Balancing fraud risk and growth: how top consumer lenders deliver both

The frontrunners in consumer lending are already leading their fraud functions like revenue engines. They optimise for approval speeds and capital efficiency, and judge success by their department’s direct contribution to growth. That means looking past raw fraud volumes and focusing instead on two outcomes: stopping high-impact fraud, and saying yes to customer loans wherever possible.

It's a clear shift in mindset. And even as fraud becomes faster and more coordinated, top lenders aren’t pulling back. They’re doubling down, and rightly so.

Fraud teams are essential to commercial performance and only with their risk expertise can lenders grow revenue without taking on uncontrolled exposure.

Why this mindset shift matters more than ever

The cost of exposure is still significant, and never far from a fraud leader’s mind. A single serious fraud event can distort commercial fundamentals and drag down performance across the board.

Fraud, increasingly powered by AI and alarmingly scalable, now threatens to move faster than risk mitigation controls can respond. This leaves leaders facing a set of critical pressures:

• Unrecoverable goods and credit written off
• Elevated PD and ECL models forcing excessive capital provisioning
• Investigation teams overloaded with manual casework
• Risk controls that delay or deter good customers

What a revenue-first approach looks like in practice

In short, top teams are embedding themselves deeper into the consumer lending lifecycle

They’re aligning fraud strategy with credit risk, onboarding and revenue operations to influence decisions upstream, not just clean up issues after the fact. And they’re enabling this approach with tools that move at speed and scale. These include:

1. Consortium risk intelligence Cross-sector data highlights fraud patterns earlier and reveals behaviours that cut across markets. Teams get earlier warnings, clearer signals and more control over their strategy and risk appetite.
2. Predictive AI AI models trained on this consortium data pick up risk signals traditional rules miss – like behavioural nuances or new patterns. They identify fraud faster and push more genuine customers through.
3. Real-time decisioning With the right setup, teams can act instantly at the point of application. Fraud is stopped upfront, without introducing friction for good applicants.

The result is a leaner, sharper fraud operation. One that protects the business while accelerating approvals and improving capital efficiency.

Case in point: shifting fraud from cost centre to growth lever

One major UK retail finance provider, processing over 350,000 credit applications annually for leading high-street brands, worked with Synectics to confront fast-scaling fraud.

The goal was clear: identify and stop high-risk applications in real time, while keeping credit flowing for legitimate customers.

To deliver, Synectics built a predictive AI model tailored to the client’s risk appetite and built on National SIRA data - the UK’s largest risk intelligence consortium. The model allowed for confident, automated decisions at scale.

The results:

• 90% of a major organised attack stopped instantly
• 10% uplift in fraud prevention
• 64% reduction in time to detect new fraud
• 50% drop in referral volumes
• Significant improvement in good customer conversion

What growth-focused fraud leaders are doing next

Fraud has evolved into a systemic threat to consumer lending performance. But for those who act decisively, the opportunity is clear.

By harnessing cross-industry shared intelligence, AI and real-time decisions, market leaders are shifting fraud functions from final checkpoint to critical lever in capital efficiency and commercial acceleration.

Now is the time to reframe fraud prevention. Not as a safeguard, but as a catalyst to compete, lead and grow in a market defined by speed and trust.