Neural network detection of management fraud using published financial data

This paper uses a Artificial Neural Network (AutoNet) to develop a model for detecting management fraud. The study offers an in-depth examination of important publicly available predictors of fraudulent financial statements. We find a model with a high probability of detecting fraudulent financial statements on one sample. The study reinforces the validity and efficiency of AutoNet as a research tool and provides additional empirical evidence regarding the merits of suggested red flags for fraudulent financial statements. © 1998 John Wiley & Sons, Ltd.     

A fuzzy logic-driven multiple knowledge integration framework for improving the performance of expert systems

To maintain a high performance in an ill-structured situation, expert systems should depend on multiple sources of knowledge rather than a single type. For this reason, we propose multiple knowledge integration by using a fuzzy logic-driven framework. Types of knowledge being considered here are threefold: machine, expert and user. Machine knowledge is obtained by a back- propagation neural network model from historical instances of a target problem domain. Expert knowledge is related to interpreting the trends of external factors that seem to affect the target problem domain. User knowledge represents a user’s personal views about information given by both expert knowledge and machine knowledge. The target problem domain of this paper is one-week-ahead stock market stage prediction: Bull, Edged-up, Edged-down, and Bear. Extensive experiments with real data proved that the proposed fuzzy logic-driven framework for multiple knowledge integration can contribute significantly to improving the performance of expert systems. Copyright © 1998 John Wiley & Sons, Ltd.     

风险管控系统建设评价

风险管控评价是目前国内外理论界与实务界关注的重点,而关注焦点集中于风险管控系统运行期间的评价,对风险管控系统建设阶段的评价则鲜有涉及。本文以风险管控系统建设过程中的成本、进度和质量为对象,探讨如何构建和使用风险管控系统建设评价,为完善风险管控系统评价体系做有益的补充和尝试。     

舞弊治理：基于上市公司财务舞弊特征的分析

选取2003～2007年度5645家沪深两地上市公司为样本,首先对其中209家舞弊公司财务舞弊的影响因素做统计分析,明晰上市公司财务舞弊的特征;然后,根据舞弊公司不同特征进一步实证检验,得出大规模事务所的选择、股权集中度、公司规模与财务舞弊负相关,独立董事比例与财务舞弊成"U"型关系,但没有发现代表财务状况指标净资产收益率的显著性影响,究其原因,发现舞弊公司存在虚增利润以外的其他更多隐性盈余操纵手段.     

A multi-factor model for the risk management of portfolios

We propose a methodology for modelling the value at risk of a complex portfolio, based on an extension of the Ho, Stapleton and Subrahmanyam technique. We model the variance-covariance structure of up to seven variables. These could represent four country indices and three exchange rates, for example. In addition, the effect of an arbitrary number of orthogonal factors can be analysed. The system is illustrated by estimating the value at risk for a portfolio of international stocks where the factors are stock market indices and exchange rates, a portfolio of international bonds where the factors are interest rates as well as exchange rates, and a portfolio of interest rate derivatives in different currencies. In this last case, we model a two-factor term structure of interest rates in each of the currencies, valuing the derivatives at a future date using these term structures and the Black model. The model is applied for different fineness of the binomial density and computational accuracy and efficiency are estimated.
G13, G15, G21     

Can alert models for fraud protect the elderly clients of a financial institution?

ABSTRACT

Using account-level transaction data at a major financial institution, we predict the incidence of suspicious activity that can be related to the external financial fraud of its elderly clients. The data consists of over 5 million accounts of clients aged 70 years and older, and over 250 million transactions extending from January 2015 to August 2016. Our main focus is to improve the detection of alerts within a proprietorial transaction monitoring system. Using logistic regression, random forest and support vector machine learning techniques, together with corrections for imbalanced alert samples, we provide a new alert model for the protection of elderly clients at a financial institution, with out-of-sample predictive accuracy. Our findings show the relative influence of client traits and account activity in our select external fraud alert models.     

A validated expert system for decision making in corporate recovery

This paper describes INSOLVE—an expert system for corporate recovery decisions. INSOLVE was built to understand the decision-making processes of corporate recovery experts who deal with companies in financial difficulties. INSOLVE has been developed using a multi-phase process similar to that widely adopted in software engineering. The expert system is described in terms of the assessment task and interpretation models of CommonKADS. The detailed results of the validation of INSOLVE with 17 experts show that it is an accurate model of human expertise in this domain. Copyright © 1999 John Wiley & Sons, Ltd.     

