2018

Oct 11 Mumbai

Credit Risk Analysis: The CRISIL Way - Certification Programme

Training dates - October 11 & 12, 2018

Training locaton - Mumbai

Training fee - ₹45,000 + applicable taxes

 

 

Summary

 

The surge in bad loans and fluctuation in asset quality in the past four years has brought the spotlight back on the fundamental tenet of giving credit – undertaking thorough credit assessment and appropriately pricing risk.

 

Banks, reeling under a mountain of bad debt, have accordingly started to work on ways to improve the efficacy of the credit assessment process and to price loans in relation to credit risk.

 

In the context, CRISIL has introduced a two-day training programme to enable credit officers to make better lending decisions.

 

The programme leverages CRISIL’s expertise in credit risk assessment and building credit assessment frameworks, and uses a case study-based approach developed using CRISIL’s credit risk evaluation framework. It starts with the core concepts and basic principles of credit risk and goes on to cover advanced concepts and their application in complex cases.

 

Target Audience

 

  • Credit officers with banks and NBFCs
  • Audit and risk management teams
  • Credit analysts with Investment managers

Programme highlights

 

  • Use of CRISIL Ratings framework: The programme uses the time-tested framework that the CRISIL Ratings team applies to 15,000+ companies every year 
  • Training by CRISIL experts: Training is imparted by CRISIL experts who have more than a decade of experience in industry and company research
  • Quantix-powered data & analytics: The programme leverages Quantix, CRISIL’s data and analytics platform with information on 25,000+ companies across 200+ industries
  • Real life case studies & examples: The case studies are handpicked by our Ratings and Research teams to bring out the practical nuances and challenges in Credit decisions
  • CRISIL’s internal approach to forecasting: The programme introduces the CRISIL way of financial forecasting that goes beyond trend extrapolation and builds strongly on principles of basic causation