi-tenant, cloud architecture. Applying its deep expertise in infrastructure allowed Centrify to redefine the legacy approach to PAM and introduce a server’s capability to self-defend against cyber threats across the ever-expanding modern enterprise infrastructure. Centrify Identity-Centric PAM establishes a root of trust for critical enterprise resources, and then grants least privilege access by verifying who is requesting access, the context of the request, and the risk of the access environment. By implementing least privilege access, Centrify minimizes the attack surface, improves audit and compliance visibility, and reduces risk, complexity, and costs for the modern, hybrid enterprise. Over half of the Fortune 100, the world’s largest financial institutions, intelligence agencies, and critical infrastructure companies, all trust Centrify to stop the leading cause of breaches – privileged credential abuse. Research firm Gartner predicts that by 2021, approximately 75% of large enterprises will utilize privileged access management products, up from approximately 50% in 2018 in their Forecast Analysis: Information Security and Risk Management, Worldwide, 4Q18 Update published March 29, 2019 (client access reqd). This is not surprising, considering that according to an estimate by Forrester Research, 80% of today’s breaches are caused by weak, default, stolen, or otherwise compromised privileged credentials. Deep Instinct – Deep Instinct applies artificial intelligence’s deep learning to cybersecurity. Leveraging deep learning’s predictive capabilities, Deep Instinct’s on-device solution protects against zero-day threats and APT attacks with unmatched accuracy. Deep Instinct safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet. By applying deep learning technology to cybersecurity, enterprises can now gain unmatched protection against unknown and evasive cyber-attacks from any source. Deep Instinct brings a completely new approach to cybersecurity enabling cyber-attacks to be identified and blocked in real-time before any harm can occur. Deep Instinct USA is headquartered in San Francisco, CA and Deep Instinct Israel is headquartered in Tel Aviv, Israel. Infoblox - Infoblox empowers organizations to bring next-level simplicity, security, reliability and automation to traditional networks and digital transformations, such as SD-WAN, hybrid cloud and IoT. Combining next-level simplicity, security, reliability and automation, Infoblox is able to cut manual tasks by 70% and make organizations’ threat analysts 3x more productive. While their history is in DDI devices, they are succeeding in providing DDI and network security services on an as-a-service (-aaS) basis. Their BloxOne DDI application, built on their BloxOne cloud-native platform, helps enable IT, professionals, to manage their networks whether they're based on on-prem, cloud-based, or hybrid architectures. BloxOne Threat Defense application leverages the data provided by DDI to monitor network traffic, proactively identify threats, and quickly inform security systems and network managers of breaches, working with the existing security stack to identify and mitigate security threats quickly, automatically, and more efficiently. The BloxOne platform provides a secure, integrated platform for centralizing the management of identity data and services across the network. A recognized industry leader, Infoblox has a 52% market share in the DDI networking market comprised of 8,000 customers, including 59% of the Fortune 1000 and 58% of the Forbes 2000. Kount – Kount’s award-winning, AI-driven fraud prevention empowers digital businesses, online merchants, and payment service providers around the world to protect against payments fraud, new account creation fraud, and account takeover. With Kount, businesses approve more good orders, uncover new revenue streams, improve customer experience and dramatically improve their bottom line all while minimizing fraud management cost and losses. Through Kount’s global network and proprietary technologies in AI and machine learning, combined with flexible policy management, companies frustrate online criminals and bad actors driving them away from their site, their marketplace, and off their network. Kount’s continuously adaptive platform provides certainty for businesses at every digital interaction. Kount’s advances in both proprietary techniques and patented technology include mobile fraud detection, advanced artificial intelligence, multi-layer device fingerprinting, IP proxy detection and geo-location, transaction and custom scoring, global order linking, business intelligence reporting, comprehensive order management, as well as professional and managed services. Kount protects over 6,500 brands today. Mimecast – Mimecast improves the way companies manage confidential, mission-critical business communication and data. The company's mission is to reduce the risks users face from email, and support in reducing the cost and complexity of protecting users by moving the workload to the cloud. The company develops proprietary cloud architecture to deliver comprehensive email security, service continuity, and archiving in a single subscription service. Its goal is to make it easier for people to protect a business in today’s fast-changing security and risk environment. The company expanded its technology portfolio in 2019 through a pair of acquisitions, buying data migration technology provider Simply Migrate to help customers and prospects move to the cloud more quickly, reliably, and inexpensively. Mimecast also purchased email security startup DMARC Analyzer to reduce the time, effort, and cost associated with stopping domain spoofing attacks. Mimecast acquired Segasec earlier this month, a leading provider of digital threat protection. With the acquisition of Segasec, Mimecast can provide brand exploit protection, using machine learning to identify potential hackers at the earliest stages of an attack. The solution also is engineered to provide a way to actively monitor, manage, block, and take down phishing scams or impersonation attempts on the Web. MobileIron – A long-time leader in mobile management solutions, MobileIron is widely recognized by Chief Information Security Officers, CIOs and senior management teams as the de facto standard for unified endpoint management (UEM), mobile application management (MAM), BYOD security, and zero sign-on (ZSO). The company’s UEM platform is strengthened by MobileIron Threat Defense and MobileIron’s Access solution, which allows for zero sign-on authentication. Forrester observes in their latest Wave on Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 that “MobileIron’s recently released authenticator, which enables passwordless authentication to cloud services, is a must for future-state Zero Trust enterprises and speaks to its innovation in this space.” The Wave also illustrates that MobileIron is the most noteworthy vendor as their approach to Zero Trust begins with the device and scales across mobile infrastructures. MobileIron’s product suite also includes a federated policy engine that enables administrators to control and better command the myriad of devices and endpoints that enterprises rely on today. Forrester sees MobileIron as having excellent integration at the platform level, a key determinant of how effective they will be in providing support to enterprises pursuing Zero Trust Security strategies in the future. One Identity – One Identity is differentiating its Identity Manager identity analytics and risk scoring capabilities with greater integration via its connected system modules. The goal of these modules is to provide customers with more flexibility in defining reports that include application-specific content. Identity Manager also has over 30 direct provisioning connectors included in the base package, with good platform coverage, including strong Microsoft and Office 365 support. Additional premium connectors are charged separately. One Identity also has a separate cloud-architected SaaS solution called One Identity Starling. One of Starling’s greatest benefits is its design that allows for it to be used not only by Identity Manager clients, but also by clients of other IGA solutions as a simplified approach to obtain SaaS-based identity analytics, risk intelligence, and cloud provisioning. One Identity and its approach is trusted by customers worldwide, where more than 7,500 organizations worldwide depend on One Identity solutions to manage more than 125 million identities, enhancing their agility and efficiency while securing access to their systems and data – on-prem, cloud, or hybrid. SECURITI.ai - SECURITI.ai is the leader in AI-Powered PrivacyOps, that helps automate all major functions needed for privacy compliance in one place. It enables enterprises to give rights to people on their data, be responsible custodians of people’s data, comply with global privacy regulations like CCPA and bolster their brands. The AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. These include a Personal Data Graph Builder, Robotic Automation for Data Subject Requests, Secure Data Request Portal, Consent Lifecycle Manager, Third-Party Privacy Assessment, Third-Party Privacy Ratings, Privacy Assessment Automation and Breach Management. SECURITI.ai is also featured in the Consent Management section of Bessemer’s Data Privacy Stack shown below and available in Bessemer Venture Partner’s recent publication How data privacy engineering will prevent future data oil spills (10 pp., PDF, no opt-in). Top 10 Cybersecurity Companies To Watch In 2020 SOURCE: BESSEMER VENTURE PARTNERS, HOW DATA PRIVACY ENGINEERING WILL PREVENT FUTURE DATA OIL SPILLS , SEPTEMBER, 2019. (10 PP., PDF, NO OPT-IN). Transmit Security - The Transmit Security Platform provides a solution for managing identity across applications while maintaining security and usability. As criminal threats evolve, online authentication has become reactive and less effective. Many organizations have taken on multiple point solutions to try to stay ahead, deploying new authenticators, risk engines, and fraud tools. In the process, the customer experience has suffered. And with an increasingly complex environment, many enterprises struggle with the ability to rapidly innovate to provide customers with an omnichannel experience that enables them to stay ahead of emerging threats.

  • Worldwide spending on information security and risk management systems will reach $131B in 2020, increasing to $174B in 2022 approximately $50B will be dedicated to protecting the endpoint according to Gartner’s latest Information Security and Risk Management forecast.
  • Cloud Security platform and application sales are predicted to grow from $636M in 2020 to $1.63B in 2023, attaining a 36.8% Compound Annual Growth Rate (CAGR) and leading all categories of Information & Security Risk Management systems.
  • Application Security is forecast to grow from $3.4B in 2020 to $4.5B in 2023, attaining a 9.7% CAGR.
  • Security Services is projected to be a $66.9B market this year, increasing from $62B in 2019.

AI, Machine Learning And The Race To Improve Cybersecurity  

The majority of Information Security teams’ cybersecurity analysts are overwhelmed today analyzing security logs, thwarting breach attempts, investigating potential fraud incidents and more. 69% of senior executives believe AI and machine learning are necessary to respond to cyberattacks according to the Capgemini study, Reinventing Cybersecurity with Artificial Intelligence. The following graphic compares the percentage of organizations by industry who are relying on AI to improve their cybersecurity. 80% of telecommunications executives believe their organization would not be able to respond to cyberattacks without AI, with the average being 69% of all enterprises across seven industries.

The bottom line is all organizations have an urgent need to improve endpoint security and resilience, protect privileged access credentials, reduce fraudulent transactions, and secure every mobile device applying Zero Trust principles. Many are relying on AI and machine learning to determine if login and resource requests are legitimate or not based on past behavioral and system use patterns. Several of the top ten companies to watch take into account a diverse series of indicators to determine if a login attempt, transaction, or system resource request is legitimate or not. They’re able to assign a single score to a specific event and predict if it’s legitimate or not. Kount’s Omniscore is an example of how AI and ML are providing fraud analysts with insights needed to reduce false positives and improve customer buying experiences while thwarting fraud.

The following are the top ten cybersecurity companies to watch in 2020:

Absolute – Absolute serves as the industry benchmark for endpoint resilience, visibility and control. Embedded in over a half-billion devices, the company enables more than 12,000 customers with self-healing endpoint security, always-connected visibility into their devices, data, users, and applications – whether endpoints are on or off the corporate network – and the ultimate level of control and confidence required for the modern enterprise.

To thwart attackers, organizations continue to layer on security controls — Gartner estimates that more than $174B will be spent on security by 2022, and of that approximately $50B will be dedicated protecting the endpoint. Absolute’s Endpoint Security Trends Report finds that in spite of the astronomical investments being made, 100 percent of endpoint controls eventually fail and more than one in three endpoints are unprotected at any given time. All of this has IT and security administrators grappling with increasing complexity and risk levels, while also facing mounting pressure to ensure endpoint controls maintain integrity, availability and functionality at all times, and deliver their intended value.

