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Deep Labs Featured in Biometric Update on Behavioral Biometrics and Persona-Based Security Intelligence

A number of companies on the market today are exploring behavioral-based security, which relies on an individual’s unique behavior patterns such as the way a person types, how hard the buttons are pressed, how quickly a person holds a device for secure and more accurate authentication. They argue it is superior to the already popular authentication methods that leverage biometric facial or fingerprint recognition, because behavioral-based security performs continuous authentication by analyzing real-time interaction with a device.

Deep Labs, a Silicon Valley-based startup founded in 2016, develops artificial intelligence security tools for banks and credit card companies. The company uses artificial intelligence and machine learning to leverage the power of behavioral biometrics to develop the concept of persona-based intelligence. According to its CEO and co-founder, Dr. Scott Edington, behavior-based security has reached a higher level of sophistication, because it would be nearly impossible for fraudsters to fake how a person types their password or holds their phone. If a user’s phone is used even in a slightly different way, the action is immediately flagged.

Read the full interview here.

Deep Labs Featured in Digital Journal on Persona-Based Intelligence™ and Behavior-Based Security

How someone holds their phone is becoming a criteria for securing their identity from hackers. If you usually hold it with your right hand, and a left-handed hacker is trying to gain access to your phone, they can be stopped because of that difference.

According to the CEO of Deep Labs, Scott Edington, such activities are becoming part of a vastly improved behavioral-based security approach that is taking ID verification to new levels. Behavior-based security is starting to look much more at how users hold their phones, how hard they press the buttons, and how quickly they might type.

Digital Journal spoke with Scott Edington about how artificial intelligence and machine learning can help to create user ‘personas’, that red flag if your phone is being used even slightly differently than how you use it.

Read the full interview here.

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Deep Labs Featured in Payments Source on How Real Time Payments Require Real Time Defenses

Globally, both consumers and businesses now have the expectation of real time payments and transactions. With the exponential increase in customers performing real time payments than ever before, it’s not surprising that fraudsters continue to seek ways to exploit the digital channel where such payments are performed.

This makes it imperative to utilize the latest approaches to mitigate risk and defend against attacks. Existing legacy authentication measures that protect accounts such as login credentials and biometric authentication are important but have been proven to be circumvented by fraudsters.

Account takeover has continued to rise, with several contributing factors, including data breaches, social engineering, poor consumer hygiene on passwords and slower than desired adoption of biometrics, and the increasing sophistication of fraudsters by using bots and crimeware.

Read the full article here.

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Deep Labs Featured in Credit Union Times on How Real-Time Payments Are Sparking Fraud Worries

Real-time payments may be booming, but they may also be growing targets for fraud — and credit unions and other financial institutions are getting worried, an industry pro warned this week.

The payment method, which allows financial institutions and members to pay bills and make payments almost instantaneously, can also enable criminals to avoid evade manual reviews, security measures that identify out-of-pattern activity and ACH service blocks, said Mike Lynch, who is chief strategy officer at San Francisco-based risk-profiling company Deep Labs. Growing account takeover activity, poor consumer password hygiene and social engineering vulnerabilities, among other things, may be helping criminals exploit real-time payments, he said.

“We have the perfect storm of many different factors at a high level, and now we’re moving money in real-time and we need to have a lot more security layers behind the scenes,” he said. “We can’t just have a rules-based approach. We need to correlate a lot of signals. So here is where you use device intelligence and behavioral analytics, et cetera.”

Real-time payment platforms aren’t necessarily the vehicles through which criminals are stealing data; they’re often the vehicles through which criminals can quickly exploit stolen data.

“It’s the tricking through social engineering or spoof calls for phishing,” he said. “That’s growing to be a pretty common technique and customers may be tricked into transferring funds to someone and never receiving the goods. So it looks like the money’s appeared in the seller’s account, but then a few days later [the platform] reverses the transaction.”

Credit unions and other financial institutions involved with real-time payment platforms should make sure they’re following best practices in terms of P2P security.

Read the full article here.

account takeover behavior analytics deep learning device recognition fraud detection fraud prevention Identity machine intelligence Open Banking Payments PSD2 real time payments risk analysis risk engine risk profiling signals intelligence supervised machine learning unsupervised machine learning

Deep Labs Featured in Bank Business on Whether Open Banking will come to the United States.

Bank sign on marble background. 3d illustration

Deep Labs Michael Lynch discusses in this Bank Business article whether open banking will come to the United States and if banks should start planning for it now.

