Bagging集成方法在保险欺诈识别中的应用研究

保险欺诈不仅危及保险公司的正常经营,增加投保人的负担,甚至有可能影响到国家的金融稳定。随着大数据时代的到来,保险反欺诈亟需引入革命性技术。Bagging集成方法以其可调节模型结构、易于部署、参数空间可控、支持并行运算等特点成为保险公司进行保险反欺诈一个好的选择。Bagging方法主要包括Bagging算法、Random Subspace算法、Random Patches算法,它们又能与不同基学习器结合构成新的分支算法及算法特例。本文基于这些算法对保险欺诈问题进行了实证检验,分析了各算法及与基学习器的适用性问题,以及基学习器个数对算法表现的影响。分析发现:针对保险欺诈识别问题,在Bagging、Random Subspace、Random Patches三者之中,Random Patches算法的表现最好,Bagging的运行时间最短;不同算法适用的基学习器不同,但总体来说最适合Bagging集成方法的是决策树;基于决策树的方法都一致选择是否委托律师代理作为最重要的特征;基学习器个数对不同Bagging算法表现的影响并不一致。     

Insurance Fraud

Insurance fraud is a major problem in the United States at the beginning of the 21st century. It has no doubt existed wherever insurance policies are written, taking different forms to suit the economic time and coverage available. From the advent of “railway spine” in the 19th century to “trip and falls” and “whiplash” in the 20th century, individuals and groups have always been willing and able to file bogus claims. The term fraud carries the connotation that the activity is illegal with prosecution and sanctions as the threatened outcomes. The reality of current discourse is a much more expanded notion of fraud that covers many unnecessary, unwanted, and opportunistic manipulations of the system that fall short of criminal behavior. Those may be better suited to civil adjudicators or legislative reformers. This survey describes the range of these moral hazards arising from asymmetric information, especially in claiming behavior, and the steps taken to model the process and enhance detection and deterrence of fraud in its widest sense. The fundamental problem for insurers coping with both fraud and systemic abuse is to devise a mechanism that efficiently sorts claims into categories that require the acquisition of additional information at a cost. The five articles published in this issue of the Journal of Risk and Insurance advance our knowledge on several fronts. Measurement, detection, and deterrence of fraud are advanced through statistical models, intelligent technologies are applied to informative databases to provide for efficient claim sorts, and strategic analysis is applied to property‐liability and health insurance situations.     

Centralizing Insurance Fraud Investigation

The study of insurance fraud and its remedy is a hot topic of research, mainly because the problem of insurance fraud is so widespread. In the United States many state governments have setup agencies to combat fraud. These Insurance Fraud Bureaus (IFB) are typically established to gather information about potential fraudulent claims, and to advise prosecuting officers on the nature of each offense. This paper presents the conditions under which more fraud will be observed in an economy where an IFB conducts all audits than in an economy where each insurance company is responsible for its own investigation. Even if fraud increases, policyholders may be better off than in economy lacking an IFB. One unambiguous case where policyholders are always better is when the IFB conducts every investigation at a cost that is equal to the industry's average.     

Claims Auditing in Automobile Insurance: Fraud Detection and Deterrence Objectives

Research on insurer management of opportunism in claiming has developed in two parallel literatures. One is a theoretical literature on insurance contracting that yields predictions about the nature of optimal auditing strategies for the deterrence of fraud. The other is a literature based upon statistical analysis of claims that yields empirical strategies for the detection of fraudulent claims. This article links the two literatures by providing an empirical assessment of insurers’ auditing practices in relation to theoretical predictions. The analysis makes use of a data set on the disposition of more than 1,000 randomly selected automobile personal injury protection claims settled in the state of Massachusetts. The findings of the article are consistent with the use of rational auditing strategies by insurers and with the use of audits for both deterrence and detection.     

Detection of Automobile Insurance Fraud With Discrete Choice Models and Misclassified Claims

The insurance industry is concerned with the detection of fraudulent behavior. The number of automobile claims involving some kind of suspicious circumstance is high and has become a subject of major interest for companies. This article demonstrates the performance of binary choice models for fraud detection and implements models for misclassification in the response variable. A database from the Spanish insurance market that contains honest and fraudulent claims is used. The estimation of the probability of omission provides an estimate of the percentage of fraudulent claims that are not detected by the logistic regression model.     

