Crises, such as the current coronavirus pandemic, often bring out the best in us. But troubled times can also provide opportunities for unscrupulous and malevolent actors to take advantage of people’s anxieties and fears.
The hoarding of personal protective equipment that occurred early in the coronavirus crisis and the spread of crazy conspiracy theories about the origins of the virus have helped create a climate of fear and suspicion. This can make dealing reasonably and confidently with the crisis that much more challenging for all of us.
Unscrupulous and malevolent actors are also taking advantage of people’s financial anxieties and fears during this time. Our Fraudtech Digital Day – part of Finovate Fintech Halftime Review – will take a close look at how the cybersecurity threats before the crisis struck have intensified in many ways in the weeks and months since.
How big is the current cybersecurity problem for financial services firms and their customers? What technologies are being deployed to help financial firms and other businesses stay one step ahead of the fraudsters? How can businesses defend themselves against fraud while still providing the kind of seamless, digital experience consumers demand? These are some of the topics we’ll discuss as part of our FraudTech Digital Day.
To whet your cybersecurity whistle, we’re sharing excerpts from our conversation earlier this month with BioCatch co-founder and Chief Cyber Officer Uri Rivner. We spoke with Mr. Rivner about the new threats to cybersecurity that have arisen with the global public health crisis of COVID-19.
“Fraud isn’t going away and, in fact, we anticipate a surge in account takeover activity as criminals scale up their cash-out operations,” Rivner said. “They already have the data they need to steal more money, but they need to scale their infrastructure.”
BioCatch specializes in providing behavior-based authentication and threat detection solutions. Headquartered in New York and Israel, and founded in 2011, the company demonstrated its Passive Biometrics/Invisible Challenge technology at FinovateFall. BioCatch’s platform analyzes 2,000 behavioral parameters based on user-device interaction, and leverages this data to build real-time risk scores that provide continuous authentication and a superior defense against account fraud, social engineering scams, and more.
“We’ve taken a scientific field in cognitive studies, something that was working in the lab, and made it extremely practical for use in solving the biggest issues in online fraud,” Rivner explained. “(A)cross dozens of banks, credit card issuers and companies outside the financial sector, (we are) protecting over 100 million online and mobile users. We’ve tackled issues that were initially deemed impossible to solve.”
Here are some key takeaways from our conversation.
On the threat of increased fraud and cybercrime during the pandemic
If I had to pick one community that is definitely going to thrive during a global virus outbreak, it’s online fraudsters. They have a golden opportunity to scale their operations while entire companies move their fraud operations and analytics teams to a work from home model, which is not an easy process for, say, a major bank.
On the danger of identity theft and why behavioral-based authentication is key to fighting it
The most scalable fraud operation is opening credit card or personal loan accounts. All you need is to buy a bigger list of stolen identity records, and have a team of people opening accounts in other people’s names. Identity theft is reported to sky-rocket, and it can be quite dangerous, especially if it’s a new digital service that is launching these days. If a new digital service is targeted by a massive campaign, there will be more fraud applications than real applications – that’s disastrous.
Traditional defenses such as checking KYC (know your customer) data and device recognition no longer hold, and new technologies such as behavioral biometrics are used to stop such fraud campaigns and reduce false rejections due to high security bars.
On the role of enabling technologies and “the right kind of AI” to help fight fraud
Machine Learning can instantly look at thousands of features, resulting in an extremely accurate model that predicts fraud and can adapt itself when cyber criminals change their strategy. At BioCatch we have over 2,000 such features.
An important consideration though is that some machine learning models are a black box and don’t really provide insights into why a certain action is risky. BioCatch, for example, uses Explainable AI models to make sure customers can get the reasons why a score was high, as well as many negative and positive behavioral factors observed during a session.