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AI & Fraud5 Feb 20258 min read

How AI-Powered Fraud Scoring Stopped £14M in Losses Last Quarter

Traditional rule-based fraud engines catch 60% of threats. Our adaptive ML models hit 99.7%. A look inside Knectd's real-time risk engine.

K

Knectd Editorial

Payment Infrastructure Insights

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In Q4 2024, Knectd's AI-powered fraud engine flagged and blocked £14.2 million in potentially fraudulent transactions across our platform. That's not a hypothetical number pulled from a model — it's real money that stayed in the accounts of our partners and their customers.

Traditional fraud prevention relies on static rules: flag transactions over £5,000, block cards used in three countries within 24 hours, reject mismatched CVVs. These rules catch obvious fraud — but they also generate false positives that frustrate legitimate customers, and they can't adapt to novel attack patterns.

Our approach is fundamentally different. Knectd's risk engine uses an ensemble of machine learning models trained on billions of data points. Each transaction is scored in under 50 milliseconds across 200+ features: device fingerprint, behavioural biometrics, velocity patterns, geolocation anomalies, merchant category risk, and network graph analysis.

The key innovation is adaptive learning. When a fraudster discovers a new exploit — say, using synthetic identities to open accounts — our models detect the pattern shift within hours, not weeks. The system re-weights features automatically, and new detection rules are deployed without engineering intervention.

We've also eliminated one of the biggest problems in fraud prevention: the false positive spiral. By combining hard signals (impossible travel, known compromised BINs) with soft signals (typing cadence changes, unusual session behaviour), we achieve a 99.7% detection rate while keeping false positives below 0.3%.

For our partners, this translates directly to revenue. A hospitality client processing 50,000 transactions per month saw chargebacks drop by 94% after switching to Knectd's scoring engine. An eCommerce marketplace reduced manual review queues from 800 tickets per week to under 30.

The regulatory landscape is catching up, too. The FCA and EBA are increasingly mandating real-time transaction monitoring. With Knectd, compliance isn't an afterthought bolted onto your payment flow — it's woven into every API call.

AI in payments isn't a buzzword. It's the difference between losing millions to fraud and running a platform your customers trust.

AIfraud detectionmachine learningrisk scoringfintech

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