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Society For Risk Analysis Annual Meeting 2008

Risk Analysis: the Science and the Art

Session Schedule & Abstracts

* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

M2-E Corporate and Financial Management Room: Commonwealth B   10:30 AM-Noon

Chair(s): Clark Nardinelli

M2-E.1  10:30  Corporate sustainability initiatives and their food safety risks: The role of certification, traceability, and authentication. Spink J*, Phillips A; Michigan State University, National Food Safety & Toxicology Center (NFSTC)   spinkj@msu.edu Abstract: Economic food fraud, or food profiteering, is not new though the huge opportunity of the growing consumer preference for sustainable products creates tremendous new momentum for this risk. As with other food safety and food defense initiatives, a root solution is in supplier certification, product traceability, and product authentication. While the risk of conventionally grown food products co-mingled with organic food products may seem merely a technicality, diethylene glycol in cough syrup is deadly. This presentation builds off previous SRA journal articles that define the sustainability issues for risk managers, to now examine specific public health, economic, and brand equity risks associated with the consumer drive towards sustainable products. The major retailers and brand manufacturers are moving from initiating corporate sustainability programs, to implementing sustainability initiatives across their entire organizations, to the next stage of incorporating focused standard operating procedures across all their business. These procedures expand from seeking and buying a sustainable product to assuring that the product is safe and authentic. The presentation leverages experience with corporate sustainability initiatives and the work of the Michigan State University’s Packaging for Food and Product Protection (P-FAPP) Initiative.

M2-E.2  10:50  Art or Science – Can these two paradigms co-exist within the field of Risk Management? HALL I*; Lloyds TSB Asset Finance   ian_s_hall@hotmail.com Abstract: Over the past 5 years, Corporate Lenders have seen the benefits of developing automated scoring solutions allowing for operational efficiencies and a reduction in the costs of processing applications for new credit applications. Additionally, the segmentation of portfolios into low, medium and high risk customers, has allowed institutions to price risk more effectively and become more astute at using rationed capital. Changes in legislation and the instability of the global economy threaten these efficiencies through a change in the environment in which these businesses compete. The question for Corporate Lenders therefore, is should they trust statistically based credit models, or allow themselves to become more reliant on subjective assessments of the risk of non payment by customers based upon the mental models of ‘expert’ actors within the business. This paper seeks to consider how the art of Risk Management can be used to supplement statistical models and allow an organisation to navigate through the rapidly changing landscape of the business environment.

M2-E.3  11:10  Risk ranking procedures for fraud signals detected in trade data. Kopustinskas V*, Arsenis S, Perrotta D; Institute for Protection and Security of Citizens, Joint Research Center, European Commission   vytis.kopustinskas@jrc.it Abstract: JRC action Statistics and Information Technology for Anti-fraud and Security has developed statistical methods to be applied on trade data and produce sets of trade flows, i.e., combinations of Product, Origin and Destination suspected for possible fraud activities against the budget of the European Community. Two of the main and most mature statistical techniques, implemented in proprietary software, are detecting sudden, unexpected, abrupt increases in trade (called spikes) and price outliers. A large number of signals are usually detected in a single dataset; typically several hundreds. Therefore, a prioritization procedure of the signals detected is needed for anti-fraud investigation activities. This paper presents the development of quantitative risk indicators to detect fraud in trade, against the budget of the European Community. Such indicators are developed for use by analysts. Indicators are based on classical risk definition. The paper presents a number of such indicators and discusses their strengths and weaknesses.

M2-E.4  11:30  A Bayesian Methodology for Uncertainty Analysis of Default. Kazemi R*, Mosleh A; University of Maryland-college park   REZAKAZEMI@GMAIL.COM Abstract: Financial risk involves any risk associated with financing. It includes investment related risks (i.e. capital risk), insurance related risks, business related risks and debt related risks (i.e. credit risk). Credit risk is endured by creditor in case of obligor’s failure or refusal to repay the debt in principal or interest. Credit risk is a natural consequence of a dynamic economy and since it can not be avoided it is best to be assessed as accurately as possible. Many models have been developed to estimate credit risk. In fact rating agencies date back to the 19th century. In the past two decades, the Basel committee on banking supervision has imposed regulatory capital requirements for credit risk that has led many large banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with precision. A major component of credit risk assessment is estimating probability of default. Rating agencies express their beliefs about probability of default and transition probabilities of various firms in their annual reports. As the objective of this paper, through uncertainty analysis, we attempt to bind the true value of default within the smallest range of possible values with some confidence. For uncertainty analysis the proposed Bayesian framework, uses the estimates from one or more rating agencies and incorporates their historical accuracy in estimating default risk and transition probabilities and ultimately provides better, more accurate estimates. The default probability estimations of rating agencies and their difference with the true values of default which have actually occurred over several years (performance data) are used as evidence to form the likelihood function in our methodology. The methodology is further designed to utilize multiple estimations from multiple models (from different rating agencies). Several examples are presented to demonstrate how the proposed methodology assesses the probability of default such that it exceeds the estimations of all the models individually, in accuracy.

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