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Digital change happens at the speed of light, and fraudsters move nearly as quickly to exploit vulnerabilities and gaps in fraud prevention capabilities. Financial institutions cannot afford to leave protection up to chance.
Consumer demand for digital-everything has been steadily rising for years but has sped up since the height of the pandemic. Steered by leading retailers adept at providing seamless end-to-end digital experiences, consumers now expect the same quick, efficient and accurate experience from their financial institutions (FIs)—whether completing a transaction, opening a new account, or applying for a loan.
The problem for FIs is how to implement the right level of due diligence in confirming applicant identities without alienating legitimate account holders. Get it wrong, and you risk hard and soft-dollar losses, reputational damage, and abandoned applications. Get it right, and you can stop fraud before it happens, improve the consumer experience, increase application completion rates, improve efficiency and reduce costs.
The stakes are high
Consumers aren’t the only ones gravitating toward digital-only interactions. Fraudsters are continually finding new and creative ways to stay one step ahead of online fraud controls—and the proliferation of digital activity has only worked in their favor.
Financial institution fraud is at an all-time high, and it’s only expected to increase:
Technology as a Competitive Differentiator
Community banks and credit unions have traditionally operated at a technological disadvantage. With fewer resources and smaller budgets, investments in sophisticated technology can be slow. FIs may rely on outdated technology and are forced into manual processes that tax limited staff resources, prove to be more costly in the long run and are prone to mistakes due to human error—it’s a catch-22.
In terms of competitive advantage, increased customer/member friction leading to abandoned applications (lost business), reputational damage and operational inefficiency all conspire to give a leg up to big bank and non-traditional financial services competitors that deploy slick and expensive enterprise fraud solutions.
Level the playing field
Fortunately, newer, more scalable game-changing fraud detection and prevention solutions exist that offer FIs the same level of sophistication at a much lower cost, thanks to machine learning (ML).
Machine learning works by assimilating large amounts of available information and identifying patterns that can differentiate between normal and abnormal attributes and behaviors. By automatically updating rules and limits, ML allows FIs to reduce false positives that drive manual reviews, increase auto-approvals for new accounts and applications and simplify fraud analysts’ jobs by providing deeper insights when manual reviews are necessary. Additionally, fraud detection powered by ML only gets more accurate over time. As ineffective processes and false positives are identified by the solution, the solution will eliminate them going forward.
Benefits of machine learning in fraud detection and prevention
While all fraud detection and prevention solutions require some level of human intervention to analyze exceptions and rejected applications, a solution that employs machine learning will minimize this, freeing up resources for more strategic initiatives. Specifically, fraud prevention enabled with AI/ML offers these benefits:
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Ruchi Rathor Founder at Payomatix Technologies
06 September
Alexander Boehm Chief Executive Officer at PayRate42
05 September
Erica Andersen Marketing at smartR AI
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