End-to-end fraud analytics platform for training, evaluating, and serving transaction fraud predictions in online and offline modes.

Fraud Engine, Machine Learning, Spark

Duration

1 Year

Year

2024

Region

USA

AI Fraud Engine is an advanced AI fraud detection system designed to identify and prevent fraudulent transactions in real time. It combines machine learning, feature engineering, and predictive analytics to deliver accurate fraud detection across online and offline payment systems.

Problems

Growing transaction volume made manual fraud review insufficient and reactive.

Opportunities

Build a scalable ML fraud pipeline to detect anomalies earlier and improve decision quality.

Solutions

Developed modular fraud-engine architecture for offline model development and online prediction execution with reusable AI components.

Future Trends

Ensemble/graph fraud analytics, adaptive thresholding, and continuous learning from investigation outcomes.

Our Projects

AI Fraud Detection System (AI Fraud Engine)

End-to-end fraud analytics platform for training, evaluating, and serving transaction fraud predictions in online and offline modes.

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NLP Call Analytics & Quality Scoring Service

Django REST web service for call-quality evaluation and historical evaluation retrieval using NLP engine integrations.

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NLP Processing Framework

Modular NLP framework covering preprocessing, feature engineering, and vectorization for conversation and text analytics.

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Model Serving Platform

Achieve scalable ML deployment and real-time inference via our containerized model serving platform for reliable AI predictions.

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Model Inference Service

Real-time inference API service for invoking deployed AI models with resilient, enterprise-ready request handling.

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Financial Document Verification AI (FVS)

AI-powered computer vision platform for check/image verification including signature, MICR, amount, date, and verbiage analysis.

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Successful Project Deliveries

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