Organizations need complete visibility and real-time insights in order to pinpoint the dark endpoints, identify what’s broken and where gaps exist, as well as respond and take action quickly. Absolute mitigates this universal law of security decay and empowers organizations to build an enterprise security approach that is intelligent, adaptive and self-healing. Rather than perpetuating a false sense of security, Absolute provides a single source of truth and the diamond image of resilience for endpoints.

CentrifyCentrify is redefining the legacy approach to Privileged Access Management (PAM) with an Identity-Centric approach based on Zero Trust principles. Centrify’s 15-year history began in Active Directory (AD) bridging, and it was the first vendor to join UNIX and Linux systems with Active Directory, allowing for easy management of privileged identities across a heterogeneous environment. It then extended these capabilities to systems being hosted in IaaS environments like AWS and Microsoft Azure, and offered the industry’s first PAM-as-a-Service, which continues to be the only offering in the market with a true multi-tenant, cloud architecture. Applying its deep expertise in infrastructure allowed Centrify to redefine the legacy approach to PAM and introduce a server’s capability to self-defend against cyber threats across the ever-expanding modern enterprise infrastructure.

Centrify Identity-Centric PAM establishes a root of trust for critical enterprise resources, and then grants least privilege access by verifying who is requesting access, the context of the request, and the risk of the access environment. By implementing least privilege access, Centrify minimizes the attack surface, improves audit and compliance visibility, and reduces risk, complexity, and costs for the modern, hybrid enterprise. Over half of the Fortune 100, the world’s largest financial institutions, intelligence agencies, and critical infrastructure companies, all trust Centrify to stop the leading cause of breaches – privileged credential abuse.

Research firm Gartner predicts that by 2021, approximately 75% of large enterprises will utilize privileged access management products, up from approximately 50% in 2018 in their Forecast Analysis: Information Security and Risk Management, Worldwide, 4Q18 Update published March 29, 2019 (client access reqd). This is not surprising, considering that according to an estimate by Forrester Research, 80% of today’s breaches are caused by weak, default, stolen, or otherwise compromised privileged credentials.

Deep Instinct – Deep Instinct applies artificial intelligence’s deep learning to cybersecurity. Leveraging deep learning’s predictive capabilities, Deep Instinct’s on-device solution protects against zero-day threats and APT attacks with unmatched accuracy. Deep Instinct safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet. By applying deep learning technology to cybersecurity, enterprises can now gain unmatched protection against unknown and evasive cyber-attacks from any source. Deep Instinct brings a completely new approach to cybersecurity enabling cyber-attacks to be identified and blocked in real-time before any harm can occur. Deep Instinct USA is headquartered in San Francisco, CA and Deep Instinct Israel is headquartered in Tel Aviv, Israel.

Infoblox – Infoblox empowers organizations to bring next-level simplicity, security, reliability and automation to traditional networks and digital transformations, such as SD-WAN, hybrid cloud and IoT. Combining next-level simplicity, security, reliability, and automation, Infoblox can cut manual tasks by 70% and make organizations’ threat analysts 3x more productive.

While their history is in DDI devices, they are succeeding in providing DDI and network security services on an as-a-service (-aaS) basis. Their BloxOne DDI  application, built on their BloxOne cloud-native platform, helps enable IT professionals to manage their networks, whether they’re based on on-prem, cloud-based, or hybrid architectures.  BloxOne Threat Defense  application leverages the data provided by DDI to monitor network traffic, proactively identify threats, and quickly inform security systems and network managers of breaches, working with the existing security stack to identify and mitigate security threats quickly, automatically, and more efficiently. The BloxOne platform provides a secure, integrated platform for centralizing the management of identity data and services across the network. A recognized industry leader, Infoblox has a 52% market share in the DDI networking market comprised of 8,000 customers, including 59% of the Fortune 1000 and 58% of the Forbes 2000.

Kount – Kount’s award-winning, AI-driven fraud prevention empowers digital businesses, online merchants, and payment service providers around the world to protect against payments fraud, new account creation fraud, and account takeover. With Kount, businesses approve more good orders, uncover new revenue streams, improve customer experience, and dramatically improve their bottom line all while minimizing fraud management cost and losses. Through Kount’s global network and proprietary technologies in AI and machine learning, combined with flexible policy management, companies frustrate online criminals and bad actors driving them away from their site, their marketplace, and off their network. Kount’s continuously adaptive platform provides certainty for businesses at every digital interaction. Kount’s advances in both proprietary techniques and patented technology include mobile fraud detection, advanced artificial intelligence, multi-layer device fingerprinting, IP proxy detection and geo-location, transaction and custom scoring, global order linking, business intelligence reporting, comprehensive order management, as well as professional and managed services. Kount protects over 6,500 brands today.

MimecastMimecast improves the way companies manage confidential, mission-critical business communication and data. The company’s mission is to reduce the risks users face from email, and support in reducing the cost and complexity of protecting users by moving the workload to the cloud. The company develops proprietary cloud architecture to deliver comprehensive email security, service continuity, and archiving in a single subscription service. Its goal is to make it easier for people to protect a business in today’s fast-changing security and risk environment. The company expanded its technology portfolio in 2019 through a pair of acquisitions, buying data migration technology provider Simply Migrate to help customers and prospects move to the cloud more quickly, reliably, and inexpensively. Mimecast also purchased email security startup DMARC Analyzer to reduce the time, effort, and cost associated with stopping domain spoofing attacks. Mimecast acquired Segasec earlier this month, a leading provider of digital threat protection. With the acquisition of Segasec, Mimecast can provide brand exploit protection, using machine learning to identify potential hackers at the earliest stages of an attack. The solution also is engineered to provide a way to actively monitor, manage, block, and take down phishing scams or impersonation attempts on the Web.

MobileIron – A long-time leader in mobile management solutions, MobileIron is widely recognized by Chief Information Security Officers, CIOs and senior management teams as the de facto standard for unified endpoint management (UEM), mobile application management (MAM), BYOD security, and zero sign-on (ZSO). The company’s UEM platform is strengthened by MobileIron Threat Defense and MobileIron’s Access solution, which allows for zero sign-on authentication. Forrester observes in their latest Wave on Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 that “MobileIron’s recently released authenticator, which enables passwordless authentication to cloud services, is a must for future-state Zero Trust enterprises and speaks to its innovation in this space.” The Wave also illustrates that MobileIron is the most noteworthy vendor as their approach to Zero Trust begins with the device and scales across mobile infrastructures. MobileIron’s product suite also includes a federated policy engine that enables administrators to control and better command the myriad of devices and endpoints that enterprises rely on today. Forrester sees MobileIron as having excellent integration at the platform level, a key determinant of how effective they will be in providing support to enterprises pursuing Zero Trust Security strategies in the future.

One Identity – One Identity is differentiating its Identity Manager identity analytics and risk scoring capabilities with greater integration via its connected system modules. The goal of these modules is to provide customers with more flexibility in defining reports that include application-specific content. Identity Manager also has over 30 direct provisioning connectors included in the base package, with good platform coverage, including strong Microsoft and Office 365 support. Additional premium connectors are charged separately. One Identity also has a separate cloud-architected SaaS solution called One Identity Starling. One of Starling’s greatest benefits is its design that allows for it to be used not only by Identity Manager clients, but also by clients of other IGA solutions as a simplified approach to obtain SaaS-based identity analytics, risk intelligence, and cloud provisioning. One Identity and its approach is trusted by customers worldwide, where more than 7,500 organizations worldwide depend on One Identity solutions to manage more than 125 million identities, enhancing their agility and efficiency while securing access to their systems and data – on-prem, cloud, or hybrid.

SECURITI.ai – SECURITI.ai is the leader in AI-Powered PrivacyOps, that helps automate all major functions needed for privacy compliance in one place. It enables enterprises to give rights to people on their data, be responsible custodians of people’s data, comply with global privacy regulations like CCPA, and bolster their brands.

The AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. These include a Personal Data Graph Builder, Robotic Automation for Data Subject Requests, Secure Data Request Portal, Consent Lifecycle Manager, Third-Party Privacy Assessment, Third-Party Privacy Ratings, Privacy Assessment Automation and Breach Management. SECURITI.ai is also featured in the Consent Management section of Bessemer’s Data Privacy Stack shown below and available in Bessemer Venture Partner’s recent publication How data privacy engineering will prevent future data oil spills (10 pp., PDF, no opt-in).

