How to Identify High-Risk Customers in Banking

by Jimmy Fong
Buy Now Pay Later companies (BNPL) inherently take a risk with every new customer they onboard. And, with the sector holding a 3% market share globally and up to 25% in countries such as Sweden, the BNPLs who keep themselves safer are going to be the ones to dominate.
Here’s how to detect high-risk customers and keep them away, without slowing down the experience of good users.
Because they cost BNPLs in revenue, resources and even compliance fines. In fact, letting in too many fraudsters as well as bad debtors can make or break such a company, even causing it to shut down due to insufficient funds left.
BNPL companies’ growth has been supercharged in recent years. Unfortunately, that usually means accepting users who won’t be the most valuable in the long run.
In the BNPL world, these high-risk customers tend to fall within four key categories:
Then, of course, while not necessarily high-risk, you should also filter out junk users who sign up with fake IDs and bad data.
The good news? You can detect all of the above using the same tools.
Versatile and fully customizable, SEON helps you block high-risk customers, get alternative credit data, combat fraud, and grow faster.
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The key to detecting high-risk BNPL customers is to monitor transactions & start gathering data on them as soon as possible. This will be at the onboarding stage, where you probably already perform basic KYC checks and fast credit scoring. In come robust device fingerprinting, IP address checks, velocity rules, and so on – as well as taking advantage of digital footprint analysis to find out a wealth of information without any friction.
But why stop at the data that the users are giving you? This is where data enrichment can help you complete the picture, without adding extra friction to the onboarding process.
Put simply, it’s about using single data points to get more information. For example:
But what do you do with all the extra data? It’s time to feed it into the custom ruleset to detect risky users.
Let’s look at 3 good custom rules to help you get started with identifying high-risk BNPL users.
The world is getting more social, not less. This is doubly true for BNPL customers, who tend to be younger Gen Zs and millennials.
This is why registered social media and other web platform profiles are a strong indicator of whether you’re dealing with a real person or not.
An IP address isn’t just used to gather geographic information. It’s also helpful to learn when someone is meddling with it.
In the world of high-risk users, this almost always points to fraudsters who are attempting to hide and spoof their IP addresses. They may do so with VPNs (low-risk), Tor (medium-risk) and datacenter proxies (high risk).
It’s the kind of information that can help you calculate an IP fraud score or segment customers based on how risky they might be for your BNPL company.
Best of all, it’s also a fantastic tool to highlight suspicious logins. This will help you reduce account takeovers and remove friction at the authentication stage for your most loyal and trustworthy customers.
Another useful custom rule to spot potential chargeback fraud and money laundering: looking at sharp increases in spending.
This could point to a customer who is gradually increasing their credibility while planning to disappear without paying for an expensive item – or, of course, it should be a legitimate purchase. It is worth getting your fraud team to take a second look at though, always.
In the example below, we want to increase our risk score by 20 points when someone spends 200% more than usual within 1 day.
You could of course automatically send the transaction for review or automatically block it if you feel it’s too risky for your company.
At SEON, we’re all about giving you as much risk management flexibility as possible.
This is true from the versatility of the dataset you can get (via specific modules), all the way to the integration method.
Perhaps more importantly, we know that our tech is loved by BNPL companies, who use it to:
Whether it’s by spotting connections between users or immediately flagging high-risk users, our BNPL fraud tools are guaranteed to help you grow safely – even as regulations and market forces change.
Partner with SEON to keep your BNPL safer with real-time data enrichment, unique digital footprinting, and advanced APIs.
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Jimmy Fong is the Chief Commercial Officer of SEON. His expertise in payments saw him supervise the acquisitions of companies by Ingenico, Visa and American Express. Jimmy’s enthusiasm for transparent sales and Product-Led-Growth companies drives SEON’s global expansion strategy, and he interviews both fraud managers and darknet fraudsters in our podcast to stay on top of the latest risk trends. Yes, it’s also him wearing the bear suit on our YouTube channel.
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