Why “Yes” and “no” are probably the wrong answers in risk management

The warnings are becoming louder and more frequent. Headline after headline, report after report, we’re constantly reminded of the increasingly sophisticated attacks from cybercriminals and fraudsters. While fintechs are transforming the financial world by leveraging data and leading-edge technology, fraudsters are likewise hard at work turning those innovations to their own advantage. 

Banks, payment providers, and online marketplaces have never been more vulnerable than they are today. In pursuit of growth and market share, they pour their resources into enhancing the customer experience – removing friction, speeding up payments, incentivizing customer onboarding – but their risk management thinking is stuck in the past, whereby “yes” or “no” are the only options.

This isn’t necessarily a question of resources, but rather a question of mindset. Digital payments have become the cornerstone of our economy, and demand for safe, secure online transactions is higher than ever. But if fintechs deploy the same binary approach towards risk management, they’re artificially capping the volume of transactions they can process or the number of customers they can onboard. Fraud moves quickly, and risk management needs to keep up. 

The growth dilemma

Fintechs are facing a dilemma. While promotional tactics such as incentivized sign-up schemes remain one of the most valuable tools for growth, they also come laden with risk. Fraudsters exploit loopholes, fooling businesses by abusing sign-up bonuses, referral rewards, and loyalty discounts. The risk of payments fraud has also skyrocketed, tripling in the space of a decade from $9 billion in 2011 to $32 billion in 2020. 

As if the stakes weren’t high enough, the current turbulence in the global economy is increasing the risk factor further still. According to one survey, more than 40% of financial service providers expect the cost-of-living crisis and rising interest rates to lead to an uptick in payments fraud over the next 12 months. The same survey revealed that almost one in three (30%) of fintechs believe their current anti-fraud methods aren’t developing fast enough to cope with the onslaught. 

The legacy approach

In payment processing and customer onboarding, risk management has typically been a binary affair. A transaction or sign-up request comes in, and a business will gauge the authenticity of that request with a simple “yes” or “no” before allowing the transaction through or blocking it. This process can be automated to speed things up, but it’s unsophisticated and prone to bias and groupthink. The criteria used to gauge whether a transaction is authentic or fraudulent is often outdated before it’s even deployed. 

This binary approach to risk management puts payment providers on an “all or nothing” footing. Company-wide risk management policies can’t be easily rolled out or changed according to the climate of risk. There may be times, for instance, when a fintech is content to expose itself to more risk in pursuit of growth, but with a binary risk management system, it doesn’t have the mobility to push that policy and certainly lacks the granular control needed to apply risk policies to individual scenarios, services or products. 

The risk of fraud, regrettably, comes with the territory. It asks a lot of questions of businesses, but those questions have become so nuanced that a simple yes/no answer will no longer suffice – at least not while growth is an objective. 

If financial service providers want to open their doors to more customers, they’re going to need to take a more modern approach to risk management that allows them to process transactions at speed without compromising on risk. In other words, they need to balance risk with growth more effectively. 

What’s a fintech to do?

Fraud itself isn’t a barrier to growth. What’s hindering businesses is how they manage their exposure to fraud risk. Instead of relying on binary processes – whether manual or automated – businesses need to be able to take a more nuanced approach.

Risk is a sliding scale, so it follows that the solution to mitigating that risk should also be a sliding scale.

As transaction requests materialize, businesses need to be able to interrogate the risk associated with those transactions – not using a static blanket policy, but using real-time intelligence and balancing it with their preferred level of exposure. Machine learning, for instance, might allow fintechs to set more nuanced risk profiles with more factors in play, applying policies and rules on a per-transaction or per-product basis. Taking this approach will allow companies to not only process robust fraud checks with speed but allow a degree of flexibility in their risk posture which will ultimately unlock more growth.