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For many institutions that offer credit (traditional banks, neo-banks, auto loan lenders, consumer credit companies, etc.), maneuvering the increasingly sophisticated traps laid by internet scam artists is too often synonymous with staggering costs—in time, human resources, and money. Yet some companies out there are managing to fight fraud effectively while increasing their profits. Their secret? Innovation and, more specifically, machine learning.

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The problem: credit fraud is up 25%, and the trend is picking up speed‍

According to WPI, credit fraud could lead to 45 billion annual losses by 2023. If fraud were a country, it would be the fifth-largest in the world. And as the digital revolution speeds along and business increasingly moves online, credit fraud attempts are climbing ahead.

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As interest rates fall, profit margins shrink, and fraud takes a more significant toll

While fraud continues to flourish, credit institutions are facing a twofold challenge. Interest rates have dropped over the last ten years, particularly for consumer loans. Low-interest rates might be great for borrowers, but this shift has made it harder for credit lenders to absorb the cost of fraud. Today, they need to sell twice as much credit just to cover the loan defaults and fraud losses chipping away at their net banking income, already dwindling under rock-bottom interest rates.

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The problem with today’s credit fraud detection solutions

‍Credit lenders are excellently defending themselves against credit fraud, preventing 90% of incidents before they happen. The problem is that to cover their losses—and more importantly, to increase their revenue, they need to eliminate the remaining 10% of fraud still slipping through the net. But when it comes to battling this increasingly cumbersome residual fraud, traditional fraud detection systems are no longer enough.

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First, they overwhelm employees with security alerts that need to be processed manually and generate too many false positives that must then be dealt with, requiring companies to hire additional staff.
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Second, from a customer service perspective, these measures are counterproductive, increasing waiting times for legitimate clients. Applicants submit an online credit request in minutes, then wait for days (or weeks) to get an answer. It’s frustrating, and not everybody is patient enough to wait. The Outcome: Lower ROI, wasted time, added pressure on staff, and a poorer customer experience. All this to recover… 1% of losses.  

How machine learning can stop residual fraud and generate revenue

To break the cycle and outwit scam artists who are becoming increasingly agile and tech-savvy, many credit lenders have realized they need to take a different approach.

From Carrefour Banque to Renault Finance, more and more companies are augmenting their existing fraud detection systems with machine learning and AI-driven solutions. Easy to set up, quick to produce results, and customizable to any business or industry, ML-driven solutions like Bleckwen Credit Fraud Services can process much more data than traditional systems, continuously learning and fine-tuning their fraud-detection radar. The result? Unparalleled performance.

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After 6 months of using Bleckwen, Carrefour Banque & Assurance had reduced residual fraud by 80%

Between July 2020 and January 2021 alone, Carrefour Banque & Assurance was able to prevent €23.18 in fraud for every €1000 of consumer credit granted and €7.41 for every €1000 of revolving credit given, thanks to machine learning. And the benefits don’t stop there. ML-driven credit fraud detection solutions like Bleckwen Credit Fraud Services generate 10x fewer alerts and false positives than rule-based systems, pinpointing the actual potential fraud attempts better and more accurately.

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‍The Outcome: Your staff saves valuable time and energy but makes the final call in potential fraud cases.

In addition, the solution’s logic and interface are intuitive, producing results that are easy to understand - a big plus for operational efficiency (teams know where to look for information), regulation compliance, and customer service. If your fraud prevention strategies have reached their limit and you want to do better with minimal effort and maximized ROI, it may be time to try Bleckwen Credit Fraud Services, our lightweight, powerful, customizable fraud detection solution powered by machine learning.

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