Part 4/11:
Incorporating diverse alternate data sources such as utility bills, telecom bills, online transaction data, demographic details, and regional information.
Leveraging this data to build comprehensive, robust customer profiles that allow for tailor-made lending products—including customized interest rates and offers.
He further clarifies that data engineering is not limited to data scientists or analysts but serves as the backbone—like fuel pipelines powering a vehicle—ensuring high-quality, accessible, and reliable data flows for downstream processes including machine learning models and decision engines.
Technical Components of Data Engineering in Lending
The speakers elaborate on the core elements that enable a resilient data platform: