Credit scoring, retail porfolio credit risk and decision making

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Credit scoring (CS) represents statistically calibrated and empirically validated prediction models to assess the risk of providing credit to a person or a business. CS models are relied on by all major financial institutions in North America. I have developed a CS model to assess the risk of lending to newly started businesses. This model is now in use by several major banks. The Intellectual Property (IP) has been sold to a Canadian business with four employees.  I also developed a scoring model that predicts the probability of commercialization for early stage IP-based ideas. The IP is being developed into a business service for use by Technology Transfer Offices, Venture Capitalists and alike and is in beta tests. I have also conducted research on methodological improvements for estimating CS models when there are missing data. Future research will develop new scoring models for non-traditional applications such as the assessment of franchisees and entrepreneurs seeking venture capital. Work will also be conducted on how experts in the innovation domain (e.g. Venture Capitalists) make decisions in the absence of scoring models and how scoring models may improve on experts' decision making accuracy. A final area of research concerns estimation of portfolio risk for retail credit portfolios. Banks are becoming forced by new regulation (Basle II) to estimate portfolio risk for retail credit portfolios. But there are no well researched models currently available. My contribution will lie in researching the possibility of applying, with suitable modifications, reduced-form models developed for commercial risk to retail credit portfolios.