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      REPORT
      VIDEO
      DBS Bank: Using Machine Learning to Automate ALM Reporting
      Winner of the 2024 Celent Model Risk Manager Award for Model Risk Manager for Data Foundations of AI
      21st March 2024
      //DBS Bank: Using Machine Learning to Automate ALM Reporting

      DBS' self-developed Movement Analyser is an intelligent tool to automate manual operations and bring advanced real time data analytics capabilities to DBS’s asset and liability management process. Using machine learning, it interprets complex and voluminous data sets and accelerate data insights to reduce time to value. The Movement Analyser is embedded into day-to-day liquidity risk reporting operations and has revolutionized the bank’s data investigation and analysis processes, thus resulting in higher efficiency in risk reporting production and increased accuracy of reports fully explained and substantiated by data.

      Key Benefits:

      • Automation of time-consuming manual processes

      • Improved data quality

      • Systematic analysis of bank’s ALM positions constantly improved by machine learning

      See webinar link below for a video interview with Ronnie Woo, Executive Director, DBS Risk Management.

      Author
      Ian Watson
      Ian Watson
      Head of Risk
      Ian Watson
      Details
      Geographic Focus
      Asia-Pacific
      Horizontal Topics
      Artificial Intelligence, BPM / RPA, Risk: Banking Risk, Risk: Financial Risk Management, Risk: Financial Services Risk
      Industry
      Corporate Banking