Worldwide spending on information security and risk management systems will reach $131B in 2020, increasing to $174B in 2022 approximately $50B will be dedicated to protecting the endpoint according to Gartner’s latest Information Security and Risk Management forecast. Cloud Security platform and application sales are predicted to grow from $636M in 2020 to $1.63B in 2023, attaining a 36.8% Compound Annual Growth Rate (CAGR) and leading all categories of Information & Security Risk Management systems. Application Security is forecast to grow from $3.4B in 2020 to $4.5B in 2023, attaining a 9.7% CAGR. Security Services is projected to be a $66.9B market this year, increasing from $62B in 2019. AI, Machine Learning And The Race To Improve Cybersecurity The majority of Information Security teams’ cybersecurity analysts are overwhelmed today analyzing security logs, thwarting breach attempts, investigating potential fraud incidents and more. 69% of senior executives believe AI and machine learning are necessary to respond to cyberattacks according to the Capgemini study, Reinventing Cybersecurity with Artificial Intelligence. The following graphic compares the percentage of organizations by industry who are relying on AI to improve their cybersecurity. 80% of telecommunications executives believe their organization would not be able to respond to cyberattacks without AI, with the average being 69% of all enterprises across seven industries. Top 10 Cybersecurity Companies To Watch In 2020 STATISTA The bottom line is all organizations have an urgent need to improve endpoint security and resilience, protect privileged access credentials, reduce fraudulent transactions, and secure every mobile device applying Zero Trust principles. Many are relying on AI and machine learning to determine if login and resource requests are legitimate or not based on past behavioral and system use patterns. Several of the top ten companies to watch take into account a diverse series of indicators to determine if a login attempt, transaction, or system resource request is legitimate or not. They’re able to assign a single score to a specific event and predict if it’s legitimate or not. Kount’s Omniscore is an example of how AI and ML are providing fraud analysts with insights needed to reduce false positives and improve customer buying experiences while thwarting fraud. The following are the top ten cybersecurity companies to watch in 2020: Absolute – Absolute serves as the industry benchmark for endpoint resilience, visibility and control. Embedded in over a half-billion devices, the company enables more than 12,000 customers with self-healing endpoint security, always-connected visibility into their devices, data, users, and applications – whether endpoints are on or off the corporate network – and the ultimate level of control and confidence required for the modern enterprise. To thwart attackers, organizations continue to layer on security controls — Gartner estimates that more than $174B will be spent on security by 2022, and of that approximately $50B will be dedicated protecting the endpoint. Absolute’s Endpoint Security Trends Report finds that in spite of the astronomical investments being made, 100 percent of endpoint controls eventually fail and more than one in three endpoints are unprotected at any given time. All of this has IT and security administrators grappling with increasing complexity and risk levels, while also facing mounting pressure to ensure endpoint controls maintain integrity, availability and functionality at all times, and deliver their intended value. Organizations need complete visibility and real-time insights in order to pinpoint the dark endpoints, identify what’s broken and where gaps exist, as well as respond and take action quickly. Absolute mitigates this universal law of security decay and empowers organizations to build an enterprise security approach that is intelligent, adaptive and self-healing. Rather than perpetuating a false sense of security, Absolute provides a single source of truth and the diamond image of resilience for endpoints. Centrify - Centrify is redefining the legacy approach to Privileged Access Management (PAM) with an Identity-Centric approach based on Zero Trust principles. Centrify’s 15-year history began in Active Directory (AD) bridging, and it was the first vendor to join UNIX and Linux systems with Active Directory, allowing for easy management of privileged identities across a heterogeneous environment. It then extended these capabilities to systems being hosted in IaaS environments like AWS and Microsoft Azure, and offered the industry’s first PAM-as-a-Service, which continues to be the only offering in the market with a true multi-tenant, cloud architecture. Applying its deep expertise in infrastructure allowed Centrify to redefine the legacy approach to PAM and introduce a server’s capability to self-defend against cyber threats across the ever-expanding modern enterprise infrastructure. Centrify Identity-Centric PAM establishes a root of trust for critical enterprise resources, and then grants least privilege access by verifying who is requesting access, the context of the request, and the risk of the access environment. By implementing least privilege access, Centrify minimizes the attack surface, improves audit and compliance visibility, and reduces risk, complexity, and costs for the modern, hybrid enterprise. Over half of the Fortune 100, the world’s largest financial institutions, intelligence agencies, and critical infrastructure companies, all trust Centrify to stop the leading cause of breaches – privileged credential abuse. Research firm Gartner predicts that by 2021, approximately 75% of large enterprises will utilize privileged access management products, up from approximately 50% in 2018 in their Forecast Analysis: Information Security and Risk Management, Worldwide, 4Q18 Update published March 29, 2019 (client access reqd). This is not surprising, considering that according to an estimate by Forrester Research, 80% of today’s breaches are caused by weak, default, stolen, or otherwise compromised privileged credentials. Deep Instinct – Deep Instinct applies artificial intelligence’s deep learning to cybersecurity. Leveraging deep learning’s predictive capabilities, Deep Instinct’s on-device solution protects against zero-day threats and APT attacks with unmatched accuracy. Deep Instinct safeguards the enterprise’s endpoints and/or any mobile devices against any threat, on any infrastructure, whether or not connected to the network or to the Internet. By applying deep learning technology to cybersecurity, enterprises can now gain unmatched protection against unknown and evasive cyber-attacks from any source. Deep Instinct brings a completely new approach to cybersecurity enabling cyber-attacks to be identified and blocked in real-time before any harm can occur. Deep Instinct USA is headquartered in San Francisco, CA and Deep Instinct Israel is headquartered in Tel Aviv, Israel. Infoblox - Infoblox empowers organizations to bring next-level simplicity, security, reliability and automation to traditional networks and digital transformations, such as SD-WAN, hybrid cloud and IoT. Combining next-level simplicity, security, reliability and automation, Infoblox is able to cut manual tasks by 70% and make organizations’ threat analysts 3x more productive. While their history is in DDI devices, they are succeeding in providing DDI and network security services on an as-a-service (-aaS) basis. Their BloxOne DDI application, built on their BloxOne cloud-native platform, helps enable IT, professionals, to manage their networks whether they're based on on-prem, cloud-based, or hybrid architectures. BloxOne Threat Defense application leverages the data provided by DDI to monitor network traffic, proactively identify threats, and quickly inform security systems and network managers of breaches, working with the existing security stack to identify and mitigate security threats quickly, automatically, and more efficiently. The BloxOne platform provides a secure, integrated platform for centralizing the management of identity data and services across the network. A recognized industry leader, Infoblox has a 52% market share in the DDI networking market comprised of 8,000 customers, including 59% of the Fortune 1000 and 58% of the Forbes 2000. Kount – Kount’s award-winning, AI-driven fraud prevention empowers digital businesses, online merchants, and payment service providers around the world to protect against payments fraud, new account creation fraud, and account takeover. With Kount, businesses approve more good orders, uncover new revenue streams, improve customer experience and dramatically improve their bottom line all while minimizing fraud management cost and losses. Through Kount’s global network and proprietary technologies in AI and machine learning, combined with flexible policy management, companies frustrate online criminals and bad actors driving them away from their site, their marketplace, and off their network. Kount’s continuously adaptive platform provides certainty for businesses at every digital interaction. Kount’s advances in both proprietary techniques and patented technology include mobile fraud detection, advanced artificial intelligence, multi-layer device fingerprinting, IP proxy detection and geo-location, transaction and custom scoring, global order linking, business intelligence reporting, comprehensive order management, as well as professional and managed services. Kount protects over 6,500 brands today. Mimecast – Mimecast improves the way companies manage confidential, mission-critical business communication and data. The company's mission is to reduce the risks users face from email, and support in reducing the cost and complexity of protecting users by moving the workload to the cloud. The company develops proprietary cloud architecture to deliver comprehensive email security, service continuity, and archiving in a single subscription service. Its goal is to make it easier for people to protect a business in today’s fast-changing security and risk environment. The company expanded its technology portfolio in 2019 through a pair of acquisitions, buying data migration technology provider Simply Migrate to help customers and prospects move to the cloud more quickly, reliably, and inexpensively. Mimecast also purchased email security startup DMARC Analyzer to reduce the time, effort, and cost associated with stopping domain spoofing attacks. Mimecast acquired Segasec earlier this month, a leading provider of digital threat protection. With the acquisition of Segasec, Mimecast can provide brand exploit protection, using machine learning to identify potential hackers at the earliest stages of an attack. The solution also is engineered to provide a way to actively monitor, manage, block, and take down phishing scams or impersonation attempts on the Web. MobileIron – A long-time leader in mobile management solutions, MobileIron is widely recognized by Chief Information Security Officers, CIOs and senior management teams as the de facto standard for unified endpoint management (UEM), mobile application management (MAM), BYOD security, and zero sign-on (ZSO). The company’s UEM platform is strengthened by MobileIron Threat Defense and MobileIron’s Access solution, which allows for zero sign-on authentication. Forrester observes in their latest Wave on Zero Trust eXtended Ecosystem Platform Providers, Q4 2019 that “MobileIron’s recently released authenticator, which enables passwordless authentication to cloud services, is a must for future-state Zero Trust enterprises and speaks to its innovation in this space.” The Wave also illustrates that MobileIron is the most noteworthy vendor as their approach to Zero Trust begins with the device and scales across mobile infrastructures. MobileIron’s product suite also includes a federated policy engine that enables administrators to control and better command the myriad of devices and endpoints that enterprises rely on today. Forrester sees MobileIron as having excellent integration at the platform level, a key determinant of how effective they will be in providing support to enterprises pursuing Zero Trust Security strategies in the future. One Identity – One Identity is differentiating its Identity Manager identity analytics and risk scoring capabilities with greater integration via its connected system modules. The goal of these modules is to provide customers with more flexibility in defining reports that include application-specific content. Identity Manager also has over 30 direct provisioning connectors included in the base package, with good platform coverage, including strong Microsoft and Office 365 support. Additional premium connectors are charged separately. One Identity also has a separate cloud-architected SaaS solution called One Identity Starling. One of Starling’s greatest benefits is its design that allows for it to be used not only by Identity Manager clients, but also by clients of other IGA solutions as a simplified approach to obtain SaaS-based identity analytics, risk intelligence, and cloud provisioning. One Identity and its approach is trusted by customers worldwide, where more than 7,500 organizations worldwide depend on One Identity solutions to manage more than 125 million identities, enhancing their agility and efficiency while securing access to their systems and data – on-prem, cloud, or hybrid. SECURITI.ai - SECURITI.ai is the leader in AI-Powered PrivacyOps, that helps automate all major functions needed for privacy compliance in one place. It enables enterprises to give rights to people on their data, be responsible custodians of people’s data, comply with global privacy regulations like CCPA and bolster their brands. The AI-Powered PrivacyOps platform is a full-stack solution that operationalizes and simplifies privacy compliance using robotic automation and a natural language interface. These include a Personal Data Graph Builder, Robotic Automation for Data Subject Requests, Secure Data Request Portal, Consent Lifecycle Manager, Third-Party Privacy Assessment, Third-Party Privacy Ratings, Privacy Assessment Automation and Breach Management. SECURITI.ai is also featured in the Consent Management section of Bessemer’s Data Privacy Stack shown below and available in Bessemer Venture Partner’s recent publication How data privacy engineering will prevent future data oil spills (10 pp., PDF, no opt-in). Top 10 Cybersecurity Companies To Watch In 2020 SOURCE: BESSEMER VENTURE PARTNERS, HOW DATA PRIVACY ENGINEERING WILL PREVENT FUTURE DATA OIL SPILLS , SEPTEMBER, 2019. (10 PP., PDF, NO OPT-IN). Transmit Security - The Transmit Security Platform provides a solution for managing identity across applications while maintaining security and usability. As criminal threats evolve, online authentication has become reactive and less effective. Many organizations have taken on multiple point solutions to try to stay ahead, deploying new authenticators, risk engines, and fraud tools. In the process, the customer experience has suffered. And with an increasingly complex environment, many enterprises struggle with the ability to rapidly innovate to provide customers with an omnichannel experience that enables them to stay ahead of emerging threats.

Transmit Security – The Transmit Security Platform provides a solution for managing identity across applications while maintaining security and usability. As criminal threats evolve, online authentication has become reactive and less effective. Many organizations have taken on multiple point solutions to try to stay ahead, deploying new authenticators, risk engines, and fraud tools. In the process, the customer experience has suffered. And with an increasingly complex environment, many enterprises struggle with the ability to rapidly innovate to provide customers with an omnichannel experience that enables them to stay ahead of emerging threats.

How AI Is Improving Omnichannel CyberSecurity In 2020

How AI Is Improving Omnichannel CyberSecurity in 2020

  • 52% of financial institutions plan to invest in additional measures to secure existing accounts, and 46% plan to invest in better identity-verification measures.
  • 42% of digital businesses that consider themselves technologically advanced are finding fraud is restraining their ability to grow and adopt new digital innovation strategies.
  • 33% of all businesses across retail, financial institutions, restaurants, and insurance are investing in their omnichannel strategies this year.

