By Chase Petrey, COO of Pi by Paytm
Customer churn is the enemy of growth. It’s throwing good money after bad, convincing more and more people to join the party while neglecting to notice or do anything about the people leaving via the back door. According to the latest figures, the financial services industry has a median churn rate of 19%, highlighting a major customer retention problem. But that’s not even the worst of it.
While customer churn rate is the figure often kicked around boardrooms, banks, financial service providers and other fintechs are currently suffering from an even deeper affliction – user churn. In many ways, user churn is worse than customer churn, because prospects leave the sign-up process before they even become customers. It’s worse than people leaving the party – it’s people arriving and deciding not to even enter.
Fintechs spend a lot of capital and resources on attracting customers. Companies know that the “build it and they will come” tactic will no longer suffice, but all of those marketing campaigns and incentivized sign-up initiatives count for very little if they hook prospects just to release them back into the wild. So what’s causing user churn? And what can banks and financial service providers do to prevent it?
An onboarding crisis for fintechs?
Banks and financial service providers operate in a fairly unique space. The industry is highly regulated, extremely competitive, and exposure to high-level risk comes with the territory. When the online payments sector was in its infancy, those risks were easy enough to manage without compromising on growth. Banks and fintechs could develop at their own pace, putting necessary checks in place to guard against threats such as payments fraud. But times have changed.
Payments fraud carries a higher risk factor than ever before. In fact, global losses in the industry from payments fraud more than tripled in the span of a decade, from just $9 billion in 2011 to $32 billion in 2020. Experts predict those losses will grow a further 25% by 2027, such is the prevalence of payment fraud. Promotional fraud or “promo abuse” is also a rising concern, where fraudsters fool businesses by abusing sign-up bonuses, referral rewards and loyalty discounts. Incentivized schemes like these are one of the best tools in a fintech’s arsenal for attracting prospects, but it’s also opening the door to greater risk.
The problems have mutated and evolved, but the solutions have remained much the same – and therein lies the problem. Banks and financial service providers can’t afford to layer on additional checks that frustrate the customer journey, because prospects will simply abandon the process. In a recent survey, we found that 72% of prospects will exit the sign-up process and go with a competitor if they’re asked to go through more than three identity checks. That’s despite those same customers having concerns around fraud and tending to trust fintechs that take fraud more seriously.
The growth-risk conundrum
Fintechs, it seems, cannot win. On the one hand, they need to demonstrate that they’re taking fraud seriously with robust processes and checks in place. On the other hand, those same checks are chasing prospects away because they make the sign-up process too long and tedious. It’s a catch-22, and the biggest contributor to runaway user churn.
At a time when interest rates around the world are rising and consumers are feeling financially stretched, now ought to be the time for fintechs to shine, removing friction and making transactions easier for the market as a whole. The growth opportunities are abundant, but financial service providers are being held back by a risk management approach that is looking increasingly outdated.
The path to a low risk, frictionless customer experience
The financial services sector may be under pressure, but it also has an excellent track record for using technological innovation to overcome obstacles in its path. One of the problems facing fintechs at the moment is that “low risk” and “frictionless experience” are considered mutually exclusive, but with breakthroughs in artificial intelligence (AI) and machine learning (ML), there’s very little reason that should still be the case. With legacy systems, risk assessments would typically be binary exercises requiring manual inputs from staff who would decide whether or not a particular sign-up or transaction gets greenlit. It’s slow, cumbersome and prone to bias, groupthink and human error. Whether or not a transaction or application is successful might depend on which individual handles the checks and their interpretation of the company’s risk policy.
Machine learning, however, removes this dependency on human input and elevates risk assessment from a passive yes/no process to something that’s more proactive, nuanced and consistent. Leveraging ML models, a fintech would be able to set its own unique risk profiles using rules and policies, then apply real-time intelligence that would allow for decisions to be made almost instantly. By automating this process, brands will acquire a reliable decision-making engine that can learn and scale with their business, putting “low risk” and “frictionless experience” firmly in the same column on the path to growth.