Intelligent Risk Control Ecosystem: Building a Closed‑Loop System with Data, Models, Strategies, and Experiments

The presentation focuses on constructing an intelligent risk‑control ecosystem that creates a closed loop across four key stages—data, model, strategy, and experiment—each forming its own sub‑ecosystem, and demonstrates the concept through QiFu Technology’s industry practice.

It begins by outlining the necessity of a smart risk‑control closed loop, emphasizing the importance of risk control in internet finance and the challenges of fragmented pre‑loan and in‑loan scenarios, which require unified, rapid experimentation platforms.

The concept of the intelligent risk‑control closed loop is defined, followed by an overview of QiFu Technology’s "Yushu" platform, which integrates large‑scale data processing, AI frameworks, feature mining, strategy authoring, and model development to enable end‑to‑end risk management.

The ecosystem’s four core components are described:

High‑performance feature service : asynchronous and synchronous feature computation, online‑offline feature consistency, and rapid variable configuration.

Secure, stable, high‑efficiency data layer : the Yushu 2.0 platform supports multi‑person collaboration, massive parallel tasks, and unified data management.

Value‑driven strategy engine : full‑life‑cycle strategy management (pre‑loan, in‑loan, post‑loan, anti‑fraud) with online‑offline consistency and integration with Hive, Kafka, and HBase.

Measurable continuous model : closed‑loop development and validation for both online and offline models, reducing deployment latency.

Intelligent experiment platform : unified online and offline experimentation to ensure results are applicable to real‑time scenarios.

The architectural diagram shows five layers: application (credit models, anti‑fraud services, strategy engine, feature service, experiment platform, bots), data/model (user profiles, warehouses, various AI models), compute (offline batch, real‑time streaming, graph, deep learning), storage (databases, distributed files, NoSQL), and data collection (foundation for the platform).

By leveraging AI, big data, and cloud computing, the ecosystem achieves high‑efficiency, secure, and innovative financial services, covering the entire risk‑control workflow from registration to post‑loan, and demonstrates significant improvements such as reducing model deployment time from a month to hours.