Real-time transaction monitoring
With sub-second scoring across cards, payments, and digital channels.
Real-time intelligence, engineered for the institution that has to defend it.
Fraud and financial crime do not stay still. Patterns evolve, channels shift, and the model that performed last quarter may already be behind the people working against it.
Entiovi engineers risk and fraud detection systems that monitor transactions in real time, detect behavioural anomalies across channels, and route the right signal to the right investigator - with the explainability, audit trail, and governance the function is held to.
Entiovi designs risk and fraud intelligence platforms across cards, payments, digital banking, lending, and capital markets. The work spans data engineering for transactional and behavioural signal, model development across supervised, unsupervised, and graph-based techniques, real-time scoring infrastructure, and integration with case management and investigator workflows.
Systems are built to evolve - pattern shifts and new fraud vectors are expected, planned for, and instrumented. The engineering objective is not a higher AUC on a static benchmark. It is a fraud and risk function that catches more, escalates better, and explains itself when asked.
With sub-second scoring across cards, payments, and digital channels.
Across supervised, unsupervised, and graph-based modelling on customer, device, and merchant signal.
With alert generation, prioritisation, and false-positive reduction.
For entity resolution, beneficial ownership, and mule-network detection.
With explainable alert surfacing, evidence assembly, and audit trail.
Covering versioning, performance monitoring, drift detection, and regulator-ready documentation.
Across issuer and acquirer.
Across retail and SME banking.
With risk-tiered alert prioritisation.
For high-value and time-critical payment rails.
In capital markets.
Staged loss, identity, and provider-network anomalies.
Lower fraud and financial crime losses, fewer false positives consuming investigator capacity, faster case resolution, regulator-defensible model documentation, and a fraud and risk function that scales without proportional headcount growth.
Engagement starts with a portfolio and signal review, followed by model and scoring architecture, integration with the relevant payment, banking, or capital markets infrastructure, and pilot deployment alongside the fraud or compliance function. Once live, model performance is reviewed continuously against fraud outcomes, alert volume, and investigator feedback - with a defined governance cadence and a model owner.
Risk and fraud intelligence is judged by what it catches, what it misses, and how clearly it can explain both. Entiovi builds for all three.
Talk to Entiovi about putting this discipline into production - from design and engineering through ongoing operation, with delivery from India and regional presence in your market.