Smart Risk Management Platform Project of Sinomach Finance Company

1. Project Background

As part of its digital transformation, Sinomach Finance Corporation needs to build five application clusters — including intelligent risk management and control and intelligent customer service — to achieve unified group treasury management and digital risk control. Specific tasks include establishing monitoring models for four major risk categories (financial health, credit risk, liquidity risk, and compliance risk) to enable single-point, panoramic monitoring and intelligent early warning of core risks.

2. Overall Objectives

Build an intelligent risk management and control platform to achieve objectives such as regulatory indicator monitoring and early warning, segmented monitoring and early warning for the four risk types (including liquidity), and 360-degree customer profiles. The platform must be highly extensible. To improve data quality and the reliability of risk alerts, it should also be complemented by capabilities in self-service analysis and querying, data modeling, data governance, data sharing, and data services.

3. Project Requirements

(1) A massively parallel processing (MPP) analytical database system capable of handling large-scale data workloads with rapid response times.

(2) Support for deployment on both x86 and ARM servers.

(3) Support for active-active disaster recovery with primary and standby clusters.

(4) System auditing with robust log management and tracking mechanisms.

(5) Built-in data encryption to protect data security.

This project deployed a 6-node GBase 8a database cluster—3 management nodes and 3 data nodes—delivering high-performance data storage and processing, and established a unified data platform built around the GBase 8a MPP Cluster. The platform enables distributed storage and efficient processing of large-scale data, meeting real-time and accuracy requirements. Leveraging its data integration capabilities, business data from core and financial systems is consolidated into the GBase 8a MPP Cluster through a data pipeline platform. Built-in access management tools ensure data security and compliance. For analytics and mining, the cluster’s distributed computing power drives machine learning and data mining initiatives. With the robust performance of the GBase 8a MPP Cluster, enterprises can further accelerate data analysis, uncover data value, and foster business innovation.

Blazing-Fast Performance: Leverage intelligent indexing, a fully parallel architecture, and transparent compression to deliver lightning-fast query and analysis, fully supporting high-performance query and analytics workloads.

Shared-Nothing Architecture with Linear Scalability: Eliminate single-node bottlenecks with distributed management of data and compute resources, ensuring linear performance growth as your system scales.

Security Control: The GBase database includes built-in permission management tools to enforce system security and access control.

High-Speed Loading and Massive Storage: Achieve high-speed loading of tables with hundreds of millions of rows. High-compression-ratio data ingestion boosts loading performance and storage capacity, while massive storage facilitates the consolidation of data from multiple business units.

Ad-Hoc Queries with Sub-Second Response: Deliver high-speed ad-hoc and range queries on massive datasets, providing stable support for analytical systems.