The article describes how Yixin Group’s product team created an in‑house intelligent data warehouse using Hadoop, Flink/Spark, and standardized data services to transform scattered automotive‑finance data into a secure, scalable platform that supports real‑time analytics and drives business growth.
This article analyzes how Didi’s unique ride‑hailing scenario big data is applied to automotive finance, detailing the business model, asset‑side and full‑process risk challenges, data‑driven solutions, and future prospects for intelligent credit risk control in both enterprise and retail lending.
This article outlines the end‑to‑end design of automotive finance risk‑control processes, discusses key data integrity and customer segmentation considerations, and details machine‑learning modeling practices—including logistic regression, decision trees, GBDT, XGBoost, LightGBM and CatBoost—along with an automated platform to streamline model development and deployment.
