About the Client

US based FinTech product company supporting giant Banking and Insurance companies assuring tight data security and robust infrastructure.

The Challenge

Client wants to integrate Real time fraud detection in core banking solution without modifying their application for integration. The system needed to be fault tolerant, allow fraud detection rules to be added/modified on the fly, audit as well as track past transactions for usage patterns, supporting million transactions per second, which meant the fraud detection system had to respond back in milliseconds.

What We Did

• RFM Analysis
• Artificial Intelligence

• Data Aggregation
• Predictive Modelling
• Classification
• Data Cleansing
• Machine Learning
• RFM Analysis
• Artificial Intelligence

The Solution

DX Factor’s in-house team of Artificial Intelligence engineer built and deployed a predictive modelling technique that detection the fraud and false entries within millions of data set.

The objective of this model is to detect Real-time fraud transactions happening in FinTech world.

• Enabled real-time blocking of card/online transactions based on fraud filters enabled causing massive savings in terms of blocked fraud transactions and better customer satisfaction.
  Developed an adapter to connect with core banking endpoints and switch gateways.
• Ensured that core banking system did not have to undergo lot of change and at the same time gave flexibility to integrate the fraud integration system seamlessly into transaction workflow.
• Developed a prediction model through user feedback, RFM analysis, historical transaction.

Results & Outcomes

State-of-the-art data platform combines out-of-the-box features for fraud detection, block false transactions and assured better customer engagement.