How Organizations Will Share Customer Risk Assessment Information to Prevent Fraud in the Future

Sharing Risk Assessments to Prevent Fraud

I think we will eventually get there. Having some type of global insight will come sooner rather than later as this has become essential. And it's not new. I think we had many efforts before, especially around big traditional banks, to create those types of consortiums.

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'Early Warning' is a great example of that. But one thing that we are doing today at Unit21 is developing something called the Fintech Fraud DAO, which will basically allow any user that decides to join our consortium to query the PII of your applicant or existing user, and get a response of whether or not this specific entity was flagged as fraudulent or abusive by one of the other players on the consortium.

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The beauty of it is that our model is designed in a way you have to give to get. So if you want to be part of our consortium, it also means that you will have to share information on your user or your applicants. And we do it in a very decentralized way. So we don't own the consortium, right? We don't own the database. And basically, even if, let's say, somebody comes and decides to buy Unit21, right, they won't become the owner and they won't see all those different entities because everything is encrypted obviously on the database of our DAO.

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I think eventually, a lot of fraud prevention practices, especially around onboarding, will start using some type of global insights and to actually be able to tell, hey, this entity already did something or conducted any type of fraud or abuse anywhere else. So maybe I will think twice before onboarding them or I will decide to onboard them but have them with more limited access to their account.

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So a lot of different ways you can actually use consortium. And also, this is relevant for existing customers as well. For example, if you're conducting some type of investigation and you think you have, let's say, quite large fraud, maybe you have 50 or 100 users that connect to each other in a similar way, you can take the elements of those entities and query them against the consortium to try to understand if those users have been flagged anywhere else. Chances are, if you suspect a fraud ring, once you query one, two, three, four, or five of them, and you'll start seeing that the results are positive, which means you probably have a true fraud ring operating on your ecosystem.

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Leverage Shared Data and Network Analysis to Uncover Fraud

Unit21’s network analysis feature allows teams to visualize links between entities on their platform and explore connections in detail.

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With this capability, we can take a suspicious user, and look at all of their connections in our ecosystem. For example, we can review a customer that is transacting with another individual, and look at any information connected to those entities. In this case, we see that both users share identifying information, including shared IP addresses, a shared Social Security number, and shared payment instruments. We can also see that the subject shares a phone number with a third subject.

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Following these connections can really help with uncovering fraud rings or groups that are looking to launder money, allowing teams to identify further fraud by investigating who this original suspicious person interacts with and what information they are using. This is an invaluable tool when it comes to deeper analysis into how a specific entity is interacting with other entities on your ecosystem, and can help you root out imminent threats.

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Interested in learning more? Catch Fraud Office Hours on-demand for a deeper dive.

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