These and many other insights are from Javelin Strategy, and Research report published this month, Protecting Digital Innovation: Emerging Fraud and Attack Vectors. A copy of the report can be downloaded here (25 pp., PDF, opt-in). The methodology is based on a survey of 200 fraud and payment decision-makers for businesses headquartered in the United States. Respondents are evenly distributed from four industries, including consumer banking, insurance, restaurants/food service, and retail merchants.

The survey’s results are noteworthy because they reflect how AI and machine learning-based fraud prevention techniques are helping retailers, financial services, insurance, and restaurants to reduce false positives that, in turn, reduces friction for their customers. All industries are in an arms race with fraudsters, many of whom are using machine learning to thwart fraud prevention systems. There are a series of fraud prevention providers countering fraud and helping industries stay ahead. A leader in this field is Kount, with its Omniscore that provides digital businesses with what they need to fight fraud while providing the best possible customer experience.

The following are the key insights from the Javelin Strategy and Research report published this month:

  • Retailers, financial institutions, restaurants, and insurance companies need to invest in fraud mitigation at the same rate as new product innovation, with retail and banking leading the way. Restaurants and insurance are lagging in their adoption of fraud mitigation techniques and, as a result, tend to experience more fraud. The insurance industry has a friendly fraud problem that is hard to catch. Over half of the financial institutions interviewed, 52% plan to invest in additional technologies to secure existing accounts, and 46% plan to invest in better identity-verification measures. Based on the survey, banks appear to be early adopters of AI and machine learning for fraud prevention. The study makes an excellent point that banking via virtual assistants is still nascent and constrained by the lack of information sharing within the ecosystem, which restricts authentication measures to PINs and passwords.

How AI Is Improving Omnichannel CyberSecurity in 2020

  • 57% of all businesses are adding new products and services as their leading digital innovation strategy in 2020, followed by refining the user experience (55%) and expanding their digital strategy teams. Comparing priorities for digital innovation across the four industries reflects how each is approaching their omnichannel strategy. The banking industry places the highest priority on improving the security of existing user accounts at 52% of financial institutions surveyed. Improving security is the highest priority in banking today, according to the survey results shown below. This further validates how advanced banking and financial institutions are in their use of AI and machine learning for fraud prevention.

How AI Is Improving Omnichannel CyberSecurity in 2020

  • Digital businesses plan to improve their omnichannel strategies by improving their website, mobile app, and online catalog customer experiences across all channels in addition to better integration between digital and physical services is how. 40% of respondents are actively investing in improving the integration between digital and physical services. That’s an essential step for ensuring a consistently excellent user experience across websites, product catalogs, buy online and pick up in-store, and consistent user experiences across all digital and physical channels.

How AI Is Improving Omnichannel CyberSecurity in 2020

  • 69% of all digital businesses interviewed are planning to make additional fraud investments this year. Banking and financial institutions dominate the four industries surveyed in the plans for additional fraud investment. 82% of consumer banks are planning to invest in additional fraud detection technologies. Insurers are least likely to invest in fraud detection technologies in 2020. The study notes that this can be attributed to insurers’ unique challenges with first-party fraud or fraud committed by legitimate policyholders, which is poorly addressed by many mainstream fraud controls.

How AI Is Improving Omnichannel CyberSecurity in 2020

  • Using AI-based scoring techniques to detect stolen credit card data being used online or in mobile apps, dominates financial institutions’ priorities today. 34% of financial institutions cite their top fraud threat being the use of stolen credit card data used online or in mobile apps. 18% say account takeovers are their most important area to reduce fraud. Financial institutions lead all others in fraud technology investments to thwart fraud, with managing digital fraud risk being the highest priority of all compared to the three other industries represented in the survey.

How AI Is Improving Omnichannel CyberSecurity in 2020

  • 52% of all financial institutions say that improving the security of existing user accounts leads all digital investment priorities in 2020. What’s significant about this finding is that it outpaces adding new digital products and services and improving identity verification of new users. This is another factor that contributes to financial institutions’ leadership role in relying on AI and machine learning to improve fraud detection and deterrence.   

How AI Is Improving Omnichannel CyberSecurity in 2020

 

 

10 Ways To Own Your Cybersecurity In 2020

10 Ways To Own Your Cybersecurity In 2020

Bottom Line: One of the best New Year’s resolutions anyone can make is to learn new ways to secure their personal and professional lives online, starting with ten proven ways they can take greater control over their own cybersecurity.

For many professionals, their personal and professional lives have blended together thanks to the growing number of connected, IoT-capable devices, including cars, home security systems, smartphones, virtual assistants including Amazon Echo, Google Home, WiFi routers, and more. It’s typical to find homes with two dozen or more connected devices that are relied for everything going on in a person’s life from personal interests, connecting with friends, and getting work done.

It’s Time to Secure Every Area of Your Smart, Connected World

Faced with chronic time shortages, many people rely on smart, connected devices supported by AI and machine learning to get more done in less time. They’re proliferating today because they’ve proven to be very effective at personalizing experiences while providing the added convenience of being always on and available to help. Smart, connected devices are an extension of a person’s identity today as they contain insights into buying behavior and, in some cases, actual conversations. The more these devices are protected, the more a person’s identity and most valuable resource of all – time – is protected too.

Strengthening your own cybersecurity starts by seeing every device and the apps you use as potential attack surfaces that need to be protected. Just as you wouldn’t likely leave any of the physical doors to your home unprotected and locked, you need to secure all the digital entrances to your home and person. Like the CEO and cybersecurity team of any organization who is focusing on how to reduce the risk of a breach, the same level of intensity and vigilance to personal cybersecurity needs to become the new normal.

10 Ways You Can Own Your Cybersecurity

The following are the top ten ways you can take control and own your own security. Several of the ways mentioned below are from the recent Centrify webinar, Cybersecurity Best Practices: The Basics and Beyond:

  • Replace weak passwords used on multiple accounts with a unique, longer password for each online account. Start by getting away from having the same password for multiple accounts. When a single account gets hacked, it can easily lead to all the others with the same password and comparable user ID. Passwords are proving to be the weakest attack vector there is for personal information today. World Password Day serves as a reminder every May to use stronger, different passwords on each account.
  • Start researching and choose a Password Manager that is flexible enough to match how you like to work. It’s time to get beyond Post-It notes and paper-based approaches to managing your own passwords now. Dashlane, LastPass, and OneLogin are all excellent password managers worth checking out. If you’re not sure password managers are worth it, I’ve seen them add an additional layer of security to personal and work accounts that would not have otherwise been available. Some will even notify you when an account you have might have been breached, and recommend a new password for you. A screen capture from the webinar illustrates the differences between personal, professional and Privileged Access Management (PAM) levels of password security:

10 Ways To Own Your Cybersecurity In 2020

  • Use single-sign-on (SSO) if available for systems at work, even if you’re logging in at the office. SSO systems use temporary tokens, which have proven to be more reliable than static credentials. One of the primary design goals of SSO is to authenticate your identity once, and give you access to the applications and system resources you need and are entitled to access to get work done.
  • Vault away passwords to critical systems and data. In the privileged access world of Cybersecurity operations in any organization, password vaults have become commonplace. Password vaults are similar to password managers many people use for their personal devices, web applications, and sites they regularly visit. In the case of a password vault, privileged credentials are checked in and out by admins, with each password automatically rotating to ensure greater randomization.
  • Enable security on all the devices you received over the holidays, starting with your WiFi router. If you’ve never set an admin password on your WiFi router and the two guest access points they typically have, now is a great time to do that. If you have an Amazon Echo or Google Home, manually disable the microphones. On the Echo, press the microphone button until the external ring turns red. On Google Home, use the small switch on the side to turn off the microphone..On an Amazon Alexa, it’s possible to review voice recordings associated with your account and delete the voice recordings one by one, by date range, by Alexa-enabled device, or all at once by visiting Settings > Alexa Privacy in the Alexa app or https://www.amazon.com/alexaprivacysettings. It’s a good idea to use PIN protection to disable voice purchases too. If you have Baby Monitors in your home, connect to them using a secured WiFi connection, not Bluetooth. Have everything behind your home firewall, so there’s a minimal number of threat surfaces in your home.
  • Take few of the many LinkedIn learning courses on practical cybersecurity to stay current on the latest techniques. LinkedIn Learning has 19 courses available today that are focused on practical cybersecurity steps you can take to protect your company’s systems and your own. You can find all the 19 courses here. LinkedIn Learning has 462 learning resources available today, available here. I’ve taken a few over a lunch break and have found them informative, interesting, and useful.
  •  Realize that you may be getting phishing and spear-phishing e-mails every week. Cybercriminals are becoming increasingly sophisticated in their use of browser plug-ins to pop up messages asking for your login and password information for sites. Combining the latest information from LinkedIn, Facebook, Twitter, and other sites, hackers often target new employees and with spearfishing campaigns where they impersonate a CEO and other senior-level executives. Spearfishing attempts can be easily thwarted by calling the supposed sender to ask if the request is legitimate. A second way to spot phishing and spear-fishing attempts is they will ask you for one or more of the pieces of information needed for completing a Multi-Factor Authentication (MFA) login to an account. Misspelled words, questionable e-mail addresses, and unsecured domains and websites are also a sure tip-off of a phishing attempt.
  • Bring Your Own Device (BYOD) greatly expands the enterprise attack surface. Define the success of a BYOD security strategy by how well it immediately shuts down access to confidential data and systems first. Being able to immediately block access to confidential systems and data is the most important aspect of securing any BYOD across a network. It’s common for BYOD enablement strategies to include integrations to Dropbox, Slack, Salesforce and Workday, Slack, Salesforce, and others.
  • Always use Multi-Factor Authentication (MFA) everywhere it’s offered. MFA is based on three or more factors that can authenticate who you are. Something you know (passwords, PINs, code works), something you have (a smartphone, tokens devices that produce pins or pre-defined pins) or something you are (biometrics, facial recognition, fingerprints, iris, and face scans). Google, for example, provides MFA as part of their account management to every account holder, in addition to a thorough security check-up, which is useful for seeing how many times a given password has been reused.

10 Ways To Own Your Cybersecurity In 2020

  • Determine where you and your company are from a privileged access maturity standpoint. Centrify shared the four stages of privileged access security on the webinar, and each phase is a useful benchmark for anyone or organization looking to improve their cybersecurity effectiveness. Centrify found in a recent survey that 42% of organizations are at the nonexistent phase of the model. As an organization progresses up the model, there’s greater accountability and visibility for each aspect of a cybersecurity strategy. For individuals, the progression is much the same, all leading to a lower risk of a breach and stolen privileged access credentials occurring.

