Detect fraud in real time with AI

Fraud detection models that identify suspicious transactions with high precision, low false positives and millisecond response times.

Overview

The Fraud accelerator combines supervised and unsupervised machine learning models to detect fraud in real time, analyzing transactional, behavioral and contextual patterns.

Services

Real-time detection

Transaction scoring in milliseconds with models that evaluate dozens of simultaneous variables for instant decisions.

Anomaly detection

Unsupervised models that identify unusual patterns and atypical behaviors without relying on fraud history.

Network analysis

Graph analytics that identifies fraud rings, related accounts, and collusion patterns.

Risk scoring

Risk score per transaction, account, and customer with continuous calibration based on investigation feedback.

Case management

Alert management platform with prioritization, investigation workflow, and feedback loop to the model.

Fraud analytics

Dashboards with visibility into attempts, blocks, false positives, and model performance.

Where we operate

Where we operate with Fraud Detection

Payment methods

Fraud detection in card, PIX, and transfer transactions with real-time decision-making.

E-commerce

Order risk analysis, fake account detection, and chargeback protection.

Banking

Bank transaction monitoring, money laundering detection, and regulatory compliance.

Insurance

Claims fraud detection, suspicious document analysis, and identity verification.

Telecommunications

Subscription fraud detection, service abuse, and SIM swap detection.

Healthcare

Health plan fraud identification, medical billing fraud, and suspicious prescription detection.

How we work

Data Analysis

Mapping transactional, behavioral data, and confirmed fraud history.

Feature Engineering

Building velocity variables, temporal aggregation, device fingerprint, and behavioral biometrics.

Modeling & Ensemble

Training supervised and unsupervised model ensembles with threshold optimization.

Real-Time Deploy

Integration via low-latency API with circuit breakers, fallbacks, and performance monitoring.

Operation & Feedback

Alert management, investigator feedback, and continuous retraining to adapt to new patterns.