STREAMLINING OPERATIONS
[ STREAMLINING OPERATIONS ]
HOW MACHINE LEARNING TRANSFORMED STANDING SETTLEMENT INSTRUCTION DATA PROCESSING, ACHIEVING 35% FTE SAVINGS AND 100% ACCURACY IN 4 MONTHS
- Problem
- Key Challenges?
- Our Solution
- The Result
The Standing Settlement Instruction Data
Enter The Organization In Different Formats (1000+ File
Formats) Which Took Significant Time And Resources.
The Goal Was To Optimize And Create Capacity.
- This caused transcription and translation challenges.
- Poor data quality resulting in low data consumption.
- Introduce Work Fusion’s Machine Learning
capabilities - Eliminate, Consolidate, Standardized the formats
where possible.
Taught the ML 35 different file formats. - Subsequently performed randomized tolerance
testing. - Altered the content of the recognized formats
and introduced new formats.
- 35% FTE saving without compromising data
quality. - 95% automation and 5% routed manually.
- Within 4 months program was delivering 100%
accuracy.
