ZTE Finance Big Data Solution

  • Background and Customer Demands
    The data surge caused by the rapid growth of banking business continuously requires deeper service insight. The traditional extensive customer marketing strategy can no longer help banks achieve rapid service growth. Banks urgently needs the big data processing capability to facilitate service development by implementing the following tasks including: fully integrate the customer data and reduce the customer churn rata and improve user loyalty through precise marketing design; make comprehensive analysis of transactions from different providers and customers to realize chain reaction; establish an effective data model to provide its customers with omni-directional butler non-financial services and make profit from the big data. 
    Every day, the financial industry generates a great amount of data, including transaction, quotation, credit, enterprise credit rating, and macro economy analysis. Meanwhile, customers also generate different kinds of information, such as online shopping information, payment records, telephone records, and social networking information. A common problem faced by the whole financial industry is how to extract useful information from the massive data so that the information can be used for the enterprise operations and decision-making. This problem can be easily addressed by big data. 

    Solution Introduction

    ZTE Finance Big Data Platform is developed based on ZTE uSmartInsight, which imports the data from the relational database and file system into the big data mining platform to realize the ETL (Extraction, Transformation, Loading) flow of importing, cleaning, transferring, and layering the data, and make centralized storage of massive non-structured data and structured data. Based on the stored data, the platform provides the unified capability openness interfaces, data product service capability encapsulation, and basic resources management, helping the financial enterprises strengthen risk control, improve refined management, and make service innovation.   

    Application Scenarios

    ● Marketing and service innovations: Include cross sales and secondary sales, specifically, how to make retain customers and evaluate customer value, and realize precision marketing 
    ● Credit and risks: Mainly include credit allocation, risk evaluation, action authorization, risk mitigation, and fraud recognition. 
    ● Prediction and evaluation: Include periodic behavior analysis, quantitative analysis, churn analysis, and collection analysis. 
    Solution Highlights

    ● ZTE has the independent intellectual property rights and core technologies and ensures data security.  
    ● The solution is proved by extensive application for customers such as Agricultural Bank of China, China CITIC Bank, Hunan Provincial Government, Smart Shenyang, and Xiantao Municipal Government.  
    ● The solution includes an overall security solution that integrates rights management, hardware protection, and software hardening. 
    ● The solution provides mature and stable O&M capabilities, such as visualized installation & deployment, configuration management, system monitoring, task management, event management, system rights control, and system backup management.  
    ● The solution provides an all-in-one development environment for third-party applications and provides multiple smart service engines. 
    ● The solution provides the 7*24 omni-directional service capability and customized localization service capability. 
    Customer Benefits

    ● Make service innovations and boost competitiveness by generating user portraits, analyzing user behaviors, rapidly responding to customer requirements, and making precision marketing, and predicting product and service requirements (to dig out the profit-gaining opportunities).  
    ● Reinforce the financial risk control and management capability. 
    ● Mine massive data, promote the IT efficiency and scale effect, increase the data processing efficiency, improve user experience, and enhance the QoS. 

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