This article explains the concept, key terminology, and practical implementation of Vintage (cohort) analysis in financial services, detailing how to build tables and curves, integrate data pipelines, and use the insights to optimize marketing strategies, credit risk assessment, and operational efficiency.
This article explains how to construct a financial indicator system and its underlying data warehouse using FineBI, covering metric hierarchy design, ODS/DWD/DWS/ADS layers, AI‑enhanced BI analysis, and practical tips for organizational adoption and governance.
This article describes how Tencent's Alluxio-based Data Orchestration Platform (DOP) was applied to financial analytics, detailing the business background, challenges of large‑scale OLAP workloads, the Alluxio architecture and usage modes, performance results, and the series of optimizations and tuning performed to achieve significant speedups.
ByteHouse, a cloud‑native data warehouse built on ClickHouse, delivers ultra‑fast real‑time and massive offline analytics with elastic scaling, addressing business needs in ByteDance and the financial sector through optimized architecture, ROI‑driven monitoring, and comprehensive operational tools.
This talk by Zhongan Insurance’s Data Senior Director Shi Xingtian outlines the company’s digital transformation, detailing the 4633 framework, the real-time data warehouse architecture, the migration from ClickHouse to StarRocks, and how these technologies support fine‑grained, intelligent financial operations and advertising analytics.
This article describes how Du Xiaoman Financial designed, built, and continuously optimized a massive graph platform—including data governance, graph learning, query performance, data import, and online deployment—to improve credit risk assessment using billions of nodes and edges, and shares practical lessons on graph databases, distributed training, and real‑time inference.
This article presents a comprehensive overview of credit risk control strategies, covering industry background, traditional scoring‑card development, data integration, feature engineering, model evaluation, rate and limit optimization, and advanced machine‑learning approaches for loan underwriting.
This talk by Ba Xueyu, a senior big data platform engineer at Zhongyuan Bank, outlines the background, architecture, and engineering practices of a real‑time financial data lake, highlighting its open, timely, and integrated design, streaming platform implementation, and use cases such as anti‑fraud and real‑time BI.
