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AI Integration

Stop Fraud Before It Happens

Our AI fraud detection engines analyze thousands of signals per transaction in under 50 milliseconds. Using graph neural networks, behavioral biometrics, and anomaly detection, we identify sophisticated fraud patterns that rules-based systems miss — while keeping legitimate customers friction-free.

The Problem

Without AI Integration, you are leaving money on the table.

  1. 1

    Without Real-Time Transaction Scoring

    Sub-50ms fraud scoring for every transaction using ensemble ML models that evaluate device fingerprints, geolocation, velocity, and behavioral patterns - Without this, you risk wasting time, money, and competitive opportunities.

  2. 2

    Without Graph-Based Fraud Networks

    Graph neural networks that map relationships between accounts, devices, and transactions to uncover organized fraud rings and money laundering networks - Without this, you risk wasting time, money, and competitive opportunities.

  3. 3

    Without Behavioral Biometrics

    Continuous authentication using typing patterns, mouse movements, touch dynamics, and navigation behavior to detect account takeover in real time - Without this, you risk wasting time, money, and competitive opportunities.

How We Do It

A proven process that transforms vision into reality

1

Fraud Landscape Assessment

Analyze your current fraud patterns, loss data, false positive rates, and existing detection capabilities to identify the highest-impact improvement areas

2

Data Pipeline Architecture

Build real-time streaming infrastructure that ingests transaction data, device signals, and behavioral telemetry with sub-second processing latency

3

Model Training & Optimization

Train ensemble fraud models on your historical data with class imbalance handling, adversarial testing, and precision-recall optimization

4

Shadow Mode Deployment

Run the AI system in shadow mode alongside your existing fraud system, comparing results and fine-tuning before production cutover

5

Production Launch & Tuning

Full production deployment with real-time monitoring, A/B testing against legacy systems, and continuous model improvement based on analyst feedback

The Proof

CodeLeap transformed our vision into a complete product in just 3 months. The quality and commitment were exceptional - we could not have achieved this on our own in an entire year.
SC

Sarah Chen

Chief Technology Officer, TechVista Inc.

40%

Average efficiency gain for clients after AI integration

What You Get

Timeline: 10-18 weeks

Technologies

PythonApache KafkaApache FlinkNeo4jTensorFlowRedisKubernetesElasticsearch

Deliverables

  • Real-time fraud scoring API with sub-50ms latency
  • Case management and investigation dashboard
  • Graph-based fraud network visualization tool
  • AML/SAR reporting automation module
  • Model performance metrics and ROI analysis report
  • Fraud analyst training documentation and playbooks

Ready to start?

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