保险诈骗的成因、类型与防范

随着保险业的迅猛发展,保险诈骗案件也日渐增多。保险欺诈不仅给保险业造成巨额经济损失,损害了诚实投保人的利益．而且严重扰乱保险市场秩序,破坏了社会的稳定。应采取积极的防范措施,通过提高员工的综合素质、建立重大赔案调查制度、实现伤者医疗跟踪服务和实行保险行业信息共享等方式,减少保险骗赔案件的发生。     

A Comparison of State-of-the-Art Classification Techniques for Expert Automobile Insurance Claim Fraud Detection

Several state‐of‐the‐art binary classification techniques are experimentally evaluated in the context of expert automobile insurance claim fraud detection. The predictive power of logistic regression, C4.5 decision tree, k‐nearest neighbor, Bayesian learning multilayer perceptron neural network, least‐squares support vector machine, naive Bayes, and tree‐augmented naive Bayes classification is contrasted. For most of these algorithm types, we report on several operationalizations using alternative hyperparameter or design choices. We compare these in terms of mean percentage correctly classified (PCC) and mean area under the receiver operating characteristic (AUROC) curve using a stratified, blocked, ten‐fold cross‐validation experiment. We also contrast algorithm type performance visually by means of the convex hull of the receiver operating characteristic (ROC) curves associated with the alternative operationalizations per algorithm type. The study is based on a data set of 1,399 personal injury protection claims from 1993 accidents collected by the Automobile Insurers Bureau of Massachusetts. To stay as close to real‐life operating conditions as possible, we consider only predictors that are known relatively early in the life of a claim. Furthermore, based on the qualification of each available claim by both a verbal expert assessment of suspicion of fraud and a ten‐point‐scale expert suspicion score, we can compare classification for different target/class encoding schemes. Finally, we also investigate the added value of systematically collecting nonflag predictors for suspicion of fraud modeling purposes. From the observed results, we may state that: (1) independent of the target encoding scheme and the algorithm type, the inclusion of nonflag predictors allows us to significantly boost predictive performance; (2) for all the evaluated scenarios, the performance difference in terms of mean PCC and mean AUROC between many algorithm type operationalizations turns out to be rather small; visual comparison of the algorithm type ROC curve convex hulls also shows limited difference in performance over the range of operating conditions; (3) relatively simple and efficient techniques such as linear logistic regression and linear kernel least‐squares support vector machine classification show excellent overall predictive capabilities, and (smoothed) naive Bayes also performs well; and (4) the C4.5 decision tree operationalization results are rather disappointing; none of the tree operationalizations are capable of attaining mean AUROC performance in line with the best. Visual inspection of the evaluated scenarios reveals that the C4.5 algorithm type ROC curve convex hull is often dominated in large part by most of the other algorithm type hulls.     

The Role of Repetition and Observability in Deterring Insurance Fraud

In this paper, I analyze an inspection game between an insurer and an infinite sequence of policyholders, who can try to misrepresent relevant information in order to obtain coverage or lower insurance premium. Because claim-auditing is costly for the insurer, ex-post moral hazard problem arises. I find that the repeated game effect serves as a commitment device, allowing the insurer to deter fraud completely (for sufficiently high discount rate) but only when the policyholders observe past auditing strategies. Under weaker observability conditions, only partial efficiency gains are generally possible. I conclude that the insurers should spend resources on signaling their anti-fraud attempts to the potential policyholders. Similar conclusions can be drawn with respect to conceptually similar problems, such as tax evasion.     

基于成本—收益理论的社会医疗保险欺诈问题研究

通过引入成本—收益理论,对社会医疗保险制度中的欺诈问题进行研究,比较该制度中各参与主体的成本、收益构成,分析各影响因子对欺诈与反欺诈行为的影响,研究表明:欺诈与反欺诈行为受行为成本、行为收益大小的制约,且有其相应的约束条件。在此基础上,提出了相应的反欺诈对策。     

Assessing Consumer Fraud Risk in Insurance Claims

Abstract

We present an unsupervised learning method for classifying consumer insurance claims according to their suspiciousness of fraud versus nonfraud. The predictor variables contained within a claim file that are used in this analysis can be binary, ordinal categorical, or continuous variates. They are constructed such that the ordinal position of the response to the predictor variable bears a monotonic relationship with the fraud suspicion of the claim. Thus, although no individual variable is of itself assumed to be determinative of fraud, each of the individual variables gives a “hint” or indication as to the suspiciousness of fraud for the overall claim file. The presented method statistically concatenates the totality of these “hints” to make an overall assessment of the ranking of fraud risk for the claim files without using any a priori fraud-classified or -labeled subset of data. We first present a scoring method for the predictor variables that puts all the variables (whether binary “red flag indicators,” ordinal categorical variables with different categories of possible response values, or continuous variables) onto a common –1 to 1 scale for comparison and further use. This allows us to aggregate variables with disparate numbers of potential values. We next show how to concatenate the individual variables and obtain a measure of variable worth for fraud detection, and then how to obtain an overall holistic claim file suspicion value capable of being used to rank the claim files for determining which claims to pay and the order in which to investigate claims further for fraud. The proposed method provides three useful outputs not usually available with other unsupervised methods: (1) an ordinal measure of overall claim file fraud suspicion level, (2) a measure of the importance of each individual predictor variable in determining the overall suspicion levels of claims, and (3) a classification function capable of being applied to existing claims as well as new incoming claims. The overall claim file score is also available to be correlated with exogenous variables such as claimant demographics or highvolume physician or lawyer involvement. We illustrate that the incorporation of continuous variables in their continuous form helps classification and that the method has internal and external validity via empirical analysis of real data sets. A detailed application to automobile bodily injury fraud detection is presented.     

