The basic premise of risk-based auditing is that more (fewer) audit resources should be allocated to accounts that are more (less) likely to be misstated. However, financial reporting managers can exploit such allocations by intentionally misstating balances that are less likely to draw auditor attention. If auditors do not recognize this strategic implication of risk-based auditing, undetected misstatements among ostensibly low-risk accounts could be much more common than traditional risk assessment procedures suggest. The purpose of this study is to examine whether prompting auditors to form beliefs about managers’ expectations of, and responses to, audit strategies can enhance auditors’ sensitivity to the strategic risk of fraud among accounts typically considered low-risk. Using a multi-account audit game, I find that auditors do not naturally attune to strategic risks but instead tend to focus resources on “highrisk” accounts. However, when auditors are prompted to reason strategically, they utilize more resources and devote that increase almost entirely to “low-risk” accounts. I also find that, although increasing available resources does result in an overall increase in the amount of utilized resources, the relative effect of the strategic prompt is robust to the level of available audit resources. / text

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

BACKGROUND Patient safety, reducing medical errors and risk management have become a global public health and administrative issue. Population-based studies around the world have alerted high rates of preventable medical errors and deaths. In response, a global effort agreed on a World Health Assembly resolution on patient safety. The World Alliance for Patient Safety guideline and the Conceptual Framework for the International Classification for Patient Safety have been launched by the World Health Organization (WHO) to galvanize and facilitate efforts by all Member States to make health care safer. The guidelines introduced adverse event reporting and focus on reporting and learning to improve the safety of patient care. The WHO suggested a conceptual framework for patient safety providing comprehensive understanding of the domains of patient safety. It represents a continuous learning and improvement cycle emphasizing on proactive (identification of risk, prevention, detection, reduction of risk) and reactive (incident recovery, system resilience) risk management. The ultimate measure of a successful incident reporting system is whether the information it yields is used appropriately to improve patient and organization safety. OBJECTIVES To systematic review literature to determine incident reporting systems improve patient outcomes and organization outcomes, and to identify successful characteristics of incident reporting system which information it yields is used appropriately to improve patient and organization safety, and to investigate if the incident reporting system can serve as an interface to support the (inform and influence) information flows in the WHO’s Conceptual Framework for the International Classification for Patient Safety. METHODS Two bibliography databases, Medline and Embase via OvidSP, were systematically searched using search keywords of ‘incident reporting’, ‘patient / organization outcomes’. Quality appraisal, data extraction were conducted on literature which met the inclusion criteria. Narrative synthesis was conducted. RESULTS A total of 584 citations were initially identified and 6 studies were finally included in this systematic review. The methodological quality of the 6 included studies was generally average to poor. The 6 included studies could be classified into 3 groups by research question and intervention strategies examined 1) case series on incident reporting system; 2) comparison study on two main streams of incident reporting systems: routine incident reporting system versus structured case note / chart review; and 3) review of incident reporting systems. Successful characteristics of incident reporting system identified including confidential, non-punitive, expert analysis, system-oriented, responsive, standardized taxonomy coding, clarified and unified concepts of incident reporting system, voluntary reporting, facilitation reporting, proper training and health informatics infrastructure support. Quantitative and qualitative evidences were identified that incident reporting system could serve as an interface to support inform and influence types of information flows in the WHO’s Conceptual Framework for the ICPS. However, no evidence could be found that incident reporting systems could directly improve patient outcomes and organization outcomes. CONCLUSION This systematic review found no evidence that incident reporting systems could directly improve patient outcomes and organization outcomes, but the systems could serve as an interface to support information flows in the WHO’s Conceptual Framework for the ICPS. Successful characteristics of an incident reporting system were identified coherent to the WHO’s recommendations. Future studies can further examine the causation relationship between incident reporting systems and the process components by applying the Donabedian’s structure-process-outcome model. / published_or_final_version / Public Health / Master / Master of Public Health

