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November 19, 2020 - Chandreyee Chakravarty

How Fintech, Small and Midsize Financial Institutions Fight Fraud Strategically

Larger financial institutions benefit from having larger budgets, bigger teams of experts, and more dedicated resources to fight fraud. However, fraudsters don’t discriminate when choosing their next targets. 

Small and mid-size financial institutions and fintech firms may find themselves at a disadvantage when it comes to fraud prevention. They’re combating the same threats as their larger counterparts but must protect their customers and organizations with a more modest budget and limited resources.

Overcoming fraud prevention challenges requires a strategic approach that prioritizes organizational efficiency without damaging the customer experience. Here’s how DataVisor’s fraud detection platform is helping small and mid-size FIs fight fraud strategically.

Comprehensive Fraud Prevention Solutions Boost Fraud Detection and Improve Customer Experience

Detecting fraud is a delicate balancing act of identifying suspicious activities with accuracy and preventing friction for good customers. One of the most detrimental customer experiences when dealing with financial institutions is to be wrongly flagged as a fraud risk. According to a recent Aite Group report, avoiding false positives is one of the three greatest pain points among financial institutions. At least 47% of respondents claim the false positive rate is too high with most fraud prevention solutions.

As part of its comprehensive fraud detection platform, DataVisor’s unsupervised machine learning (UML) helps to reduce false positives while keeping accuracy high. This is because UML doesn’t rely on extensive data training to identify fraud and can evolve with new and unknown threats. By reviewing all data and transactions in relation to each other and in real time, fraud teams can better understand why certain activities are flagged as suspicious and decide how to proceed.

UML is just one part of DataVisor’s comprehensive fraud detection platform, which also includes supervised machine learning, an advanced rules engine, device intelligence, and a global intelligence network that all contribute to a holistic view of emerging fraud patterns. This multi-layered approach to fraud detection and prevention boosts fraud detection while improving customer experience.

Achieve and Measure a Higher ROI

A KPMG report noted that banks typically recover less than 25% of funds lost to fraud each year. What’s more, LexisNexis reports that most mid-size banks see about 2.41% of their annual revenue be eaten away by fraud-related expenses. 

Topline costs can be better justified with the return on investment from a fraud detection platform. There are a number of variables that must be considered when calculating ROI, including:

  • Operational savings, in the form of reduced manual reviews, automated decisions, and accelerated efficiencies
  • Rapid onboarding, with most financial institutions seeing increases in fraud detection in as little as two weeks from implementation
  • Significant fraud savings (One large bank was able to save $15 million annually in fraud costs.)
  • Reduced customer friction, leading to improved customer experience and reduced customer attrition.

For more information about how to calculate the ROI of your fraud detection solution, try out our ROI calculator.

Increase Operational Efficiency

One strategic solution to mitigate fraud is to focus on operational efficiency; when overhead costs are reduced, more resources are available to take action against fraudsters.

DataVisor has built operational efficiency into its comprehensive fraud detection platform by eliminating the need for ongoing modelretraining, reducing response times, and including bulk decision-making: 

  • UML allows FIs to detect new and unknown threats without ongoing fraud model retuning(conventional fraud platforms require fraud model retuning every 3-6 weeks), resulting in more fraud detected with higher accuracy. 
  • DataVisor’s Knowledge Graph visualizes multidimensional connections among entities, groups, money flows, IPs, emails, and other attributes in real time, to uncover hidden patterns and empower contextual decisions. Bulk actions increase efficiency by 10-100x. 

DataVisor breaks down data silos to provide insight across all channels and transactions to detect more fraud. This gives financial institutions a major advantage, especially since the Aite Group report notes that 65% of them struggle with harnessing internal data to feed their analytics. See how DataVisor is helping fintech firms and small and mid-size financial institutions fight fraud strategically; join our bi-weekly demo today. 

about Chandreyee Chakravarty
Chandreyee is the Regional Head of Sales at Datavisor. She has held high-profile sales positions within the Identity Management and AI space over the last 20 years globally.
about Chandreyee Chakravarty
Chandreyee is the Regional Head of Sales at Datavisor. She has held high-profile sales positions within the Identity Management and AI space over the last 20 years globally.