Rural Credit Cooperative Funds Clearing Data Platform – National Clearing Data Center for Rural Cooperative Financial Institutions

lMassive Data Consolidation: Leverages the GBase 8a MPP Cluster's standout strengths in massive-scale storage and massively parallel processing to manage vast business data repositories. Its efficient data integration and processing capabilities deliver a consistent and reliable data view.

lPer-Transaction Ad Hoc Queries: Utilizes the GBase 8a MPP Cluster's high-performance ad hoc query capabilities on massive datasets to enable fast, per-transaction queries of detailed transaction records.

lComplex, Multi-Dimensional Analysis: Built on the robust ROLAP analysis capabilities of GBase 8a MPP Cluster, this underpins complex, multi-dimensional reports over massive data volumes, empowering member institutions and clearing centers with analytical insights for decision-making.

lHigh Linear Scalability: GBase 8a MPP Cluster's robust online scalability ensures the data platform can seamlessly accommodate future business systems and higher-level requirements for complex analysis and strategic decision-making.

The project deployed a 2×2 cluster tailored to the data platform requirements of the Rural Credit Banks Funds Clearing Center, using GBase 8a MPP Cluster—a large-scale distributed parallel database cluster system—as the core data management layer of the data platform.

It integrates data from multiple core business systems and platforms—including payment and clearing systems, electronic commercial draft platforms, online banking platforms, online interbank payment and clearing platforms, self-service financial services platforms, and shared multi-medium financial services platforms—into a foundational data platform, achieving message-level granular data management. With integration and common processing for upper-layer applications, it forms a unified foundational data platform for all data. On top of this platform, both a fixed-reporting platform and an ad-hoc reporting platform are built to enable multi-dimensional analysis of business information and fast per-record queries of historical transaction data.

By building a data platform, data centralization for the Rural Credit Banks Funds Clearing Center (RCBFCC) will be achieved, enabling unified storage, access, and analysis. The platform integrates data from various systems and platforms within RCBFCC to form an authoritative data center, reducing the data preprocessing workload for business personnel and providing timely, multi-dimensional business analysis reports for member institutions and clearing centers.

Additionally, the system must offer high reliability and ease of maintenance to reduce operational workload and costs. It should feature flexible horizontal scalability to accommodate future business growth and new service requirements. It must also support high-concurrency processing, with a capacity of 300 users and 20 concurrent clearing center user accesses.

Rural Credit Banks Funds Clearing Center Co., Ltd. (hereinafter referred to as RCCFC) provides fund clearing services, including remittance, bank drafts, and universal deposit and withdrawal for personal accounts, to 30 rural cooperative financial institutions and their tens of thousands of outlets across China. Guided by the national agriculture, rural areas, and farmers policy, which continues to drive rapid rural economic growth, RCCFC's business has expanded significantly, with annual transaction volumes nearly doubling in recent years and accumulated data now reaching 5TB.

With the rapid growth of existing business and continuous expansion into new services, the legacy system could no longer meet the diverse, time-sensitive, and complex data analysis demands of RCCFC's business departments and member institutions. It became urgent to build a unified data platform to support numerous and complex report generation and satisfy the data analysis needs of all members.

In the next phase, a big data platform will be built on top of this data center, integrating more comprehensive business and external data to enable higher-level applications such as real-time fund flow analysis, risk management, credit rating, and internet finance.