A Leader’s Guide to Navigating the Future of Fraud Prevention with DataVisor’s Dennis Maicon

Banking has changed so much in the last 30 years that many of the ways customers expect to be able to bank now were merely pipe dreams back then. The rise of mobile banking apps, digital banks, fintechs, and AI has revolutionized the customer banking experience and financial offerings across the industry. Most crucially, they’ve completely transformed how fraudsters and fraud prevention teams square off in the modern age.

Dennis Maicon, DataVisor’s new Vice President of Payments and Banking, has had a front-row seat to that 30 years of evolution. A product, sales, and management expert and leader in both financial and information services, Dennis served as VP and General Manager of FIS’ Financial Crime Management Business Unit, VP of Product Management for FIS’ Risk, Fraud and Compliance Business Unit. Before FIS, Dennis was the co-founder of Digital Envoy and EVP of the company’s Financial Services Business unit. For the last nearly eight years, Dennis was Vice President of Sales and Business Development ad IDology.

He was gracious enough to provide his perspective on how fraud gaps and crime rings have evolved, which frauds to target prevention at hardest in the modern era of banking, what fraud leaders should be preparing for in the coming years, and one big piece of advice he has for fraud and risk teams.

You’ve been in the financial and information sectors for decades. What has your experience been like in that time?

I was a former banker going back 25-plus years before I got into technology. My first endeavor in tech was with ARRIS doing phone over cable systems. I spent time as a finance guy for a bit, and from there I started a company that mapped out the IP address space in 2000. Once we mapped it, I used that data to create authentication tools we sold to the banking industry.

Back then I was the CFO and EVP of our Financial Services division, where we created many authentication tools banks and brokerage firms used to authenticate their consumers as they logged into the online platform. Since that was the very early days of the internet, we were doing business with Google when they were in their dorm room. I talked to Larry Page and Sergey Brin on the same call when we originally sold our authentication services to them.

After about seven years we sold the company. But I stayed on for about a year and a half before I went over to FIS, and from leading a finance division to heading up a risk, fraud, and compliance product team. FIS had about $200 million in revenue at the time, and they didn’t want me to just maintain the fraud solution that they had—which was a risk decisioning tool that used data from past checking accounts to see if a new account opener would have their account closed for cause within about 15 months.

I was brought in to build out the fraud tools that, at the time around 2009, the market was trying to get to. That goal was to be able to look at all transactions from a holistic perspective on each consumer. It could be check fraud, wire fraud, ACH fraud—any kind. This was well before any real-time payments, but some of the concepts around those started to come out towards the end of my time at FIS in 2014. The big challenge to building those holistic solutions was the computing power. There was no such thing as AI at the time—everything was driven by rules. You could only be looking at certain transactions. You couldn’t have that holistic picture to ask, “Where did the funds come in from?” or “Where are they going?” or “How quickly did those funds come in?”

After FIS, I moved on to IDology where I’d been for about eight years. It’s an identity verification company, so we were at the beginning of the customer life cycle. We did two things—KYC and using the data we had for additional attributes around mobile phones, emails, and IP addresses to find fraud at the point of account opening.

What interested you most about DataVisor?

What interests me most and led me to DataVisor was the technology and the machine learning that’s been built within the platform. We had a good handle on what to do to prevent fraud ten or 15 years ago, we just didn’t have the processing power. We didn’t have the power to go and do what needed to be done with the data that we had at hand. That really excites me coming over to DataVisor, because now, that technology does exist inside a platform that can give that holistic view of a customer and all their activities, monetary and non. Non-monetary activities by themselves might not be anything. But when you combine them with monetary transactions, you can see some really bad customer experiences or activities happening.

Are there any common fraud gaps you see FIs struggle with?

The key to the whole equation is how you can treat your good customers well while you’re trying to pinpoint those needles in a haystack. How do you single out that bad actor that’s coming through to take money? When you look at the gaps FIs struggle with, one of the big ones is a holistic approach to fraud.

From an identity perspective, all those years ago you had to layer different attributes and techniques into the onboarding process to know 1) you’re onboarding the right person from a KYC perspective, and 2) you’re onboarding the right person at this time. That same premise carries forward with fraud prevention. There’s not just one tool or technique that’s going to stop bad activities. The criminals have figured out ways to play off all the different channels and products that banks offer. You have to have a multi-pronged approach to fraud that all leads to that holistic viewpoint.

Some of the common things still happen. In account opening, that account might sit dormant for years until it busts out. It was just a mule account that’s out there waiting to take advantage of a scheme down the road. Or it might sit there and act normal for six months to a year, and then all of a sudden get wires from people neither you or the consumer’s ever seen before. Then when those ACH or other payments are coming in, the money is being wired out quickly.

Are fraud rings different now than they were when you started in fraud prevention?

