Explore Crisil, a company of S&P GlobalFormerly known as Global Research & Risk Solutions
August 19, 2025
Case study
Case study
We empowered a leading asset management firm by automating its sustainable investment eligibility decision model, delivering 95% workflow efficiency
August 19, 2025
Case study
Case study
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Background
- A leading US-based asset management firm sought to automate its sustainable investment eligibility decision model for a universe of 1,200 emerging market companies, based on its proprietary methodology
- The existing process was entirely manual-collecting ESG data from multiple vendors and applying the client’s rulebook to determine investment eligibility, which made the process time-consuming, error-prone and difficult to scale
Crisil Integral IQ solution
- We analyzed the detailed methodology document provided by the client, which laid out the rules, thresholds and data dependencies for determining investment eligibility
- The end-to-end workflow was automated using Python on Jupyter Notebook, starting with replacing the manual data collection process by retrieving over 30 ESG and financial metrics data for 1,200 companies from the client’s internal data ecosystem via API, which served as a centralized repository that stores ESG and financial data from external vendors
- We codified the client’s decision-making methodology, which involved applying specific thresholds, statistical tests and screening criteria, and generated investment eligibility decisions for all the emerging market companies
Client impact
- Reduced end-to-end turnaround time for generating investment eligibility decisions from 12 hours to 30 minutes-a 95% improvement in operational efficiency
- Replaced fragmented manual data collection with a robust, API-driven pipeline-enhancing data reliability, minimizing analyst intervention and streamlining downstream ESG analysis
- Developed a modular Python framework to support scalable deployment across regions and investment themes
