About iTrack
Enterprise Transactions Sentry | ML and BIg Data Powered
Who We are
iTrack Sentry is an enterprise anti fraud and AML solution. Encouraging businesses to establish confidence in each digital transaction is our mission with iTrack. To protect financial transactions from fraud, iTrack amongst other things combines machine learning with cutting-edge algorithms. We guarantee that our clients will function with confidence in an increasingly complicated digital context by upholding integrity and security.
Your dependable choice on Fraud Prevention
iTrack helps build trust on every digital transaction and can extend the trust to manual transactions
iTrack helps organisations build trust in every digital transaction by utilising cutting-edge algorithms and intelligence to effectively defend against fraud. The security and veracity of financial transactions are guaranteed by the unique machine learning transaction monitoring technology
Fraud Prevention and AML Compliance tool
Enterprise Transaction Sentry powered by big data and Machine Learning (ML).
iTrack blends powerful big data tools, data analytics with cutting-edge Machine learning algorithms, alongside state-of-the-art enterprise rule engine to effectively defend and mitigate fraud and to provide in-depth insights and from near real-time to real-time transactions monitoring.
Why iTrack
iTrack will benefit financial organizations looking for a cutting edge, ML-powered solution to preserve their financial integrity and their clients’ assets.
Our Mission
iTrack’s main aim is to help financial services companies (deposit money banks, Financial Technology companies, Microfinance banks amongst others) to meet regulatory compliance obligations regarding AML and general fraud mitigations strategies.
Our technology
iTrack is an enterprise transaction monitoring system that combines machine learning, big data technologies, and a state-of-the-art rule engine. Our platform is designed to handle and process large volumes of data efficiently, providing real-time capabilities for fraud detection