You can look back to 2010 when we started trying to do some things in banking with the internet—mobile banking, digital banking—it was still in its infancy. The criminals didn’t have all the technology that they have today or real-time payment-type opportunities. But the simpler we make the banking experience, the harder it is to find fraud rings.

What the consumer wants is an Amazon-like experience. They believe the bank should know them even though they’re not standing in front of them at a branch. Criminal groups know that, too, and their technology has advanced. The products that they can pull into their schemes is much greater than it was ten or 14 years ago.

Is there a specific fraud challenge FIs should be keeping top of mind?

Phishing has been a big problem, and it’s almost like a cycle. It comes and goes, but the strategies are still very similar to what was happening back in 2010. And people still to this day fall for them.

The biggest fraud gap or challenge though has always been the human element of the consumers. At the end of the day, they’re the weakest link for fraudsters to attack in this whole process. Now, fraudsters can use voice recordings or AI to create deepfakes. They’ll robocall you and all they need to get you to say is “yes.” Because with the AI technology, that “yes” is going to sound just like you, so the fraudsters can use your voice when someone at the bank asks them to approve something over the phone. They can also create other things to say using your voice and trick the bankers too. Then you as a consumer could be toast, and your money and your account could be gone.

Knowing that the human element of customers is always going to be a gap, the banks have to have that full customer view. I know they say they try to have that full view, but until now they really haven’t been able to. DataVisor is at the forefront of providing that holistic view of all the activities of each consumer.

Is there anything you see coming in the next year or two that will make a significant difference in the financial industry?

The big ones, which also tie back to that holistic view requirement, are compliance and AML. When you look at fraud, we know all the decisions are made off of the same data. But there’s never really been that true centralized orchestration data repository that’s been able to take in the data and feed both systems. That’s caused inefficiencies within institutions.

It brings confusion because you have two different groups that might be in the same building—maybe even on the same floor—but they don’t talk to each other. The concept of financial crimes investigative units has been talked about for years, but we haven’t had the full use of the technology to get there. Now with what DataVisor provides, we can achieve that efficiency amongst different groups and be able to work through the same data. Sharing notes across different teams as to why they’re working on certain things is a tremendous savings within the banks and keeps them more coordinated.

Being able to fight criminals with a single joint purpose is highly important as well. I think that’s something that will make a significant difference as the industry starts to move forward. Those concepts were discussed years ago, and some institutions have them but they don’t quite work as smoothly. We can give them the ability to work incredibly smoothly with the DataVisor Platform, with the efficiencies of Generative AI, and the efficiency of unsupervised machine learning (UML). Let’s face it, the traditional supervised machine learning models are only as good as what we know. Yes, they learn over time, but they can’t take all the data and spot new trends right away. It’s like a car that has lane signals designed to keep you within a certain area, but it can’t tell you that there’s a crash ahead of you and you need to get over quickly. That’s what unsupervised machine learning really does—it’s able to spot those trends that supervised models can’t.

The GenAI and UML innovations are going to lead the industry. It comes back to the layers that you’re utilizing within the system. First, it’s rules, then it’s supervised machine learning, then unsupervised machine learning which is like the safety net for the others. Throw in GenAI as the fourth technique to continually automate optimizing your rule set or your thresholds, and the fraud team’s and AML investigators’ lives will be much easier and their work more effective and efficient.

What’s one piece of advice you would give to fraud leaders right now?

Stay up to date with technology. Fraudsters and money launderers are using all of the new technology that they can get. Then they’re playing that technology off of all of the good that the FIs are doing to give their consumers a great experience. Staying up to date on technology and embracing the new waves within machine learning, both supervised and unsupervised, is going to be the way FIs stay ahead of crime rings.

As another part of that—don’t just use one technique. You’ve got to use the gamut of tools that are there. Take that holistic approach to all transactions, look at how your rules are working, look how your machine learning is working, look at how your unsupervised machine learning is spotting trends. Stay on top of your game and continue to optimize the rule sets that you’re using. I’ve talked a lot about the technology, but the use of that technology can redefine an old market around AML and fraud. It can make the banks, fintechs, e-commerce companies, and financial services companies that much more productive and put them ahead of the fraud that’s occurring.

I think that’s crucial because let’s face it, the criminals that we’re fighting have an army of people that use sophisticated technology every day. They’re smart and know how to use it for their benefit. I like this quote I heard once, “Fraud used to be a cost of doing business. Now fraud management is an enabler of doing business.”

| “Fraud used to be a cost of doing business. Now fraud management is an enabler of doing business.”

It goes back to the unfortunate dilemma that the easier we make things for customers, the harder they become for fraud fighters. With the services FIs offer now, fraud leaders now have to change their mindset that fraud is a cost. You can’t live in the past with these old, outdated systems. You have to think of fraud management as an enabler to all those good solutions that you provide for your good customers. A good fraud system is enabling your FI to do business digitally the right way.

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