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AI Can Help Fintechs Fight Fraud-as-a-Service

We’ve entered a perfect storm for financial crime where fraud is flourishing. This maelstrom has been created by the combined effects of geopolitical events and the ongoing global pandemic, which has led to the digitalization of society ramping up, by necessity, even faster than it was before.

While all sectors are suffering, financial technology (fintech) has been hit particularly hard, which makes striking the right balance between preventing financial crime and maintaining high levels of customer service and satisfaction all the more difficult — and business-critical. As the situation continues to evolve and worsen, it has become a high priority for fintechs to learn how to effectively fight and defeat fraudsters, while continuing to grow their top lines.

As companies address this challenge, they must consider:

  • What key areas should fintechs focus on? Where is fraud rife?
  • How can fintech minimize the negative impact of fraud on operations and finances?
  • Can technology defend against the fraudsters?

‘Fraud-as-a-Service’ Takes Center Stage

It sounds like just a clever play on words based on the software-as-a-service (SaaS) model, but fraud-as-a-service (FaaS) is a real phenomenon. Mirroring the cloud model through which fintechs deploy many of their capabilities via services, bad actors with worse intentions are leveraging similar technology to commit service-based crime on an unprecedented scale. FaaS occurs when an individual or group of fraudsters facilitate fraudulent online activity by providing tools and services to others.

This devious method enables fraudsters to purchase and exploit data and tools leveraging stolen or synthetic identities, which they then use for fraudulent purposes. FaaS also enables scaled attacks on fintechs in which fraudsters overwhelm financial systems with bad traffic and complete illegal transactions at a high volume. Using this approach, fraudsters are mimicking the fintechs’ use of quick, easy, and cost-effective online processes, as well as the best analytics and data, only to defraud instead of enrich. The result: Software fights software at an unmanageable scale.

Trouble Spots

One area where fraud is particularly pernicious in the industry is onboarding, where it’s vital for fintechs to balance keeping crime at bay while still ensuring a high level of customer service. Identity fraud and fraudulent documentation issues often arise during the onboarding of new customers, which can hurt a company’s growth objectives and hinder its customer service goals.

Identity theft and document fraud are on the rise and already cost the global economy billions of dollars a year, with no end in sight. Beyond onboarding, institutions are asking for more documents to verify customer identities, requiring proof of residence and age and evidence of income, in addition to standard IDs. Whether it’s the alteration of bank or government documents or the creation of false ones, the fact is that it just takes one valid forgery for a bad actor to wreak havoc.

If that same fraudster has access to multiple stolen identities, then the fintech is going to face scaled attacks via serial fraud attempts. Often a case of successful fraud is the precursor to other crimes, such as money laundering, human trafficking, and even terrorism.

Using AI to Scrutinize Identity

It can feel hopeless when learning of scaled-up attacks executed at high speed, but resisting and rooting out fraud is possible with artificial intelligence (AI). Typically, new fraud patterns are hard to detect until they have been observed for a period of time, at which point fintechs can react and deploy defenses against the attack. Usually, the time lag is too great and the damage has been done. But AI can subject every customer interaction, from documentation to behaviors, to a level of forensic analysis that would be impossible for humans to achieve at the same speed. The technique can filter out everything from fake documents and stolen data to bot-executed serial fraud efforts.

Incorporating AI ensures that fintechs will allow fewer high-risk identities and document transactions in their processes, helping them outsmart the fraudsters and beat them at their own game.

However, it’s not enough to simply invest in AI technologies; human capabilities are just as important to achieve financial crime prevention at scale within an AI-centric model. Fintechs should not only understand the data they’re working with and have AI expertise at the ready, but they should also ensure alignment with business objectives and establish an appropriate operational workflow. By blending these critical elements, fintechs can successfully fight financial crime.

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