Automated Data Aggregation Solution for Fintech

This case study outlines the challenges faced by a US-based fintech company in aggregating large amounts of data from various sources. The client's manual data aggregation approach was inefficient, leading to wasted resources and inaccurate conclusions. They sought an automated solution to consolidate mortgage data in real-time from different online lending marketplaces while ensuring information security. The company approached Xtract.io to streamline their data integration process. A customized data aggregation solution was designed, employing site-specific custom bots to gather mortgage data from numerous online sources. This solution enabled the client to collect 30,000 input records every hour, with extracted data uploaded into a database for deduplication. The implementation of an API facilitated regular communication between the user’s browser and server. The results included over 95% data accuracy, enhanced decision-making speed, and a 75% optimization in resource spending within two months, ultimately allowing the client to lend money to credible customers while eliminating poor loans.