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Creating effective revenue forecast models for CCAR using machine intelligence

Sponsored webinar: Ayasdi

Building accurate and defensible revenue forecast models that will stand up to the Federal Reserve’s scrutiny

THE PANEL

  • Michael Woods, principal data scientist for financial services, Ayasdi
  • Lourenco Miranda, managing director, operations risk quantification, capital and CCAR, AIG
  • Kenneth Swenson, senior vice-president and manager of operational risk modelling

The Federal Reserve-mandated Comprehensive Capital Analysis and Review (CCAR) and stress tests put tremendous pressure on banks to have accurate models in place that can demonstrate capital adequacy under stressed economic and financial conditions.

How do you ensure that you have accurate and defensible revenue forecast models that will stand up to the Federal Reserve’s scrutiny?

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