Early-warning analysis for currency crises in emerging markets: A revisit with fuzzy clustering

Currency crises, also often called balance-of-payment crises, occur when massive capital outflows force a country to devalue or float its currency. The world-wide integration of capital markets since the 1980s and 1990s has increased the degree of capital mobility, which also determined a substantial turbulence in foreign exchange markets and frequent currency crises. In this paper, we explore advanced supporting instruments for predicting currency crises, based on an empirical study of the currency crisis episodes in 23 emerging markets around the world during the second half of last century. More specifically, we investigate the usefulness of prediction models built based on the fuzzy c-means method. First we build clustering models that partition data into a certain number of overlapping natural groups. Thereafter, we classify the data clusters into early-warning clusters and tranquil clusters. We compare the performance of our models with a conventional c-means clustering model and a benchmark probit model. The results show that the proposed models achieve a similar level of out-of-sample performance as the probit model and c-means model. The fuzzy approach also introduces additional explanatory advantages into the early-warning analysis process. Copyright © 2010 John Wiley & Sons, Ltd.     

商业银行内部风险管理体系及其职责

风险管理是商业银行的一项重要管理工作,从内部体系看,风险防控的三道防线是由经营部门、风险管理部门、内控合规部门和内审部门分别承担的,它们在风险防控上存在着交集,需要各司其职、明确分工,以提高风险管理效率。此外,各部门间的相互制约应当适度,风险管理部门的设置要计成本、讲效率。     

A framework for assessing the systemic risk of major financial institutions

In this paper we propose a framework for measuring and stress testing the systemic risk of a group of major financial institutions. The systemic risk is measured by the price of insurance against financial distress, which is based on ex ante measures of default probabilities of individual banks and forecasted asset return correlations. Importantly, using realized correlations estimated from high-frequency equity return data can significantly improve the accuracy of forecasted correlations. Our stress testing methodology, using an integrated micro–macro model, takes into account dynamic linkages between the health of major US banks and macro-financial conditions. Our results suggest that the theoretical insurance premium that would be charged to protect against losses that equal or exceed 15% of total liabilities of 12 major US financial firms stood at $110 billion in March 2008 and had a projected upper bound of $250 billion in July 2008.     

基于战略风险管理模式下的养老保险公司风险管理分析

战略风险管理模式是金融企业比较流行的一种全面风险管理模型。本文在分析养老保险公司业务经营及风险管理特殊性的基础上,应用战略风险管理基本思想,提出了当前形势下养老保险公司风险管理的核心问题,并对公司目前面临的风险类别、风险因素以及风险管控措施进行了分析研究。     

A new approach to assessing model risk in high dimensions

A central problem for regulators and risk managers concerns the risk assessment of an aggregate portfolio defined as the sum of d individual dependent risks $X_i$. This problem is mainly a numerical issue once the joint distribution of $\left(X_1\text{,}{X}_2\text{,}\dots \text{,}{X}_d\right)$ is fully specified. Unfortunately, while the marginal distributions of the risks $X_i$ are often known, their interaction (dependence) is usually either unknown or only partially known, implying that any risk assessment of the portfolio is subject to model uncertainty.Previous academic research has focused on the maximum and minimum possible values of a given risk measure of the portfolio when only the marginal distributions are known. This approach leads to wide bounds, as all information on the dependence is ignored. In this paper, we integrate, in a natural way, available information on the multivariate dependence. We make use of the Rearrangement Algorithm (RA) of Embrechts et al. (2013) to provide bounds for the risk measure at hand. We observe that incorporating the information of a well-fitted multivariate model may, or may not, lead to much tighter bounds, a feature that also depends on the risk measure used. In particular, the risk of underestimating the Value-at-Risk at a very high confidence level (as used in Basel II) is typically significant, even if one knows the multivariate distribution almost completely.Our results make it possible to determine which risk measures can benefit from adding dependence information (i.e., leading to narrower bounds when used to assess portfolio risk) and, hence, to identify those situations for which it would be meaningful to develop accurate multivariate models.     

An inductive reasoning approach for building system safety risk models of aviation accidents

An inductive reasoning approach is employed to develop a prototype hybrid decision support tool whose main objective is to build probabilistic causal models representing the safety risk involved in aviation accidents. In this context, 15 aircraft accidents representative of five major accident types are selected to build an initial seed for the case‐base of the prototype tool. Consequently, within each individual accident model, main clusters of causal factors are identified for inclusion in the initial seed, thereby improving, both quantitatively and qualitatively, the case‐base of the prototype tool. A new methodology developed specifically for indexing aviation accidents into databases is used for indexing the initial seed into the case‐base of the tool. The resulting product is a highly customized conversational decision support tool that provides solution possibilities in the form of probabilistic causal models of accident scenarios retrieved and ranked according to their similarity to the current accident that the intended user investigates.     

