Formerly known as Global Research & Risk Solutions

  • Crisil Integral IQ
  • Asset Management
  • Automation
  • Business Transformation
  • Data Quality
  • Digital Transformation
  • Fixed Income
  • Investment Management
  • Operational Excellence
  • Performance Attribution
  • Power BI
  • Python
  • Scalability
February 26, 2026 Content Type Case study

Delivered 82% execution efficiency for a leading global asset manager through automation

February 26, 2026 Content Type Case study
 

Background

 

  • The fixed income performance attribution team of a leading global asset manager was facing operational bottlenecks in reporting workflows, leading to delays
  • Weekly and monthly attribution report generation was heavy on manual effort and prone to data quality issues, which affected reporting accuracy and decision-making confidence
  • Lack of standardized reporting formats made comparisons across portfolios difficult and slow report turnaround times impacted decision timelines of portfolio managers

Our solution

Automation and process transformation

  • Automated 16+ attribution report generation processes

Standardized reporting framework

  • Established consistent formats for cross-portfolio comparisons
  • Enhanced data quality controls

Infrastructure set-up

  • Set up centralized GitHub repositories and central servers
  • Improved version control, process documentation and collaboration

Ad hoc enhancements

  • Delivered the improvements portfolio managers wanted, including conversion of Excel reports into Power BI

Client impact

  • Improved overall efficiency by 82% through automation
  • Saved 1,285 hours annually across automated processes
  • Enhanced decision-making by portfolio managers with unified Power BI dashboards
  • Eliminated key person dependency and operational risk through centralized version control, ensuring uninterrupted client delivery and business continuity

Key transformation metrics

82%

Efficiency gain
 

1,285

Hours saved/ year

13

Processes automated

~15 days

Average delivery time

Tools and technology

Python

GitHub

Power BI

Central servers

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