10 Ways To Own Your Cybersecurity In 2020

Conclusion

While not every user in an organization is going to have privileged entitlements, it is up to every individual to take ownership of their cybersecurity hygiene to ensure they don’t become the most-easily-exploited employee in the company. That’s what the bad guys are looking for: the easiest way in. Why try to hack in against sophisticated technology when they can just guess your easy password, or get you to hand it over to them by phishing? Be cyber smart in 2020 – these ten tips might save you from being the weakest link that could cost your organization millions.

Five Factors Predicting The Future Of MacOS Management And Security

Bottom Line: Going into 2020, CISOs’ sense of urgency for managing their fleets of Android, Apple iOS & macOS, Windows Phone, and Windows 10 devices all from an integrated Unified Endpoint Management (UEM) is transforming the MacOS Management and Security landscape.

For many, CISOs, the highest priority project they’re starting the New Year with is getting their diverse fleet of devices on a common unified endpoint management platform. “We’ve gone through no less than a dozen UEMs (Unified Endpoint Management) systems, and they are either very good at supporting iOS and macOS or terrible at every other operating system or vice versa,” the CISO of a leading insurance and financial services firm told me over lunch recently. “Our sales, marketing, graphic artists, DevOps, and Customer Success teams all are running on Macs and iPhones, which makes it even more of a challenge to get everyone on the same endpoint management platform.” He went on to explain that the majority of macOS and iOS endpoint management systems aren’t built to support the advanced security he needs for protecting Android, Windows Phone, and Windows 10 devices.

Unified Endpoint Management is a key CISO priority in 2020

macOS and iOS devices had their own endpoint management tools in previous years when they were limited in use. Now they’re common in the enterprise and need to be considered part of an organization-wide fleet of devices, making it a high priority to add them to the unified endpoint management platform all other devices are on. Further accelerating this change is the success of BYOD policies that give employees the choice of using the tablets, smartphones, and laptops they’re the most productive with. One CISO told me their BYOD program made it clear macOS and iOS are the de facto standard across their enterprise.

While endpoint management platforms are going through an Apple-driven inflection point, forcing the need for a more inclusive unified endpoint management strategy, CISOs are focusing on how to improve application and content control at the same time. How enterprises choose to solve that challenge are predicting the future of MacOS management and security.

Five Factors Driving the Future of macOS Management and Security

CISOs piloting and only buying platforms that can equally protect every device operating system, macOS, and iOS’ rapidly growing enterprise popularity and better support for adaptive access are a few of the catalysts redefining the landscape today. The following five factors are defining how MacOS Management and Security will improve in 2020:

  • Enterprises need more effective endpoint and application management that includes Android, Apple iOS & macOS, Windows Phone, and Windows 10. There’s a major gap in how effective endpoint protection is across the UEM platforms today. Data-at-risk encryption and App distribution, or how well a UEM system can create, update, and distribute macOS applications are two areas cybersecurity teams are focusing on today.

Five Factors Predicting The Future Of MacOS Management And Security

  • System integration options needs to extend beyond log reports and provide real-time links to Security Information and Event Management (SIEM) systems. CISOs and their cybersecurity teams need real-time integration to incident management systems so they can be more effective troubleshooting potential breach attempts. Sharing log files across other systems is a first step, yet real-time integration is clearly what’s needed to protect enterprises’ many devices and threat surfaces today. The following Splunk dashboard illustrates the benefits of having real-time integration beyond log reports, encompassing SIEM systems:

Five Factors Predicting The Future Of MacOS Management And Security

  • UEM platforms that differentiate between corporate-owned and personal devices, content and authentication workflows, and data are defining the future of macOS Management and Security. Key factors that CISOs need in this area of unmanaged device support include more effective content separation, improved privacy settings, support for actions taken on personally-owned devices, and role-based privacy settings. MobileIron is a leader in this area, with enterprises currently using their role-based workflows to limit and verify access to employee-owned devices. MobileIron can also limit IT’s scope of control over an employee device, including turning off location tracking.
  • Support and proven integration of Identity solutions such as Okta, Ping Identity, Microsoft, and Single sign-on (SSO) are defining the future of adaptive access today. This is the most nascent area of UEM platform development today, yet the one area that CISOs need the greatest progress on this year. Endpoint protection and system integration are the two areas that most define how advanced a given UEM providers’ platform is today.
  • The ability to provision, revoke, and manage device certificates over their lifecycles is becoming a must-have in enterprises today. UEM platforms, in large part, can handle certificate device provisioning, yet Certificate Authority (CA) integration is an area many struggle with. CISOs are asking for more effective certificate lifecycle management, especially given the proliferation of macOS and iOS devices.

Conclusion

The five factors of MacOS management and security are transforming the Unified Endpoint Management (UEM) solution landscape. CISOs often speak of wanting to have a more integrated UEM strategy, one that can provide better SIEM system integration, differentiate between corporate-owned and personal devices, and also manage the lifecycles of device certificates. MobileIron has proven their ability to scale in a BYOD world and is a UEM vendor to watch in 2020.

10 Ways Asset Intelligence Improves Cybersecurity Resiliency And Persistence

10 Ways Asset Intelligence Improves Cybersecurity Resiliency And Persistence

Bottom Line: By securing every endpoint with a persistent connection and the resiliency to autonomously self-heal, CIOs are finding new ways to further improve network security by capitalizing on each IT assets’ intelligence.

Capturing real-time data from IT assets is how every organization can grow beyond its existing boundaries with greater security, speed, and trust. Many IT and cybersecurity teams and the CIOs that lead them, and with whom I’ve spoken with, are energized by the opportunity to create secured perimeterless networks that can flex in real-time as their businesses grow. Having a persistent connection to every device across an organizations’ constantly changing perimeter provides invaluable data for achieving this goal. The real-time data provided by persistent device connections give IT and cybersecurity teams the Asset Intelligence they need for creating more resilient, self-healing endpoints as well.

How Asset Intelligence Drives Stronger Endpoint Security 

Real-time, persistent connections to every device in a network is the foundation of a strong endpoint security strategy. It’s also essential for controlling device operating expenses (OPEX) across the broad base of device use cases every organization relies on to succeed. Long-term persistent connections drive down capital expenses (CAPEX) too, by extending the life of every device while providing perimeterless growth of the network. By combining device inventory and analysis, endpoint data compliance with the ability to manage a device fleet using universal asset management techniques, IT and cybersecurity teams are moving beyond Asset Management to Asset Intelligence. Advanced analytics, benchmarks, and audits are all possible across every endpoint today. The following are the 10 ways Asset Intelligence improves cybersecurity resiliency and persistence:

  • Track, trace and find lost or stolen devices on or off an organizations’ network in real-time, disabling the device if necessary. Every device, from laptops, tablets, and smartphones to desktops and specialized use devices are another threat surface that needs to be protected. Real-time persistent connections to each of these devices make track-and-trace possible, giving CIOs and their teams more control than had been possible before. Real-time track-and-trace data combined with device condition feedback closes security blind spots too. IT and cybersecurity teams can monitor every device and know the state of hardware, software, network and use patterns from dashboards. Of the endpoint providers in this market, Absolute’s approach to providing dashboards that provide real-time visibility and control of every device on a network is considered state-of-the-art. An example of Absolute’s dashboard is shown below:

10 Ways Asset Intelligence Improves Cybersecurity Resiliency And Persistence

  • Asset Intelligence enables every endpoint to autonomously self-heal themselves and deliver constant persistence across an organization’s entire network. By capitalizing on the device, network, threat, and use data that defines Asset Intelligence, endpoint agents learn over time how to withstand breach attempts, user errors, and malicious attacks, and most importantly, how to return an endpoint device to its original safe state. Asset Intelligence is the future of endpoint security as it’s proving to be very effective at enabling self-healing persistence across enterprise networks.
  • Asset Intelligence solves the urgent problem created from having 10 or more agents installed on a single endpoint that collide, conflict and decay how secure the endpoint is. Absolute Software’s 2019 Endpoint Security Trends Report found that the more agents that are added to an endpoint, the greater the risk of a breach. Absolute also found that a typical device has ten or more endpoint security agents installed, often colliding and conflicting with the other. MITRE’s Cybersecurity research practice found there are on average, ten security agents on each device, and over 5,000 common vulnerabilities and exposures (CVEs) found on the top 20 client applications in 2018 alone.
  • Asset Intelligence sets the data foundation for achieving always-on persistence by tracking every devices’ unique attributes, identifiers, communication log history and more. Endpoint security platforms need a contextually-rich, real-time stream of data to know how and when to initialize the process of autonomously healing a given endpoint device. Asset Intelligence provides the centralized base of IT security controls needed for making endpoint persistence possible.
  • Having a real-time connection to every device on a perimeterless network contributes to creating a security cloud stack from the BIOS level that delivers persistence for every device. CIOs and CISOs interested in building secured perimeterless networks are focused on creating persistent, real-time connections to every device as a first step to creating a security cloud stack from each devices’ BIOS level. They’re saying that the greater the level of Asset Intelligence they can achieve, the broader they can roll out persistence-based endpoints across their networks that have the capacity to self-diagnose and self-heal.
  • Device fleets are churning 20% a year or more, increasing the urgency CIOs have for knowing where each device is and its current state, further underscoring Asset Intelligence’s value. Gavin Cockburn of ARUP is the global service lead for workplace automation and endpoint management, including how the firm acquires devices, manages and reclaims them. ARUP is using the Absolute Persistence platform for managing the many high-value laptops and remote devices their associates use on global projects. During a recent panel discussion he says that device replacements “becomes part of our budgeting process in that 33% of devices that we do replace every year, we know where they are.” Gavin is also using API calls to gain analytical data to measure how devices are being used, if the hard drive is encrypted or not and run Reach scripts to better encrypt a device if there is not enough security on them.
  • The more Asset Intelligence an organization has, the more they can predict and detect malware intrusion attempts, block them and restore any damage to any device on their perimeter. When there’s persistent endpoint protection across a perimeterless network, real-time data is enabling greater levels of Asset Intelligence which is invaluable in identifying, blocking and learning from malware attempts on any device on the network. Endpoint protection platforms that have persistence designed in are able to autonomously self-heal back to their original state after an attack, all without manual intervention.
  • Persistent endpoints open up the opportunity of defining geofencing for every device on a perimeterless network, further providing valuable data Asset Intelligence platforms capitalize on. Geofencing is proving to be a must-have for many organizations that have globally-based operations, as their IT and cybersecurity teams need to track the device location, usage, and compliance in real-time. Healthcare companies are especially focused on how Asset Intelligence can deliver geofencing at scale. Janet Hunt, Senior Director, IT User Support at Apria Healthcare recently commented during a recent panel discussion that “our geo-fencing is extremely tight. I have PCs that live in the Philippines. I have PCs that live in India. I have one PC or actually two PCs that live in Indonesia. If somebody goes from where they say that they’re going to be to another part of Indonesia, that device will freeze because that’s not where it’s supposed to be and that’s an automatic thing. Don’t ask forgiveness, don’t ask questions, freeze the device and see what happens. It’s one of the best things we’ve done for ourselves.”  Gavin Cockburn says, “We actually do some kind of secretive work, government work and we have these secure rooms, dotted around the organization. So we know if we put a device in that room, what we do is, what we say is this device only works in this area and we can pinpoint that to a pretty decent accuracy.”  From healthcare to secured government contracting, geofencing is a must-have in any persistent endpoint security strategy.
  • Automating customer and regulatory audits and improving compliance reporting by relying on Asset Intelligence alleviates time-consuming tasks for IT and cybersecurity teams. When persistent endpoint protection is operating across an organization’s network, audit and compliance data is captured in real-time and automatically fed into reporting systems and dashboards. CIOs and their cybersecurity teams are using dashboards to monitor every device’s usage patterns, audit access, and application activity, and check for compliance to security and reporting standards. Audits and compliance reporting are being automated today using PowerShell, BASH scripts and API-based universal asset commands. Gavin Cockburn of ARUP mentioned how his firm gives customers the assurance their data is safe by providing them ongoing audits while project engagements are ongoing. “We need to show for our clients that we look after their data and we can prove that. And we show that again and again. I mean similar story, we’ve seen machines go missing, either breaking into cars, re-image three times. We wipe it every time. Put the new hard drive in, think it might be a hard drive issue, it wipes again. We never see it come online again, “ he said.
  • Asset Intelligence improves data hygiene, which has a direct effect on how effective all IT systems are and the customer experiences they deliver. CIOs and their teams’ incentives center on how effective IT is at meeting internal information needs that impact customer experiences and outcomes. Improving data hygiene is essential for IT to keep achieving their incentive plans and earning bonuses. As Janet Hunt, Senior Director, IT User Support at Apria Healthcare said, “right now we are all about hygiene and what I mean by that is we want our data to be good. We want all the things that make IT a valued partner with the business operation to be able to be reliable.” The more effective any organization is at achieving and sustaining a high level of data hygiene, the more secure their perimeterless network strategies become.