Tax risk management and the multinational enterprise

The financial scandals in the United States and other countries ushered in financial reporting and corporate governance reforms that extend beyond the U.S. Sarbanes-Oxley Act of 2002 (SOX). These initiatives have increased the international financial community's awareness of the importance of risk management and internal controls. Tax risk management and related internal controls have been accorded less focus than risk management generally. The purpose of this research is to describe the current state of tax risk management of multinational enterprises (MNEs) by reporting survey responses from chief financial officers (CFOs) of U.S. and non-U.S. MNEs. The research shows that significant progress has been made by large MNEs in developing and implementing both general and tax risk management policies. The results provide guidance in identifying the loci and impact of organizational tax risk and indicate that respondents do not perceive alarming degrees of tax risk in their organizations. The study reveals a remarkable degree of similarity in U.S. and foreign firm responses and demonstrates, unexpectedly, that existing reporting structures enable CFOs to shift a significant degree of tax risk management to heads of tax.     

养老金业务全面风险管理

随着中国经济和金融体制改革的不断深入,社会保障制度特别是养老金制度也发生了剧烈的变革,逐步建立起社会统筹和个人账户相结合的养老保障体系,包括了国家基本养老保险、企业年金和个人储蓄养老保险三个支柱,养老基金也随之正式登陆中国资本市场。养老金是退休人员的养命钱,其性质决定了它在满足盈利性、流动性的前提下必须保持更低风险的特点,决定了它在风险管理上的高要求。     

Choosing project risk management techniques. A theoretical framework

The pressure for increasing quality while reducing time and costs places particular emphasis on managing risk in projects. To this end, several models and techniques have been developed in literature and applied in practice, so that there is a strong need for clarifying when and how each of them should be used. At the same time, knowledge about risk management is becoming a matter of paramount importance to effectively deal with the complexity of projects. However, communication and knowledge creation are not easy tasks, especially when dealing with uncertainty, because decision-making is often fragmented and a comprehensive perspective on the goals, opportunities and threats of a project is missing. With the purpose of providing guidelines for the selection of risk techniques taking into account the most relevant aspects characterising the managerial and operational scenario of a project, a theoretical framework to classify these techniques is proposed. Based on a literature review of the criteria to categorise risk techniques, three dimensions are defined: the phase of the risk management process, the phase of the project life cycle and the corporate maturity towards risk. The taxonomy is then applied to a wide selection of risk techniques according to their documented applications. This work helps to integrate the risk management and the knowledge management processes. Future research efforts will be directed towards refining the framework and testing it in multiple industries.     

The dispositif of risk management: Reconstructing risk management after the financial crisis

Despite its dubious role during the global financial crisis of 2008, risk management has continued its expansion. This paper addresses the question why risk management, in the face of its evident failure to manage risks during the crisis, has retained its importance even today. We build on the existing critical literature on risk management (Power, 2007) and advance it by introducing a more rigorous consideration of power. We refer to the notion of the “permanent state of exception” as conceptualized by the Italian social theorist Giorgio Agamben, 1998, Agamben, 2005 in order to argue that risk is a powerful social category as it reflects a potential exception, challenging norms as well as normalizing forms of control. We conclude that a dispositif of risk management, an assemblage of institutions, regulations and models, lies at the heart of risk management. This dispositif provides elites engaged in risk management with an argument that allows them – in exceptional situations – to take extraordinary measures which cannot be rescinded after the initial state of exception has ended. The logic of the state of exception can be used as a discursive resource and adds to, but also gradually replaces, other forms of management control. Our study contributes to management control theory by focusing on post-disciplinary forms of control and provides a novel focus on how elites use management control systems for their own interests.     

Corporate governance and risk management: The role of risk management and compensation committees

This paper examines the role of compensation and risk committees in managing and monitoring the risk behaviour of Australian financial firms in the period leading up to the global financial crisis (2006–2008). This empirical study of 711 observations of financial sector firms demonstrates how the coordination of risk management and compensation committees reduces information asymmetry. The study shows that the composition of the risk and compensation committees is positively associated with risk, which, in turn, is associated with firm performance. More importantly, information asymmetry is reduced when a director is a member of both the risk and compensation committees which moderate the negative association between risk and firm performance for firms with high risk.     

Data for outcome payments or information for care? A sociotechnical analysis of the management information system in the implementation of a social impact bond

ABSTRACT

Social Impact Bonds (SIBs) are a policy intervention designed to explicitly link the activity of social interventions to outcome payments. Despite a burgeoning literature on SIBs there is a lack of evidence in relation to the information system characteristics and accounting mechanisms of SIBs. Applying a multi-dimensional sociotechnical lens to a case study of a SIB allows us to reveal the current problematic convergence of public management and information systems. The authors found that an information system within a SIB is introduced and adapted to increasingly prioritize the production of data for payment over documenting care accounts to support improved provision. The ?ndings of this paper also suggest that claims of SIBs as an innovation are limited as they are subject to the familiar problems of New Public Management practice, in the way they shape the design and use of the data in governance, management and service delivery practices.