Risk Management

Wagner Math Finance has worked in the area of developing value-at-risk models for credit risk management for several years, helping our clients reserve capital for losses and counterparty defaults, as well as for making risk aware allocation of capital to multiple enterprises. In joint projects with KPMG, the methods have been applied to the loan and equity investment portfolio of the International Finance Corporation (IFC), an arm of the World Bank, and to the loan portfolio of Hanvit Bank of Korea.

An essential feature of these models is that they include both a stochastic systematic risk Z(t) factor affecting all borrowers whose sample paths are generated by Monte Carlo methods, as well as borrower specific risk factors which, conditioned on Z(t), are independent of one another. This hybrid approach allows the model to retain much of the computational efficiency of purely analytic methods and does not restrict the value-at-risk distribution to be Gaussian.

Please contact consultus@pa.wagner.com to inquire about our consulting services in credit risk management.