EPE Optimisation

Challenge

A major European Investment Bank’s trades were failing to be processed via internal expected positive exposure (“EPE”) methodology, leading to received detrimental current exposure method treatment for counterparty credit risk RWA purposes.

Solution

  • CPRA provided both subject matter expertise and project management to address populations of trades that were failing to be processed via the internal regulatory approved EPE methodology.
  • Two distinct workstreams were created to solve the main issues that were identified:

    A prototyping workstream to deal with trade populations that did not have a valuation methodology in the existing EPE calculation engine. Front office valuation engines were used to generate pathwise PVs that were then passed into the EPE engine to carry out portfolio level aggregation. CPRA provided subject matter expertise to assess the optimal simulation methodology for each of the different trade populations and to liaise with counterparty credit risk management to ensure regulatory requirements were met.

    Data optimisation workstream: whose primary focus was to address data flow issues which prevented the EPE calculation engines from processing trades . A detailed mapping of the data architecture was created to understand the understand existing flows from multiple cross-business systems into the EPE calculation engine. This was followed by a system migrations phase to optimise data flows to maximise the number of trades processed for EPE.

Result

The project delivered significant (multi EUR billion) counterparty credit risk RWA savings for the client.