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The Costly Limitations of Black Box Fraud Solutions

Armen Najarian by Armen Najarian
June 30, 2023
in Featured Content, Fraud, Industry Opinions
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black box fraud solutions

Hand press typing on keyboard to unlock passwords or access to computer laptop. Cyber security concept.

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The recent emergence of generative AI (artificial intelligence) tools such as ChatGPT has captured the world’s attention, including that of fraud actors who readily embrace new technologies. Cybercriminals already have an arsenal of tools and tactics at their fingertips via the deep and dark web, and developments in AI are sure to supercharge their efforts to steal from consumers and businesses. Faced with this intensifying and ever-shifting fraud landscape, business leaders must re-evaluate whether their fraud prevention tools are up to the task.

For fintech, payment, and retail industries, now is the time to reassess your third-party fraud prevention providers and call for a higher standard of transparency and control over your fraud operations. It’s important to ask: does your fraud prevention solution provide you with the transparency and flexibility required to adjust to quickly evolving fraud patterns? And does it effectively protect revenue and enable growth?

The Problem with Black Box Fraud Prevention

While the fraud prevention market is crowded with solutions that use machine learning, some operate essentially as a ‘black box,’ giving little to no insights into their decisioning and offering limited flexibility. Typically, these types of solutions rely simply on a ‘yes’ or ‘no’ method when determining transaction risk, resulting in a disproportionate amount of declines and false positives experienced by legitimate users.

When you entrust your fraud prevention system to a technology provider that doesn’t fully understand your business and the context of your fraud signals, you risk a third-party calling the wrong shots on your business. Leaving these types of systems to freely make transaction decisions can quickly lead to consumer insults and lost sales—and overall interfering with the quality of customer experiences and your business’s bottom line. By the time fraud prevention teams spot inaccurate decisions made by a black box fraud solution, it’s too late—the transaction has already been accepted or declined.

Strategically Applying Fraud Controls

While visibility into risk decisioning is one important element of a quality fraud solution, your risk team also needs the ability to control and adjust fraud operations as needed. Fraud patterns change quickly and novel attack types surface year-round, so having the capabilities that allow you to quickly identify and stop these evolving threats is key.

But applying these risk decisions doesn’t need to be done blindly. Fraud technology impacts the consumer-facing side of your business, so choosing a fraud prevention service that takes the user experience into account is essential. When evaluating fraud solutions, look for ones that enable your business with dynamic friction, which is a method by which additional fraud controls are only applied to risky transactions, while legitimate customers continue to enjoy a smooth user experience. 

How you apply dynamic friction should continually evolve based on the needs of your business, situational circumstances, and data insights from your fraud prevention solutions.

Regain Control Over Your Fraud Operations

While dynamic friction is one key feature that black box fraud solutions are missing, there are several other capabilities that these types of solutions lack—qualities that are indispensable if you want full control and transparency over your fraud operations. Below are just a few of the important features you should look for in a fraud solution:

Nuanced risk assessments: Fraud patterns and abuse tactics can change quickly, which means that your strategy and risk decisioning may need to adjust as well. A fraud solution that gives you both \visibility into these changing patterns and the ability to address them in real time enables your risk team to be both proactive and reactive at the same time.

Detailed analytics: Access to the underlying data allows fraud analysts to conduct deeper case forensics. Additionally, fraud performance visualization and reporting is an essential capability for ROI analysis and business insights.

Simulation tools: Equally important is having tools that allow you to test scenarios before applying new rules to your decision strategy. These allow risk teams to run historical data through a proposed rule change as if it were live, to see how it would perform.

Configurable policies: As a business operator, you should have the ability to refine risk rules and thresholds based on your unique needs and risk tolerance.

Moving away from black box fraud solutions requires a fundamental mindset shift on behalf of both technology providers and businesses. For businesses to succeed amid the torrent of digital risk they face today, fraud prevention can no longer be treated as a disconnected line item in the budget. Rather, fraud prevention must be reimagined as an integral part of a business’s health and growth strategy. The businesses that have both control over and visibility into their fraud prevention systems will be the ones that can not only protect their revenue, but also expand their growth potential.

Tags: AICybercrimefraud managementFraud PreventionMachine Learning
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