The procurement of commodity materials for production is an important issue in supply chain management. Effective procurement should consider both uncertain customer demand and fluctuating commodity price which, when act together, give rise to the procurement risk. To protect the bottom line, a manufacturer has to plan its procurement activities with special attention given to such procurement risk. Existing research has studied the use of exchange market-traded commodities in mitigating procurement risk. This study addresses the case of a manufacturer with long-term procurement commitments who wishes to hedge against the risk exposure by using long-dated futures contracts. In the commodities markets, however, long-dated futures are often illiquid or even unavailable, thus making the hedge ineffective. Alternatively, in a stack-and-roll hedge, the hedging positions are rolled forward in actively traded short-dated futures contracts of equal maturity until the procurement is executed. This in effect replicates the long-term futures contract in performing a hedge. This study therefore aims at developing a dynamic stack-and-roll approach that can effectively manage the long maturity procurement risk. The proposed dynamic stack-and-roll approach is inherently a discrete-time hedging strategy that divides the procurement planning horizon into multiple decision stages. The nearby futures are adopted as the short-dated futures as they are typically liquid. The hedging positions are adjusted periodically in response to the commodity price behaviour and updated information about the forward customer demand. For a manufacturer who wishes to mitigate the procurement risk as well as maximise the terminal revenue after the procurement, the mean-variance objective function is employed to model the manufacturer’s risk aversion behaviour. Then, a dynamic program formulation of the approach is presented for determining a closed-form expression of the optimal hedging positions. Notice that the hedging policy is a time-consistent mean-variance policy in discrete-time, in contrast to the existing discrete hedging approaches that employ minimum-variance policies. In this study, the commodity prices are modelled by a fractal nonlinear regression process that employs a recurrent wavelet neural network as the nonlinear function. The purpose of this arrangement is to incorporate the fractal properties discovered in commodity prices series. In the wavelet transform domain, fractal self-similarity and self-affinity information of the price series over a certain time scale can be extracted. The Extended Kalman Filter (EKF) algorithm is applied to train the neural network for its lower training error comparing with classical gradient descent algorithms. Monthly returns and volatility of commodity prices are estimated by daily returns data in order to increase the estimation accuracy and facilitate effective hedging. The demand information is updated stage by stage using Bayesian inference. The updating process are defined and adapted to a filtration, which can be regarded as the information received at the beginning of each decision stage. Numerical experiments are carried out to evaluate the performance of the proposed stack-and-roll approach. The results show that the proposed approach robustly outperforms other hedging strategies that employ minimum-variance or naïve policies, and effectively mitigate the procurement risk. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Over the past decades, researchers in economics, financial mathematics and actuarial science have introduced results to the concept of comonotonicity in their respective fields of interest. Comonotonicity is a very strong dependence structure and is very often mistaken as a dependence structure that is too extreme and unrealistic. However, the concept of comonotonicity is actually a useful tool for solving several research and practical problems in capital allocation, risk sharing and optimal allocation. The first topic of this thesis is focused on the application of comonotonicity in optimal capital allocation. The Enterprise Risk Management process of a financial institution usually contains a procedure to allocate the total risk capital of the company into its different business units. Dhaene et al. (2012) proposed a unifying capital allocation framework by considering some general deviation measures. This general framework is extended to a more general optimization problem of minimizing separable convex function with a linear constraint and box constraints. A new approach of solving this constrained minimization problem explicitly by the concept of comonotonicity is developed. Instead of the traditional Kuhn-Tucker theory, a method of expressing each convex function as the expected stop-loss of some suitable random variable is used to solve the optimization problem. Then, some results in convex analysis with infimum-convolution are derived using the result of this new approach. Next, Borch's theorem is revisited from the perspective of comonotonicity. The optimal solution to the Pareto optimal risk-sharing problem can be obtained by the Lagrangian method or variational arguments. Here, I propose a new method, which is based on a Breeden-Litzanbeger type integral representation formula for increasing convex functions. It enables the transform of the objective function into a sum of mixtures of stop-losses. Necessary conditions for the existence of optimal solution are then discussed. The explicit solution obtained allows us to show that the risk-sharing problem is indeed a “point-wise” problem, and hence the value function can be obtained immediately using the notion of supremum-convolution in convex analysis. In addition to the above classical risk-sharing and capital allocation problems, the problem of minimizing a separable convex objective subject to an ordering restriction is then studied. Best et al. (2000) proposed a pool adjacent violators algorithm to compute the optimal solution. Instead, we show that using the concept of comonotonicity and the technique of dynamic programming the solution can be derived in a recursive manner. By identifying the right-hand derivative of the convex functions with distribution functions of some suitable random variables, we rewrite the objective function into a sum of expected deviations. This transformation and the fact that the expected deviation is a convex function enable us to solve the minimizing problem. / published_or_final_version / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

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D. Tech. Civil Engineering / Construction contracts have provisional clauses to control financial risks, but studies have shown that cost overruns are still common, which require the inclusion of additional management techniques to improve cost estimates. The research investigated, analysed and identified the shortcomings that exist within the current mechanisms to manage financial risk. A new risk ranking model that can be used to eliminate construction cost overruns in South Africa was developed. The study sought the views from a variety of construction professionals, based on knowledge and experiences within their own organisations, to explore new mechanisms to limit the risk impact of persistent cost overruns.