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Research carried out at the University of Southampton into banking, economic growth and development has made Professor Richard Werner a trusted source of advice for economic policy-makers at the highest level, for example for the Financial Services Authority, the Independent Banking Commission, the International Monetary Fund and the Bank of England. Through articles, books and many media contributions, he has promoted a greater public understanding of economics and the financial crisis. His credit creation analysis has also been adopted by two investment funds in their portfolio management, leading to financial gains for investors, outperforming the FTSE100.
Credit scoring, the process of estimating the risk of lending to consumers, has traditionally estimated the likelihood of default over a fixed period, usually 12 months. Research carried out at Southampton's School of Management has led to a gradual shift by many financial institutions in the UK and elsewhere towards an alternative method that estimates default over any period. This approach provides accurate risk estimates over any time period. It also allows for the inclusion in the "scorecard" of economic conditions and the lending rates charged — features whose absence from previous scorecards was identified as contributing to the sub-prime mortgage crisis.
Research of Professor Brigo in the areas of credit risk, pricing models for the valuation of counterparty risk, and the development of accurate calibration methods of various credit risk models has generated significant impact both on public policy and on practitioners and professional services. His models were implemented and his calibration methods adopted in the financial industry. The significance attached to his work by the industry also resulted in a collaboration with the German regulator (BAFIN). Further evidence of his impact can be found in the fact that a Court of Law based its analysis in a financial intermediation case on Brigo's research.
Research by the School's Centre for Finance, Credit and Macroeconomics (CFCM) on the monetary transmission mechanism has been influential in improving the design, implementation and effectiveness of the monetary policies of a number of central banks, including the Bank of England, Banque de France and the European Central Bank. The research has influenced changes in the way that official monetary aggregates are measured so as to capture the impact of non-bank financial institutions on the money supply and credit availability, and in better understanding of how monetary policy affects different interest rates. This in turn has allowed for improved control by central banks of their policy targets, and for better understanding of the effects of their monetary policies on economic activity and inflation.
The focus of this impact is the effect of the Global Vector Autoregressive (GVAR) project on international organisations such as the International Monetary Fund (IMF) and the European Central Bank (ECB) as well as its use by commercial organisations such as the Economist Intelligence Unit and the Asian Development Bank. The impact has enhanced the tools used by the ECB for communicating its policies. It has also allowed the IMF to demonstrate the effects of oil prices. The Economist Intelligence Unit found it an effective framework for assessing a wide-range of scenarios. The Asian Development Bank uses the GVAR model for forecasting in Asia.
The School of Mathematics at Cardiff University has developed important statistical and mathematical models for forecasting consumer buying behaviour. Enhancements to classical models, inspired by extensively studying their statistical properties, have allowed us to exploit their vast potential to benefit the sales and marketing strategies of manufacturing and retail organisations. The research has been endorsed and applied by Nielsen, the #1 global market research organisation that provides services to clients in 100 countries. Nielsen has utilised the models to augment profits and retain their globally leading corporate position. This has led to a US$30 million investment and been used to benefit major consumer goods manufacturers such as Pepsi, Kraft, Unilever, Nestlé and Procter & Gamble. Therefore the impact claimed is financial. Moreover, impact is also measurable in terms of public engagement since the work has been disseminated at a wide range of national and international corporate events and conferences. Beneficiaries include Tesco, Sainsbury's, GlaxoSmithKline and Mindshare WW.
Research on risk assessment of SMEs conducted at the University of Edinburgh Business School (2005-current) in conjunction with the international credit industry has improved understanding of SME behaviour with a view to assisting lending bodies in their decision-making. It has led to refinements in the process of developing commercial credit risk models by providing valuable additional details to enhance existing models. It has developed methodologies now used by some of the leading lenders [text removed for publication] to cut the cost of providing credit, thereby making more credit available to SMEs. The reach of the work has extended across 349 credit practitioners from 38 countries.
According to the European Commission, over ninety nine per cent of Europe's businesses are SMEs. Their success is crucial for local enterprise, employment and taxation revenue. However, such organisations face major obstacles to accessing additional equity that typically are not faced by large corporations. This research has changed the way some Italian SMEs make decisions about the relative proportion of short-and long-term debt through adopting an optimisation model developed at Leicester's School of Management and which is now being rolled out in Italy and the UK. The Italian firms involved have reduced their cost of borrowing and enhanced their reputation with banks, hence making it easier for them to access more credit.
This case study describes impact resulting from research on assessing the performance of credit scoring models conducted by the Consumer Credit / Retail Banking Research Group of the Mathematics Department at Imperial College. The group's work has influenced both high-level industry strategies for developing scoring models, and also low-level performance measures for which such models are developed, refined and evaluated. We describe examples of companies or bodies that have benefitted from improved credit scoring models, including Prescient Models (a US credit scoring company), Experian and the US Office of the Comptroller of Currency. The group has established a very significant reputation for a wide range of commercially valuable work in this area — to the extent that the group received the major Credit Collections and Risk industry award for Contributions to the Credit Industry in 2012.
The research group investigated UK borrowers' payment protection insurance (PPI) decision making using randomised-groups experiments and a novel cognitive process-tracing methodology. This contributed to the design and interpretation of a consumer survey, a key element of the Office of Fair Trading's 2006 market study of PPI, via the involvement of the principal investigator as consultant. The survey played a major role in the referral of PPI to the competition commission and subsequent major changes implemented by the FSA to the regulation of the PPI market and associated consumer support. This has been of direct benefit to millions of UK borrowers and has also had a major impact on the competitiveness of the UK personal insurance market.