Open banking is currently mandated in the EU, via a European directive. The regulation behind open banking is the second Payment Services Directive (PSD2). Open banking is designed to permit consumers’ data to be used by third party providers and thereby increase the competition and quality of products in the banking, payments, and credit cards space. Other benefits include ways to save consumers money with better interest rates or cash incentives, as well as making it easier to switch accounts, or to permit consumers’ data to be used by third party providers for helpful tools such as creating a dashboard of all their financial accounts.

PSD2’s main goal is to increase commerce, create a consumer-friendly ecosystem, while ensuring that the consumers’ data remains secure in the process.

One continual question is will we see open banking come to the United States under similar regulations? It is only matter of speculation at this point, but it seems thus far in the U.S. that the private sector will trend towards similar capabilities without a regulatory mandate.

Read the full article here.

account takeover behavior analytics deep learning device recognition fraud detection fraud prevention Identity machine intelligence Open Banking Payments PSD2 risk analysis risk engine signals intelligence supervised machine learning unsupervised machine learning

Deep Labs Featured in Credit Union Business on Whether Open Banking will come to the United States.

In this article, Deep Labs Chief Strategy and Product Officer, Michael Lynch discusses whether open banking will come to the United States and if banks and credit unions should start planning for it now.

Open banking is currently mandated in the EU, via a European directive. The regulation behind open banking is the second Payment Services Directive (PSD2). Open banking is designed to permit consumers’ data to be used by third party providers and thereby increase the competition and quality of products in the banking, payments, and credit cards space. Other benefits include ways to save consumers money with better interest rates or cash incentives, as well as making it easier to switch accounts, or to permit consumers’ data to be used by third party providers for helpful tools such as creating a dashboard of all their financial accounts.

PSD2’s main goal is to increase commerce, create a consumer-friendly ecosystem, while ensuring that the consumers’ data remains secure in the process.

One continual question is will we see open banking come to the United States under similar regulations? It is only matter of speculation at this point, but it seems thus far in the U.S. that the private sector will trend towards similar capabilities without a regulatory mandate.

Read the full article here.

account takeover behavior analytics deep learning device recognition fraud detection fraud prevention Identity machine intelligence Open Banking Payments PSD2 risk analysis risk engine signals intelligence supervised machine learning unsupervised machine learning

Deep Labs Featured in RIS on How Retail Needs A New Approach To Fraud Using Artificial Intelligence

Deep Labs Chief Strategy and Product Officer, Michael Lynch discusses how account opening fraud is a rapidly increasing challenge for issuers due to the plethora of identity data available to fraudsters. The 2018 Identity Fraud Study by Javelin Strategy & Research shows that the number of identity fraud victims increased by eight percent in 2017, with the amount stolen totaling $16.8 billion.

Some of the top financial institutions employ specific and often expensive point solution providers for device risk, behavioral risk, mobile phone intelligence, social reputation, email reputation, call center fraud defense, bot and malware detection. And each of these providers typically provides a risk score or a rules-based approach, and a potentially long list of data attributes.

But this approach creates an issue and an opportunity. It isn’t necessarily a bad investment to add new point solution or data providers as long as you are getting value out of these investments. However, that is often the hardest determination to make. Personally, I have worked in large organizations where we invested in the latest and greatest data source, but never fully realized the potential of what we had purchased.

To complicate this further, often there is no cross-channel communication for authentication or identity decisions. Each channel is working in its own silo as is each point solution provider with their scores and rule sets. And from a consumer view, they must prove their identity or authenticate across different lines of business or for different types of transactions. It starts to be obvious why we are losing the battle against fraud with this approach. Many systems, many rules, many scores, no central decision maker or analysis to determine the optimal blend of accurate decision, cost, and performance.

Read the full article here.

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Deep Labs Wins ‘Gold’ for Company of the Year at the 11th Annual Golden Bridge Awards® in the Artificial Intelligence Category

First placed winner championship gold trophy

SAN FRANCISCO, September 26th, 2019 — Deep Labs has earned the prestigious Gold status in the Golden Bridge Awards® Artificial Intelligence Category as Company of the Year. The coveted annual Golden Bridge Awards program encompasses the world’s best in organizational performance, innovations, products and services, executives and management teams, women in business and the professions, innovations, best deployments, product management, public relations, marketing, corporate communications, international business, and customer satisfaction programs from every major industry in the world.

Winners will be honored in San Francisco on Monday, October 28, 2019 during the annual Red Carpet SVUS Awards Ceremony.

