Big data for finance
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This solution provides a complete architectural framework. It helps banks smoothly migrate their IT systems to new technologies. This migration reduces hardware costs and accelerates business innovation in the finance industry.
Data warehouse solution
This solution provides a big data warehouse for the finance industry.
Business architecture
Architecture description:
- The big data warehouse retrieves data from external sources and data marts. This data is then filtered, analyzed, and transformed through several layers, including data retrieval, data model, data transformation, application data service, and an analytics mart. Finally, a big data service interface provides the processed data for various user scenarios.
- Big data warehouse features:
- Integrates internal and external data from financial enterprises and performs multi-dimensional data transformation and in-depth analysis.
- Helps financial enterprises discover the business value in their data and drive business innovation.
- Uses a logical, hierarchical approach to transform and restructure data for targeted data outputs.
- The big data warehouse leverages the powerful data processing and computing capabilities of Alibaba Cloud's big data products.
Architecture advantages:
- Effective integration of internal and external data in the finance industry.
- An optimized hierarchical data architecture.
- Efficient methods for data transformation and service delivery.
Technical architecture
Architecture description:
- The Alibaba Cloud big data warehouse solution is battle-tested within Alibaba Group. It is developed entirely in-house, continuously optimized and improved, and offered as a mature product to customers in the finance industry.
- The big data warehouse integrates a variety of compute engines to support different business scenarios, such as offline computing, real-time computing, stream processing, and graph computing.
- It also supports the storage and computation of both structured and unstructured data.
Architecture advantages:
- A unified solution for both structured and unstructured data.
- Support for business scenarios that involve offline, online, and streaming data.
- Resolved integration issues with the big data platform.
- An efficient solution for the development and management of big data platforms.
Financial risk control solution
The financial risk control solution leverages big data profiling, machine learning, knowledge graphs, and complex relation network analysis. It helps financial institutions build a comprehensive risk control system for pre-event prevention, in-event warnings, and post-event analysis.
Business architecture
Architecture description:
- The solution leverages the powerful computing capabilities of the Alibaba Cloud big data platform, including offline data processing, interactive Online Analytical Processing (OLAP) analysis, and real-time stream processing, along with the distributed visual algorithm platform PAI. This combination seamlessly integrates batch and real-time computing to support real-time credit scoring and risk alerts.
- The real-time decision engine uses the intelligent Tag Factory from the DTBoost product to provide a unified risk tag view for heterogeneous data sources and apply scorecard model rules to calculate credit scores in real time. The engine also uses risk alert rules configured in its built-in rules engine to monitor and trigger risk events in real time.
- The Yidun Anti-Fraud engine leverages Alibaba's extensive big data to provide identity verification, information authenticity validation, and RAIN risk scoring services. These services deliver high-precision, reliable, and internet-based identity verification and anti-fraud capabilities for marketing campaigns.
- The complex relation network analysis engine builds a knowledge graph based on the Object-Link-Property (OLP) model and combines this graph with spatio-temporal data. Using instant search, visual relation network analysis, and spatio-temporal relationship analysis, the engine quickly identifies risk factors such as fraud rings, critical paths, and key members.
Architecture advantages:
- Unified management of tags from heterogeneous data sources.
- A solution for real-time computing and decision-making.
- End-to-end integrated risk control.
- Intelligent risk identification and analysis.
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