RiskAgenticHigh complexity
Fraud Detection & Response
Catch fraud on instant payments, where money leaves in seconds and authorised push payment scams look like ordinary customer behaviour.
How we approach it
Streaming features on every payment, scored by rules plus models, with graph features to expose mule networks. Agents gather the context for each alert, draft the case and propose an action; holds and customer contact above a set threshold need an analyst's approval. Verification of payee results and device signals join the feature set, and analyst decisions feed retraining.
Business value
Fraud stopped before the money leaves, with analysts on the hard cases
Technology stack
- Kafka
- Flink
- LightGBM
- graph database
- agent framework
- case management
Related service
Proprietary AI DevelopmentRelated use cases
- Financial Services · RiskCredit Risk AssessmentScore borrowers on financials, payment history and macroeconomic data, with decisions that a credit committee, a customer and a supervisor can each follow.
- Financial Services · RiskRegulatory Compliance CheckAnswer questions on CRR3, MiFID II, DORA, the AI Act and internal policy, with the article behind every answer.
- Financial Services · RiskProprietary Risk ScoringUse years of internal loan performance data to price and select risk in ways a bureau score cannot.