John Birge is the Jerry W. and Carol L. Levin Distinguished Service Professor of Operations Management at the University of Chicago. He studies stochastic programming and large scale optimization. His June 2012 paper with Pedro Judice, Long-term bank balance sheet management: estimation and simulation of risk-factors is very relevant to Net Interest Margin Optimization and is worth discussion. Some earlier slides from a Birge talk on Stochastic Optimization in Asset Liability Management are here. He published a book titled Introduction to Stochastic Programming with Francois Louveaux in 2011. His google scholar page attests to a wide range of expertise and a rich publication history.
The 2012 paper proceeds from a one period model used to determine optimal bank policy under credit risk to a multiple period model defining stochastic processes for risk factors evolving from the interest rate and credit cycles. The idea is to enable balance sheet simulation over time and provide a capital allocation plan that achieves a predefined set of objectives. There is a good summary of the literature in this paper focussing on risk management applications and models. The authors present a Vasicek/Kupiec like process definition of the charge off rate, which is critical in formulating an interest rate/credit dynamics suitable for optimization. The Kupiec 2009 FDIC tech report, How Well Does the Vasicek-Basel AIRBModel Fit the Data? Evidence from a Long Time Seriesof Corporate Credit Rating Data deals with the autocorrelation of corporate bond default rates from 1920 to 2008 in setting regulatory capital adequacy levels in a bank risk framework. The key takeaway from Birge and Judice is one of the principal risk factors to model stochastically in bank ALM (possibly the main one) is the interaction of the interest rate and credit cycles relative to the underlying securities. The slippery part is getting a grip on the correlation of loss write-downs on the underlying securities (see Duffie et.al.,2009, Frailty Correlated Default).