A Practical Case Study: Incorporating Liquidity and Credit Risk within ERM and ALM to drive Risk-aware Business Decision-Making

This session takes a practical view related to the successful incorporation of Liquidity Risk and Credit Risk within ERM/ALM systems at two insurers, a regional insurer located in North American and a global insurer headquartered in the United Kingdom. While regulatory requirements were an important consideration, the key for both firms was to transform their business processes by providing actionable risk information to key business stakeholders. Participants will take away important lesson learned related to determining the appropriate implementation scope, data requirements and challenges, modeling choices and working across multiple departments and stakeholders to deliver tangible business benefits within a limited implementation timeframe. The handout will include functional architecture diagrams, modeling and methodology descriptions and examples of key deliverables to stakeholders. The audience will be involved via survey questions or polling (via smart phone if supported) regarding presentation topics.

  • Date:Monday, March 9
  • Time:10:35 AM - 11:50 AM
  • Session Type:Concurrent Session
  • Audience Level:2
  • Learning Objective 1::Make key technological and functional choices that allow your insurance firm to deploy a true ERM platform, which can address various business needs: from economic to regulatory capital, from asset and liability management to strategic asset allocation.
  • Learning Objective 2::Obtain a unified view of market and credit risk and improve your portfolio construction process on the basis of a reliable correlation structure, without hindering the computational performance.
  • Learning Objective 3::Meet new business and regulatory requirements around liquidity risk management by improving the analytics and their fruition across the ALM and investment functions, and integrate them in your wider ERM infrastructure.
Paolo Laureti
SS&C Algorithmics, Inc.
Andrew Dansereau
SS&C Algorithmics, Inc