Engagement at a Glance

Banks are seeking breakthroughs for positive growth by exploring customer demand through in-depth analysis, innovating financial products, collaborating in multiple channels, controlling risks, and making other investments for the purpose of providing customers with more intelligent, convenient, and secure services in the next generation of “Smart Banking”. Based on a profound industry understanding and many years of accumulated experience, Pactera has formed comprehensive Smart Banking solutions and services designed to help banks achieve strategic transformation.

Client Background

Bank of China is one of five state-owned commercial banks, offering comprehensive financial services for customers in mainland China, Hong Kong, Macao, Taiwan and 37 countries, mainly engaged in commercial bank business, including corporate financial service, personal financial service, financial market business and many other businesses.

Business Challenge

  • Building an efficient and flexible interest rate risk and liquidity analysis system.
  • Through the new system, drive bank interest rate risk and liquidity management to a higher degree, and improves comprehensive management.
  • The future analysis system for BOC interest rate risk and liquidity management must be endowed with good scalability and powerful data processing capabilities.

Pactera Solution

  • Provide specific data processing embodiment for data layer architecture design.
  • Build a stable scalable data model to access the new data sources.
  • Complete the data mapping.
  • Design and implement the program for data storage, backup and recovery Provide data processing.
  • Develop the specific data processing interface.
  • Provide customized development for client.

Project Highlights

  • Built the data mart model based on customer, product and protocol themes.
  • Achieved more than 200 data interfaces.
  • Customized statement: To construct four static statements for interest rate risk and liquidity risk, G21\G22\G24 statements and two information batch statements.
  • Built three customer behavior analysis models for prepayment, exit from fixed deposit/withdrawing in advance and demand deposit.

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