Transaction Analysis and Monitoring for a Financial Organization to Determine Suspicious Operations

Description

The client is a leading financial institution renowned for its innovative approach to digital banking. Catering to over 4.5 million users nationally, the bank has established itself as a key player in the financial sector, offering a wide range of services including personal banking, corporate finance, and online banking solutions.

The bank's system is robust, handling over 1.8 million transactions and 5 million actions daily, with a significant user engagement of over 350,000 daily logins.

Industry

Finance & Banking

Challenges

1 / Data integration. Seamlessly integrating various data sources into a unified data lake.

2 / Transaction monitoring. Managing and analyzing the vast number of daily transactions.

3 / User behavior analysis. Understanding client actions and payment details across multiple channels.

4 / Real-time analysis. Ensuring the timely and effective analysis of incoming data for instant decision-making.

5 / Fraud detection. Identifying and preventing suspicious transactions and patterns of money theft.

Goals

1/ Analyze transaction history, client actions, and payment details for insights

2/ Set up predictive analytics

3/ Enhance the monitoring department’s efficiency with an intuitive interface for rule generation and editing

Results

1/ Our service advanced algorithms that enabled instantaneous insights, allowing for real-time fraud detection.

2/ The implementation of predictive analytics within our service allowed for a 90% confidence level in forecasting customer trends, utilizing sophisticated data modeling.

3/ Rounding loss fraud identification. Detected a unique fraud scheme involving multiple small transactions in different currencies, exploiting rounding differences.

4/ Predicted customer financial trends with a 90% confidence level, greatly enhancing foresight in fraud prevention.