Cutting False Positives: How AI-Native Models Improve Fraud Detection for Fintechs

Discover how fintechs cut false positives, speed onboarding, and improve ROI with Coris’ AI-native fraud detection and merchant risk models.

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The False Positive Crisis

Fraud is rising, but false positives are the real profit killer. Rates of 95% or higher force teams to burn resources chasing “fraud” that isn’t fraud at all. The result: wasted labor, lost conversions, and frustrated customers.

The cost is massive:

  • 63% of financial firms saw fraud grow 6%+ in just a year [1]
  • $274B spent on compliance in 2024, with most going to false positives [2]
  • 79% of firms admit fraud prevention erodes customer trust [1]
  • 75% of ecommerce leaders say fraud checks cut into conversion rates [3]

For many institutions, investigating false positives isn’t optional — it’s a regulatory necessity. But treating them as “just the cost of doing business” destroys ROI.

Why Legacy Fraud Detection Fails

Most fraud systems weren’t built for today’s fintech realities. Static rules, disconnected tools, and generic models can’t adapt fast enough. Instead of catching fraud, they bury analysts in false alarms.

The result:

  • Ballooning manual review queues
  • Slower onboarding and payouts
  • Higher operational costs with less accuracy

Legacy tools don’t just miss fraud — they actively drain efficiency.

Purpose-Built AI for Merchant Risk

Coris was designed from the ground up for fintech and merchant risk. Unlike generic fraud tools, our platform combines:

  • Real-time AI models — scoring transactions and merchants in milliseconds
  • Continuous monitoring — spotting anomalies before they escalate
  • Integrated intelligence — from social media, online footprint, credit, compliance, and payments data

This approach cuts false positives, streamlines reviews, and delivers consistent, explainable decisions.

Proof in the Numbers

Across our customer base, fintechs using Coris report:

  • 70% fewer manual reviews
  • Faster onboarding with AI scoring and automated workflows
  • More consistent approvals without adding headcount
  • Improved customer experience through reduced friction

Real ROI comes from fewer wasted investigations and higher conversion rates — not just fraud prevented.

Rethinking ROI in Fraud Prevention

Fraud defense shouldn’t be measured only by losses avoided. The bigger lever is operational efficiency:

  • Every false positive avoided saves analyst hours
  • Every reduced delay improves conversion rates
  • Every automated decision lowers compliance costs

The math is simple — cutting false positives pays for itself.

The Way Forward

Fraud isn’t going away, but false positives don’t have to cripple ROI. With AI-native infrastructure, fintechs can:

  • Catch fraud faster
  • Review fewer cases
  • Approve more good merchants
  • Protect both margins and customer trust

It’s time to move past outdated tools. Fintech growth depends on fraud systems that reduce noise, not create it.