/case-studies / bank-realtime-fraud-agent
AGENTIC AI & AUTOMATION

A real-time fraud agent reduces false positives for a bank

client
Digital Bank
industry
Financial Services
services
Agentic AI · AI / ML
duration
6 months
fig.90// skillikzIAMSIEMZero-TrustSOCthreats.logrollout89%0breachesusage87coveragelive
// OVERVIEW

Digital Bank — a financial services organisation — engaged Skillikz on real-time fraud agent: Pattern-detecting AI that catches fraud without blocking good customers. This case study sets out the business challenge, the AI-led approach we took, the technologies involved and the measurable outcomes delivered over 6 months.

// TECHNOLOGIES
LangGraphClaude / GPT-4PythonVector DBAWSKubernetes
-35%
false positives
real-time
scoring
fraud caught
explainable
decisions
01 // THE CHALLENGE

Rule-based fraud checks blocked too many legitimate payments while still missing novel fraud patterns.

02 // OUR APPROACH

We combined ML scoring with an agent that gathers context and acts in real time, with explainable, auditable decisions.

Real-time ML fraud scoring
Agentic context-gathering and action
Explainable, auditable decisioning
Continuous evaluation against new patterns
03 // THE RESULTS

False positives fell 35% while catching more genuine fraud — protecting revenue and customer experience together.

Fewer good customers blocked, more real fraud stopped. That balance was the whole game.

Head of Financial Crime · Digital Bank
// HOW WE'D DELIVER THIS TODAY

The AI services behind this outcome

A project like this draws on a focused set of Skillikz services — from first assessment to a working pilot and a clear path to scale.

// MORE WORK
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