How to Use Machine Learning to Reduce End-User Friction

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.
Ritesh Arora

Ritesh Arora

August 15, 2022

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 FIs may rely on outdated technology and are forced into manual processes that tax limited staff resources, prove to be more costly in the long run and are prone to mistakes due to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:

  • Improved accuracy – The solution will be continually trained to analyze and detect patterns across large amounts of seemingly disconnected data that would be impossible for humans to see. This not only helps spot suspicious activity better, but it also helps reduce false positives.
  • Increased speed – ML can evaluate enormous amounts of data in a very short amount of time—in near to actual real-time—in line with consumer expectations for speed and convenience.
  • Improved efficiency – With its continuous learning and improvement, ML can detect subtle changes in patterns across large amounts of data. This means the fraud detection process becomes more accurate and automated over time, requiring analysts to review only the few exceptions that the ML wasn’t able to confidently evaluate.   This significantly improves their efficiency by enabling them to focus on investigating fewer, exceptional cases.
  • Scalability – ML capabilities level the playing field for community banks and credit unions. Staff resources need not be increased even as application volume or fraud activity increases—all while sacrificing nothing in terms of accuracy and protection. You can offer your account holders the same level of protection and security as larger, more sophisticated competitors at a fraction of the cost.

 

Effectiv’s fraud and compliance solutions – Scalable, turnkey, cost-effective and accurate

Effectiv’s turnkey, customizable application and onboarding fraud detection and compliance automation platform helps community banks and credit unions stop fraud at the source while minimizing friction for legitimate applicants because of its AI/ML capabilities that help eliminate false positives.

The platform comes integrated with trusted third-party data intelligence providers and can be deployed out of the box with built-in rules or customized so rules can be added, deleted, or adjusted based on your FI’s unique risk profile and tolerances. Better still, customizations are as easy as drag-and-drop and don’t require any intervention from IT staff or programmers.

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. The Effectiv platform offers a sensible, cost-effective and elegant way for FIs to protect account holders and improve the user experience that leaves a stellar first impression. For more information on this topic or to learn more about Effectiv’s fraud and financial crimes solutions, visit effectiv.ai.

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