“We’re honored to be named Company of the Year Gold winner,” said Scott Edington, CEO of Deep Labs. “The award is a testament to Deep Labs’ commitment to providing unique persona-based artificial intelligence that enables businesses to solve complex problems and continuously assess risk in real time.”

About the Golden Bridge Awards

Golden Bridge Awards are an annual industry and peers recognition program honoring best companies in every major industry from large to small and new start-ups in North America, Europe, Middle-East, Africa, Asia-Pacific, and Latin-America, Best New Products and Services, Best Innovations, Management and Teams, Women in Business and the Professions, Case Studies, Customer Satisfaction, and PR and Marketing Campaigns from all over the world. Learn more about Golden Bridge Awards here.

About Deep Labs

Founded in 2016 by a team of experienced Payments and Signals Intelligence experts, Deep Labs has created a platform that leverages persona-based dynamic risk & propensity profiles to address Payments and Healthcare risk.

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Deep Labs Featured in Value Walk on How Banks Can Protect Real Time Payments From Fraud

ValueWalk’s interview with Michael Lynch, Chief Strategy and Product Officer, Deep Labs. In this interview, Michael discusses his and his company’s background, fraud-prevention strategies for real time payments, the problems with Zelle, Venmo and other big fintech giants, the three-day good funds model that banks use for wire transfers, if Chase is offering safe real time transfers, fraudsters using social engineering to transfer money, FedNow, the role of Libra and crytocurrencies in real time payments, using AI or machine learning to predict problematic payments, legislation related to consumer protection, and the the potential for fraud in persons to person payments.

Interview with Deep Labs’ Michael Lynch

Can you tell us about Deep Labs?

Founded in 2016 by a team of experienced payments and signals intelligence experts, Deep Labs has created a machine intelligence platform that leverages persona-based dynamic risk & propensity profiles.

Deep Labs’ context-aware platform can use persona-based intelligence to better differentiate between a fraudulent transaction and a legitimate one. We are therefore able to provide a solution, based on our ability to distinguish between different contexts, that allows the banks, the payment networks and the various merchants to really understand the context surrounding that transaction.

The use of personas improves consumer activity verification and engagement by determining the likely needs or activities of that individual, based on past behaviors and external variables.

Deep Labs’ patented machine learning technology provides key insights on identity behavior through billions of calculations, iterative insights and process analytics.

Our platform connects authentication, device, behavior, and transaction data for modeling across customer interaction points and solves for siloed views of customer interactions across channels.

Read the full interview here.

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Deep Labs Featured in BankInfo Security on PSD2 Authentication Requirements

Because banks, fintech firms, merchants and payments processors in the European Union have struggled to meet the Sept. 14 deadline for compliance with the new PSD2 “strong customer authentication” requirements for electronic payments, it may take awhile for European consumers to notice authentication changes.

Back in June, the European Banking Authority, an EU regulatory agency, said that “on an exceptional basis” national regulators may be able to provide limited additional time for implementation. Subsequently, regulators in the U.K. announced in August they were delaying enforcement of the authentication requirements by 18 months – but only for online payments within the U.K.

In a statement, the Financial Conduct Authority, a regulator in the U.K., said: “All parties involved in card-not-present transactions, both FCA regulated and unregulated, should continue to work together over the next 18 months to ensure the smooth and timely implementation of SCA [strong customer authentication] by 14 March 2021 and the third parties should make every effort to move to API access where available as soon as possible during this period.”

The Hurdles to Overcome

Security experts say many banks are not ready to comply with the PSD2 strong customer authentication requirement because they face technical and operational challenges as well as budgetary constraints.

“The bottlenecks for banks to comply with the PSD2 standards are the complexity of requirements owing to the competing environments of the third parties, particularly in the context of potential deployment of APIs, identity and security,” says Gavin Littlejohn, chairman of the Financial Data and Technology and Association, a global association for financial services companies.

Michael Lynch, chief strategy and product officer at Deep Labs, an IT services firm, says many European banks and payment service providers lack the necessary technologies to meet the authentication requirements.

“The problem is, it requires a deep understanding of technical and security components to understand and design a solution for the requirements. The banks are not geared up to provide a platform for the transaction risk analysis, leveraging data signals and new technologies such as context-aware machine intelligence.”

Lynch says that banks preparing to comply with the new mandate need to make multiple investments beyond authentication technologies, such as malware detection and secure communication via encryption.

But one of the most significant challenges, security experts say, is putting in place the necessary APIs to enable authentication transactions with merchants processors and fintech firms.

Read the full article here.

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