On AI, fraud, and human connections —?A reflection from Las Vegas

How often do we catch ourselves saying: “It is so good to see you in real life!” I am not sure about you, but I’ve certainly lost count of saying “in person” in the recent Money20/20 in Las Vegas, an intense melting pot of serendipity moments and bear hugs.

As it turns out, as much as our industry is all hyped up about technology and the actual form that money will take — be it bits and bytes or paper — the future of money in this connected world is still very much human —?and with human connections.

Unfortunately, at the same time, it’s precisely the humanness of our world that bad actors like to take advantage of.

“There’s almost no area of people’s lives that can’t be exploited by fraudsters in our increasingly connected world.”

As our lives increasingly shift to online channels, either by choice or by necessity, scammers exploit our new digital habits, in an always-on world filled with uncertainty, increased anxiety, and feeling of loneliness. From employees or consumers of services, we have become the perfect targets of social engineering schemes with convincing phishing emails and text messages. It is perhaps no wonder that over 70% of survey respondents indicated that they have been the victim of fraud at least once during their lifetime in the recent Faces of Fraud study commissioned by 赛仕软件 .

And while some groups might be of higher risk than others, anyone from Gen Z to older adults can become victims of fraudulent schemes, from romance scams, phishing, and impersonation scams to credit card fraud, business opportunity scams, lottery fraud, and more. The increased adoption of generative AI tools to create deepfake videos and convincing content have only heightened the risks and exposure.

This begs the question. What role can technology such as artificial intelligence play in combating financial crimes?

What about AI?

It is interesting to note that according to SAS’ survey, today’s consumers are willing to do more with technology if it helps to protect them from fraud. Majority of survey respondents (nearly 80%) said “they were willing to use security features such as fingerprints, facial recognition, hand geometry, iris recognition, retinal identification and voice recognition when completing a transaction.” Some are willing to go as far as switching providers if they believe someone else can offer them better protection.

Luckily, there are now new fraud detection technologies that help organizations stay ahead of sophisticated threats, including ones that leverage AI and machine learning to identify anomalies and trends in real time. Coupled with increased consumer education and awareness, we are more equipped than ever when it comes to fraud prevention.? ?

It is ultimately about trust.

Of course, we cannot talk about artificial intelligence without diving into trustworthy AI. After all, our industry and our society are built with trust as the foundation.

Think about our day-to-day lives for instance and the money that we load in various stored value cards (or gift cards) in exchange for our morning cup of coffee. How the exchange takes place is less important than the trust we place in the merchant: that we will be able to get something in return at a future date with the preloaded card. Similarly, when we deposit money in the incumbent financial institution or a fintech, we trust that the money that we deposit will be safe, and that we could withdraw it at our own terms, at a future date.

That same trust is assumed in when it comes to other banking services. When we secure a car loan or a mortgage for our dream house, we demonstrate a level of trust with the financial institution —?and we trust that the algorithms used for credit decisioning will be fair, transparent, and explainable, and that our data will be kept private and secure.

“Trust in AI has to start before the first line of code is written.” Reggie Townsend —VP of Data Ethics at 赛仕软件

As a friend of mine once said, in financial services, if you are not reliable, you are liable. Now even more than ever, our industry has the duty to care — to act responsibly and to listen empathetically — to earn the trust of those who place their trust and their aspirations in our hands. Ultimately, it is our collective responsibility to ensure that no harm is done, especially to those who are most vulnerable and underrepresented, by historical biased data.

We have an immense task and an opportunity to use data for good and to turn dreams into reality.

A shared prosperity is possible —?if we are intentional.

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What are the current applications and risks of generative AI in the financial services industry and what does the future hold for the technology?

Check out my recent conversation with Diana Rothfuss and Heather Sugg at Money20/20 , where we explore:

[1] The key use cases for generative AI in financial services and how firms are deploying the technology.

[2] The risks posed by generative AI and deepfakes and how financial companies can protect their business and customers.

[3] How collaboration between financial institutions and regulators can help forge the future of the technology.

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