 

The Best Machine Learning Startups To Work For In 2020 Based On Glassdoor

The Best Machine Learning Startups To Work For In 2020 Based On Glassdoor

  • Duolingo, HOVER, Ironclad, Orbital Insight, People.ai, Dataiku, DeepMap, Cobalt, Aktana, Chorus.ai, Noodle Analytics, Inc. (Noodle.ai), Signal AI, Augury, SparkCognition, and KONUX are the most likely to be recommended by their employees to friends looking for a machine learning startup to work for in 2020.
  • 96% of the employees of the 15 highest rated machine learning startups would recommend their company to a friend looking for a new job, and 98% approve of their CEOs.
  • Across all machine learning startups with Glassdoor ratings, 74% of employees would recommend the startup they work for to a friend, and 81% approve of their CEO.
  • There are over 230 cities globally who have one or more machine learning startups in operation today with Crunchbase finding 144 in San Francisco, 60 in London, 69 in New York, 82 in Tel Aviv, 22 in Toronto, 20 in Paris, 18 in Seattle and the remainder distributed over 223 global locations.

These and many other insights are from a Crunchbase Pro analysis completed today using Glassdoor data to rank the best machine learning startups to work for in 2020. Demand reminds high for technical professionals with machine learning expertise.  According to Indeed, Machine Learning Engineer job openings grew 344% between 2015 to 2018 and have an average base salary of $146,085 according to their  Best Jobs In The U.S. Study. You can read the study shows that technical professionals with machine learning expertise are in an excellent position to bargain for the average base salary of at least $146,085 or more.

Methodology

In response to readers’ most common requests of which machine learning startups are the best to work for, a Crunchbase Pro query was created to find all machine learning startups who had received Seed, Early Stage Venture, or Late Stage Venture financing. The 2,682 machine learning startups Crunchbase is tracking were indexed by Total Funding Amount by startup to create a baseline.

Next, Glassdoor scores of the (%) of employees who would recommend this company to a friend and (%) of employees who approve of the CEO were used to find the best startups to work for. 79 of the 150 machine learning startups have 15 or more Glassdoor reviews and are included in the analysis. 41 have less than 15 reviews and 30 have no reviews. The table below is a result of the analysis, and you can find the original Microsoft Excel data set here.

The Best Machine Learning Startups To Work For In 2020 Based On Glassdoor

 

 

10 Ways AI Is Going To Improve Fintech In 2020

Bottom Line: AI & machine learning will improve Fintech in 2020 by increasing the accuracy and personalization of payment, lending, and insurance services while also helping to discover new borrower pools.

Zest.ai’s 2020 Predictions For AI In Credit And Lending captures the gradual improvements I’ve also been seeing across Fintech, especially at the tech stack level. Fintech startups, enterprise software providers, and the investors backing them believe cloud-based payments, lending, and insurance apps are must-haves to drive future growth. Combined with Internet & public cloud infrastructure and mobile apps, Fintech is evolving into a fourth platform that provides embedded financial services to any business needing to subscribe to them, as Matt Harris of Bain Capital Ventures writes in Fintech: The Fourth Platform – Part Two. Embedded Fintech has the potential to deliver $3.6 trillion in market value, according to Bain’s estimates, surpassing the $3 trillion in value created by cloud and mobile platforms. Accenture’s recent survey of C-suite executives’ adoption and plans found that 84% of all executives believe they won’t achieve their growth objectives unless they scale AI, and 75% believe they risk going out of business in 5 years if they don’t. The need to improve payment, lending and insurance combined with customers’ mercurial preferences for how they use financial services are challenges that AI and machine learning (ML) are solving today.

How AI & Machine Learning Will Improve Fintech In 2020

Fintech’s traditional tech stacks weren’t designed to anticipate and act quickly on real-time market indicators and data; they are optimized for transaction speed and scale. What’s needed is a new tech stack that can flex and adapt to changing market and customer requirements in real-time. AI & machine learning are proving to be very effective at interpreting and recommending actions based on real-time data streams. They’re also improving customer experiences and reducing risk, two additional factors motivating lenders to upgrade their traditional tech stacks with proven new technologies.

The following are ten predictions of how AI will improve FinTech in 2020, thank you Zest.ai for your insights and sharing your team’s expertise on these:

  1. Zest predicts lenders will increase the use of ML as the way to grow into the no-file/thin-file segments, especially rising Gen Zers with little to no credit history. Traditional tech stacks make it difficult to find and grow new borrower pools. Utah-based auto lenderPrestige Financial Services chose to rely on an AI solution instead. The chose Zest AI to find and cultivate a borrower pool of people in the 19-35 age group. Using an AI-based loan approval workflow, Prestige was able to increase loan approval rates by 25%, and for people under 20 by threefold.
  2. Mortgage lenders’ adoption of AI for finding qualified first-time homeowners is going to increase as more realize Gen Z (23 – 36-year-olds) are the most motivated of all to purchase a home. In 2020, long-standing assumptions about first-time homebuyers and their motivations are going to change. A recent story in HousingWire, “This generation is the most willing to do whatever it takes to buy a home,” explains that Gen Z, or those people born between 1996 and 2010, are the most likely to relocate to purchase a new home. A recent TransUnion market analysis found 70% of Gen Z prospective home buyers are willing to relocate to buy their first home, leading all active generations. 65% of Gen Xers, or those born between 1965 to 1980, were the second most likely to move. AI and ML can help lenders more precisely target potential Gen Z first-time homebuyers, measuring the impact of their marketing campaigns on attracting new borrowers. The TransUnion market analysis finds that 58% of respondents are delaying a home purchase due to anticipated high down payments or monthly payments. 51% said the need to obtain a 10% to 20% down payment was stopping them. According to Joe Mellman, TransUnion senior vice president, and mortgage business leader, “Many of our potential first-time homebuyer respondents don’t seem to be aware of the wide variety of financing options available to them.” The TransUnion market analysis found that many of the potential first-time homeowner respondents have never heard of low down-payment options from Fannie Mae, Freddie Mac, or of the Federal Housing Administration.
  3. Zest predicts banks and other financial institutions will strengthen their business cases for AI pilots and production-level deployments by recognizing the operating expense (OPEX) savings of ML. Several recurring costs involved in developing, validating and deploying credit risk models can be reduced or cut by switching to machine learning, according to Zest. Lenders can get the most out of their data acquisition spending by using modern ML tools to assess which data sources yield the most predictive power for a model. Lenders will also switch to ML to simplify their IT and risk operations by consolidating into fewer models that can do the work of what used to be multiple individual linear models for every customer segment.
  4. Compliance cost growth will decline even faster due to ML. Financial institutions that have AI/ML algorithms in production log every change in a model and can produce all the required model risk governance documents in minutes instead of a compliance team manually taking weeks to do it. Automated tools also shrink the time it takes to do fair lending testing by building less discriminatory models on the fly rather than the time-intensive approach of drop-one-variable-and-test. Time is money, especially in lending.
  5. AI and ML will gain critical mass in collections, providing insights into which approach is the most effective for a given customer. Zest has built collections models for a few financial services firms and has found them to be very effective. Collections logic, predicting which customers to wait on when bills are past due, is a strong fit for machine learning. With one bank, Zest found that ML models can, for example, accurately target the borrowers most likely to make a certain minimum payment based on the value of their loan within 60 days of falling behind their due date. In three months, Zest built two models from traditional credit bureaus and the bank’s proprietary collections metrics to predict this repayment propensity of borrowers. One insight into the data was that borrower behavior accounted for just over half of the bank’s ability to collect missed payments, but operations played a significant role.
  6. If there’s a downturn, ML will get blamed (even though it can actually help in a downturn). Pankaj Kulshreshtha, CEO of Scienaptics, originally made this observation at the Money 20/20 Conference held earlier this year. Models built only in good times can see their correlations break when times go bad. Lenders who observe best practices in AI and ML adoption will make sure to stress-test their models, perhaps by including synthetic data to add heterogeneity. Better ML monitoring will be important, too. “ML models and algorithmic monitors can do a better job seeing around corners, spotting rising numbers of inbound outlier applicants that signal more volatile conditions ahead,” says Seth Silverstein, Executive Vice President of Credit Risk Analytics for Zest AI.  An effective ML monitoring tool should excel at spotting outlier applicants and feature drift, ensuring more accurate model outcomes.
  7. 2020 is going to be a break-out year for partnerships and co-opetition as payments, lending and insurance firms vie for a growth position in embedded financial services. Matt Harris of Bain Capital Ventures’ prediction of embedded fintech suggests a proliferation of cloud-based Fintech apps around the core: payments, lending, insurance. That creates an ideal situation for AI-related alliances and partnerships among the incumbent lenders, startups, data aggregators and the CRAs. To Harris, the layers of the stack are centered around connectivity, intelligence, and ubiquity. According to Crunchbase, there have been 51 Fintech acquisitions in 2019 alone. Plaid’s acquisition of Quovo in January for approximately $200 million and Fiserv’s acquisition of First Data reflect how Fintechs are creating their own unique tech stacks already.
  8.  Zest predicts Fintechs will seek out AI and ML modeling expertise more so than build expertise and teams on their own, which will be costlier and take longer. Embedded Fintech’s future adoption rate is predicated on how effective development efforts are today at minimizing incidental bias and providing customers with greater visibility into how and why models provide specific results “Some of these startups are bringing their own data science and ML models. We have to hope these firms own, build, or buy the tools to ensure their models are inclusive, free of incidental bias, and use transparent AI customers can trust. We see explainable AI as being an essential feature or service in that tech stack,” says Zest’s Silverstein.
  9.  Fintechs will rely on AI and ML to help close the talent gap each of them has today while also improving the effectiveness of their talent management strategies. Finding, recruiting, and hiring the best candidates for development, engineering, marketing, sales, and senior management roles is an area Fintechs will increasingly adopt AI and ML for in 2020. Fintech CEOs and CHROs will begin upskilling programs for themselves and their teams to increase AI fluency and skills mastery in 2020. According to a recent Harris Interactive survey completed in collaboration with Eightfold titled Talent Intelligence And Management Report 2019-2020, 73% of U.S. CEOs and CHROs plan to use more AI in the next three years to improve talent management.
  10. Credit unions will adopt ML in 2020 to automate routine tasks and free up human underwriters to focus on providing more personalized services, including improvements in inquiry resolution & dispute and fraud management. Credit unions are built on an annuity-based business model that delivers successively higher profitability the longer a member is retained. Credit unions will capitalize on ML by driving up loan approvals with no added risk and automating more of the loan approval process. By the end of 2020, according to a Fannie Mae survey of mortgage lenders, 71% of credit unions plan to investigate, test, or fully implement AI/ML solutions – up from just 40% in 2018. AI and ML will also be adopted across credit unions to improve inquiry resolution & dispute and fraud management while improving multichannel customer experiences. Providing real-time, relevant responses to customers to expedite inquiries and dispute resolutions using AI and ML is going to become commonplace in 2020. AI and ML are predicted to make a significant contribution to automating anomaly detection and borrower default risk assessment as the graphic below from Fannie Mae’s Mortgage Lender Sentiment Survey® How Will Artificial Intelligence Shape Mortgage Lending? Q3 2018 Topic Analysis illustrates:

 

 

Predicting How AI Will Improve Talent Management In 2020

Predicting How AI Will Improve Talent Management In 2020

47% of U.S.-based enterprises are using AI today for recruitment, leading all countries in the survey. U.S.-based enterprises’’ adoption of AI for recruitment soared in the last year, jumping from 22% in 2018 to 47% this year based on last years’ Harris Interactive Talent Intelligence and Management Report 2018.

  • 73% of U.S. CEOs and CHROs plan to use more AI in the next three years to improve talent management.
  • U.S.-based enterprises’’ adoption of AI for recruitment soared in the last year, jumping from 22% in 2018 to 47% this year.
  • U.S.-based enterprises lead in the use of AI to automate repetitive tasks (44%) and employee retention (42%).

These and many other fascinating insights are from a recent study completed by Harris Interactive in collaboration with Eightfold titled Talent Intelligence And Management Report 2019-2020, which provides insights into how CHROs are adopting AI today and in the future. You can download a copy here. A total of 1,350 CEOs and CHROs from the U.S., France, Germany, and the U.K. responded to the survey. One of the most noteworthy findings is how U.S-based CEOs and CHROs lead the world in prioritizing and taking action on improving their teams and their own AI skills. The more expertise they and their teams have with AI, the more effective they will be achieving operational improvements while taming the bias beast. The following graphic provides insights into how the four nations surveyed vary by their CEOs’ and CHROs’ perception of new technologies having had positive impacts, their plans for using AI in three years, and employee’s concerns about AI:

Predicting How AI Will Improve Talent Management In 2020

Predicting The Future Of AI In Talent Management

Four leading experts who are actively advising clients, implementing, and using AI to solve talent management challenges shared their predictions of how AI will improve talent management in 2020. The panel includes Kelly O. Kay, Partner, Heidrick & Struggles, Jared Lucas, Chief People Officer at MobileIron, Mandy Sebel, Senior Vice President, People at UiPath and David Windley CEO, IQTalent Partners. Mr. Kay leads the Software Practice for Heidrick & Struggles, a leading executive search and consulting firm commented: “As we all know, the talent crisis of 2019 is real and Eightfold’s application of AI on today is the most impactful approach I’ve seen and the outcomes they deliver eliminate unconscious bias, increases transparency and improves matching supply and demand of talent.” The following are their predictions of how AI will improve the following areas of talent management in 2020:

  • “Pertaining to talent attraction & acquisition-as adoption of intelligent automation and AI tools increases hiring managers and recruiters more easily uncover and surface overlooked talent pools,” said Mandy Sebel, Senior Vice President, People at UiPath.
  • “I predict that AI will become a requirement for companies in the screening of candidates due to the pervasive need to find higher-quality candidates at a faster pace,” said Jared Lucas, Chief People Officer at MobileIron.
  • “I believe the use of AI in the talent acquisition space will begin to hit critical mass in 2020. We are still in the early adopter phase, but the use of AI to match potential candidates to job profiles is catching on. Especially the use of AI for rediscovering candidates in ATS systems of larger corporations. Companies like Eightfold, Hiretual, and Atipica are leading the way,” said David Windley CEO, IQTalent Partners.
  • “Fear of job replacement will also subside, and more focus on job/role evolution as teams are experiencing firsthand how respective task elimination allows them to do more meaningful work,” commented Mandy Sebel, Senior Vice President, People at UiPath.
  • AI will provide the insights needed for CHROs to retain and grow their best talent, according to Jared Lucas, Chief People Officer at MobileIron. “I predict that AI will drive better internal mobility and internal candidate identification as companies are better able to mine their internal talent to fill critical roles,” he said.
  • Having gained credibility for executive and senior management recruiting, AI platforms’ use will continue to proliferate in 2020. “Private Equity is beginning to commercialize how AI can help select executives for roles based on competencies and experiences, which is exciting!” said Kelly O. Kay, Partner, Heidrick & Struggles.

Top 25 AI Startups Who Raised The Most Money In 2019

Top 25 AI Startups Who Raised The Most Money In 2019

  • $10.7B was invested in AI startups this year in their seed, early-stage venture, or late-stage venture funding rounds.
  •  Over half, or 57.9% of all AI startup financing rounds where either seed or pre-seed, 21.2% are Series A, 11.8% are Series B, and all others comprise 9% of all funding rounds.
  • The median AI startup funding round generated $4M with the average being $14.6M and the maximum, $319M, obtained by Vacasa.

These and many other fascinating insights are from an analysis of AI startups’ funding rounds in 2019 using Crunchbase Pro research. AI startups who have had seed, early-stage venture or late-stage venture funding since December 31, 2018, and are U.S.-based are included in the analysis which is provided here. Crunchbase Pro found 499 startups meeting the search criteria as of today.

Top 25 AI Startups Who Have Raised The Most Money In 2019

  1. Vacasa – Raised $319M from a Series C round on October 29th, Vacasa is creating and using AI-driven tools to improve their customers’ experiences renting vacation homes around the world. Their AI strategies include improving every aspect of the customer’s lifecycle from pricing through scheduling post-stay cleans. The company manages a growing portfolio of more than 14,000 vacation homes in the U.S, Europe, Central, and South America, and South Africa.
  2. Samsara – Raised $300M from a Series F round on September 10th. Samsara is an IoT platform combining hardware, software, and cloud to bring real-time visibility, analytics, and AI to operations. Samsara’s portfolio of Internet of Things (IoT) solutions combine hardware, software, and cloud to bring real-time visibility, analytics, and AI to operations. Their core strengths include vehicle telematics, driver safety, mobile workflow and compliance, asset tracking, and industrial process controls all in an integrated, open, real-time platform.
  3. TripActions – Raised $250M from a Series D round on June 27th. TripActions is a business travel platform that combines the latest AI-driven personalization with inventory and 24×7 365 live human support to serve employees, finance leaders, and travel managers alike all while empowering organizations to seize travel as a strategic lever for growth.
  4. ThoughtSpot – Raised $248M from a Series E round on August 22nd. ThoughtSpot’s AI-Driven analytics platform enables business analyst to capitalize on the expertise and shared knowledge of experienced data scientists. With ThoughtSpot, business analysts can analyze data or automatically get trusted insights pushed to you with a single click. ThoughtSpot connects with any on-premise, cloud, big data, or desktop data source. Business Intelligence and Analytics teams have used ThoughtSpot to cut reporting backlogs by more than 90% and make more than 3 million decisions and counting.
  5. CloudMinds – Raised $186M from a Series B round on February 23rd. Founded in 2015, CloudMinds’ unique Cloud Robot Service Platform consists of Human Augmented Robotics Intelligence with Extreme Reality (HARIX), a Secure virtual backbone network (VBN over 4G/5G), and Robot Control Unit (RCU). Designed by CloudMinds, XR-1 Robot is the first commercial humanoid service robot powered by our Smart Compliant Actuator (SCA) technology with precise and compliant grasping capability. Their AI Cloud Brain platform (HARIX) is designed to enable robotic intelligence through a secured network over 4G/5G. CloudMinds is focused on several core technologies, including Smart Vision, Smart Voice, Smart Motion and Human Augmentation. The following is an overview of their architecture:

Top 25 AI Startups Who Raised The Most Money In 2019

  1. Icertis – Raised $115M from a Series E round on July 17th. Icertis is an enterprise contract management platform in the cloud that solves contract management problems using AI. Using advanced algorithms, Icertis helps its customers accelerate business cycles by increasing contract velocity, protecting against risk by ensuring regulatory and policy compliance and optimizing the commercial relationships by maximizing revenue and reducing costs. 3M, Airbus, Cognizant, Daimler, Microsoft, and Roche who rely on Icertis to manage 5.7 million contracts in 40+ languages across 90+ countries, are all customers. The following is an overview of the Icertis Contract Management Platform:

Top 25 AI Startups Who Raised The Most Money In 2019

  1. SparkCognition – Raised $100M from a Series C round on October 8th. SparkCognition builds artificial intelligence systems focused on the needs of its customers in the aviation, cybersecurity, defense, Financial Services, manufacturing, maritime, and Utilities industries. SparkCognition offers four main products: DarwinTM, DeepArmor, SparkPredict, and DeepNLPTM. One of their most noteworthy products is DeepArmor, an AI-powered endpoint security solution that has trained on millions of malicious and benign files and provides industry-leading protection against a broad spectrum of threats. With millions of new malware variants showing up each month, DeepArmor uses AI to assess risk levels and thwart malware and break attempts. DeepArmor’s dashboard is shown below:

Top 25 AI Startups Who Raised The Most Money In 2019

  1. Vectra AI – Raised $100M from a Series E round on June 10th. Vectra specializes in network detection and response – from cloud and data center workloads to user and IoT devices. Its Cognito platform accelerates threat detection and investigation using artificial intelligence to collect, store, and enrich network metadata with the right context to detect, hunt and investigate known and unknown threats in real-time.
  2. Globality – Raised $100M from a Series D round on January 22nd. The January round enabled Globality to accelerate its growth through investment in its AI technology, increasing business capacity by hiring additional members of its engineering, product, and client teams, and expanding its Marketing and Sales programs. Through its AI-powered Platform, Globality is automating the procurement of B2B services and improving the RFP process. Globality efficiently matches companies with service providers that meet their specific needs, cutting the sourcing process from months to hours, and delivering savings of 20% or more for companies.
  3. Black Sesame Technologies – Raised $100M from a Series B round on April 12th.  Black Sesame Technologies is an AI digital imaging technology firm provides solutions for image processing and computing images, as well as embedded sensing platforms. The firm specializes in algorithms for smartphones, autonomous driving, and other consumer electronics. Its R & D teams are actively working on core algorithm development, ASIC design, software system, and ADAS engineering applications.
  4. Scale – Raised $100M from a Series C round on August 5th. Scale accelerates the development of AI applications by helping computer vision teams generate high-quality ground truth data. Our advanced LiDAR, video, and image annotation APIs allow self-driving, drone, and robotics teams at companies like Waymo, OpenAI, Lyft, Zoox, Pinterest, and Airbnb focus on building differentiated models vs. labeling data. Scale’s greatest strength is its API for training data, providing access to human-powered data for a multitude of use cases.
  5. AutoX – Raised $100M from a Series A round on September 16th. AutoX is a self-driving car startup that uses AI to fine-tune Location-Based Services with camera-first autonomous driving technology. In July of this year, AutoX announced a partnership with NEVS, the Swedish holding company, and electric vehicle manufacturer that bought Saab’s assets out of bankruptcy, to deploy a robotaxi pilot service in Europe by the end of 2020.
  6. DISCO – Raised $83M from a Series E round on January 24th. DISCO is a legal technology company that applies artificial intelligence and cloud computing to legal problems to help lawyers and legal teams improve legal outcomes for clients. Corporate legal departments, law firms, and government agencies around the world use DISCO as an ediscovery solution for compliance, disputes, and investigations. The company is looking to reinvent legal technology to automate and simplify complex and error-prone tasks that distract from practicing law.
  7. QOMPLX – Raised $78.6M from a Series A round on July 23rd. QOMPLX makes it faster and easier for organizations to integrate disparate internal and external data sources across the enterprise via a unified analytics infrastructure that supports better decision-making using AI at scale. This enterprise data-fabric is called QOMPLX OS: an enterprise operating system that powers QOMPLX’s decision platforms in cybersecurity, insurance, and quantitative finance. The following is an example of how the QOMPLX OS automates data management while providing greater contextual intelligence to data:

Top 25 AI Startups Who Raised The Most Money In 2019

  1. Galileo Financial Technologies – Raised $77M from a Series A round on October 17th. Galileo’s APIs are used widely throughout the neobank, payments, gig economy, investing and SaaS market segments. As of September 2019, Galileo was managing over $26B in annual payments volume, a 130% increase over September 2018. Galileo’s latest round, a $77M investment led by venture capital firm Accel with participation from Qualtrics Co-Founder & CEO Ryan Smith. The company, which is already profitable and growing rapidly, plans to use the funds to accelerate growth, including expansion into Latin America, the UK, and Europe, and for continued product expansion.
  2. BlackThorn Therapeutics – Raised 76M from a Series B round on June 13th. BlackThorn Therapeutics, Inc., is a clinical-stage neurobehavioral health company pioneering the next generation of AI technologies to advance its pipeline of targeted therapeutics for treating brain disorders. The company has engineered PathFinder, a cloud-based computational psychiatry and data platform, to enable the collection, integration, and analysis of multimodal data at great speed and scale. BlackThorn applies its data-driven approaches to create an understanding of the core underlying pathophysiology of neurobehavioral disorders and uses these insights to generate objective neuromarkers, which support drug target identification, patient stratification, and objective clinical trial endpoints.
  3. Highspot – Raised $75M from a Series D round on December 3rd. Highspot is a sales enablement platform that relies on AI technologies to elevate and add value to companies’ conversations with their customers and drive strategic growth. The platform combines intelligent content management, training, contextual guidance, customer engagement, and actionable analytics. Revenue teams use Highspot to deliver a unified buying experience that increases revenue, customer satisfaction and retention. Highspot has attained a 90% average monthly recurring usage rate and has global support across 125 countries. It’s available on the Salesforce AppExchange, Microsoft Store, Google Play and Apple AppStore.
  4. Moveworks – Raised $75M from a Series B round on November 11th. Moveworks is a cloud-based AI platform designed for large enterprises’ IT support and service desk challenges. Instead of just tracking issues, Moveworks uses advanced AI to solve IT support and service problems automatically, often with no human intervention. Customers include AutoDesk, Broadcom, Nutanix and many other Fortune 500 companies. Moveworks is backed by Bain Capital Ventures and Lightspeed Venture Partners and is headquartered in Mountain View, California.
  5. Reonomy – Raised $60M from a Series D round on November 7th. Reonomy is an AI-powered data platform for the commercial real estate industry. The goal of the company’s platform is to leverage big data, partnerships, and machine learning to connect the fragmented world of commercial real estate. Reonomy products enable individuals, teams, and companies to unlock new insights from property intelligence. By constantly aggregating and organizing up-to-the-minute marketplace data, Reonomy offer investors and brokers the opportunity to research nuanced property characteristics that indicate the likelihood of a future sale. Below is an example of an analysis of the San Francisco neighborhood using AI-based filtering technology:

Top 25 AI Startups Who Raised The Most Money In 2019

  1. Clari – Raised $60M from a Series D round on October 10th. Clari is a connected revenue operations platform that uses automation and AI to unlock all the activity data captured in key business systems such as marketing automation, CRM, email, calendar, phone, content management, and conversations. It automatically aligns that data to accounts and opportunities to deliver visibility, forecasting, and apply predictive insights, which results in more insight, less guesswork, and more predictable revenue. Clari helps companies by changing their revenue operations to be more connected, efficient, and predictable. Clari’s platform is used by hundreds of sales, marketing, and customer success teams at B2B companies such as Qualtrics, Lenovo, Adobe, Dropbox, and Okta to control pipeline, audit deals and accounts, forecast the business, and reduce churn. The following is an example of a Clari dashboard:

Top 25 AI Startups Who Raised The Most Money In 2019

  1. People.ai – Raised $60M from a Series C round on May 21st. People.ai is an artificial intelligence (AI) platform for enterprise revenue. People.ai helps sales, marketing, and customer success teams uncover every revenue opportunity from every customer by capturing all customer contacts, activity, and engagement to drive actionable insights across all revenue teams. People.ai enables sales leaders to be more effective at managing their teams and growing revenue by giving them a complete picture of sales activities and leveraging AI to deliver sales performance analytics, personalized coaching, one-on-one feedback, and pipeline reviews. The People.ai platform identifies and targets the buying group, and gives marketers a clear visualization of whom sales have spoken with, and which campaign has been successful in each opportunity. Using this information, marketers are able to build personas and deal models in order to better target their marketing efforts and get better campaign ROI. Customer success and services teams use People.ai to ensure they are engaging with the right people when the customer is handed off to them, but more importantly, these post-sales teams are constantly looking to align their effort and activities with the right opportunities and customers, tracking the true cost to support each customer. The following graphic illustrates the People.ai platform automatically capture all contact and customer activity data, dynamically update your CRM, and provide actionable intelligence to realize the full potential of customer-facing teams. The following graphic illustrates the People.ai platform:

Top 25 AI Startups Who Raised The Most Money In 2019

 

  1. Invoca – Raised $56M from a Series C round on October 17th. Invoca is an AI-powered call tracking and analytics platform that helps marketers drive inbound calls and turn them into sales. The platform delivers real-time call analytics to help marketers take informed actions based on data generated before and during a phone conversation. It also allows marketers to understand, in real-time, the factors affecting consumers’ intent to buy, like competitive promotional campaigns. Marketers can put the data to work directly in the platform by automating customer experience workflows during, before, and after each call. Invoca’s platform integrates with Google Marketing Platform, Facebook, Adobe Experience Cloud, and Salesforce Sales and Marketing Clouds. Invoca’s investors include Accel Partners, H.I.G. Growth Partners, Upfront Ventures, Morgan Stanley Alternative Investment Partners, Salesforce Ventures, and Rincon Venture Partners. The following is an example of an Invoca dashboard used for measuring Google AdWords effectiveness:

Top 25 AI Startups Who Raised The Most Money In 2019

  1. Clinc – Raised $52M from a Series B round on May 20th.  Clinc is a conversational AI platform that enables enterprises to build “human-in-the-room” level, next-gen, virtual assistants. In contrast to a speech-to-text word matching algorithm, Clinc analyzes dozens of factors from the user’s input including wording, sentiment, intent, tone of voice, time of day, location, and relationships, and uses those factors to deliver an answer that represents a composite of knowledge extracted from its trained brain. Clinc’s underlying technology is based on state-of-the-art machine learning and deep neural networks (DNN)-as-a-service developed by computer science professors at the University of Michigan. Clinc is a standalone “trained brain” that has been given an initial deep knowledge of the financial and banking industry. Its machine learning capabilities enable it to expand its knowledge with every query and to then draw from that knowledge for each subsequent customer query.
  2. Biz2Credit – Raised $52M from a Series D round on June 4th. Biz2Credit is a hub connecting small business owners with lenders and service providers, and seek solutions based on their online profiles. Biz2X uses a streamlined user interface, AI-driven analytics, and a customizable white label environment to help banks enhance their core services such as offering focused customer service, growing their portfolio, and increasing the use of their products. With enhanced loan management, servicing, risk analytics and a configurable customer journey, Biz2X is helping banks like these run their lending operations at scale.
  3. Uniphore – Raised $51M from a Series C round on August 13th. Uniphore is a global Conversational AI technology company that offers a customer service platform that is powered by AI and automation technologies. The Company’s vision is to bridge the gap between people and machines through voice. Uniphore enables businesses globally to deliver transformational customer service by providing a platform of Conversational Analytics, Conversational Assistant, and Conversational Security that changes the way enterprises engage their consumers, build loyalty and realize efficiencies.

 

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