Deterring Fraud: The Role of General Damage Awards in Automobile Insurance Settlements

Awards for pain and suffering and other noneconomic losses account for over half of all damages awarded under third‐party auto insurance bodily injury settlements. This article hypothesizes that third‐party insurers use general damage awards to reduce the incentive to submit exaggerated claims for specific damages for injuries and lost wages. Consistent with this hypothesis, the article finds evidence using data on over 17,000 closed bodily injury claims that special damage claims that exceed their expected value receive proportionally lower general damage awards than claims that do not. Among the implications of this research is the possibility that insurers will be less zealous in challenging fraudulent special damage claims under a third‐party insurance regime than they will be under a first‐party insurance regime in which access to general damages is limited.     

Can Bonus‐Malus Allieviate Insurance Fraud?

Traditionally, insurance companies attempt to reduce (or even eliminate) fraud via audit strategies under which claims may be investigated at some cost to the insurer, with a penalty imposed upon insureds who are found to report claims fraudulently. However, it is also clear that, in a multiperiod setting, bonus‐malus contracts (increases in subsequent premiums whenever a claim is presented) also provide an incentive against fraud. In this article, we consider a model in which, conditional upon the client renewing his contract, the only mechanism used to combat fraud is bonus‐malus. In this way, our model provides the opposite pole to the pure audit model. We show that in our simplified setting there exists a bonus‐malus contract that will eliminate all fraud in all periods, while guaranteeing nonnegative expected profits to the insurer and participation by the insured. We also consider the dynamics of the solution, the effect of an increase in risk aversion on the solution, and the welfare implications.     

强制保险对机动车险市场的影响

即将实施的《中华人民共和国道路交通安全法》是我国第一部道路交通安全法律,保监会据此制定了《机动车第三者责任强制保险条例》,详细规定了机动车辆第三者强制保险的具体内容,将对商业保险公司的机动车辆产生重大影响。对此,各保险公司应加强制定费率规章,增设绝对免赔额制度和明确对机动车辆超载问题的处理标准。     

各国存款保险体系的制度安排

存款保险体系的制度安排对存款保险体系的成功运作至关重要.正式的存款保险制度,对保险最高限额、筹资安排、行政管理方式、银行处置标准,以及在处理银行破产时政府的责任,都由法律或合约进行了明确的规定.尽管各国的存款保险制度存在很大差异,但越来越出现许多共同的演进趋势.     

社会保险信息系统差异性分析

社会保险管理信息系统是社会保险政策执行和政策效果实现的重要载体.当前我国社会保险管理信息系统存在建设标准不统一、系统差异巨大、数据标准碎片化的客观问题,这不仅在技术层面造成了各地社会保险政策执行的不统一,还在社会保险实践层面给社会保险的异地转移接续和全国统筹带来了巨大障碍.本文从政策、险种、业务环节、管理部门、统筹层次、设计标准、数据库和数据存储位置8个维度,分析了当前中国各地社会保险信息系统差异的主要因素,指出了多种形态交叉混杂下社会保险信息系统差异的复杂程度.而后探讨了社会保险信息系统差异的根源与必然性,探讨了其对社会保险信息化建设、精细化管理、发挥内外部监督力量的影响,并提出三条针对社会保险信息化建设的建议.     

The Impact of the European Union Insurance Directives on Insurance Company Stocks

This article examines the impact of the passage of the Second and Third Life and Non‐Life European Insurance Directives on insurance firms located in 14 European Union countries, Norway, and Switzerland. The third directives have a wealth effect on the European insurance market, while the second directives do not. The Third Life Directive resulted in a wealth increase for the European insurance market, while the Third Non‐Life Directive had a modest negative wealth effect. The wealth effects differ at both the country and firm level. The directives have differential impacts on firms depending on the firms’ characteristics and those of the market they operated in prior to the directives. Regression results indicate that the second directives have impacted firms in protected markets negatively, especially those with higher debt and higher returns on assets. At the time of the third directives, insurance firms benefited, even those in previously protected markets, indicating that firms may have positioned themselves in preparation for the liberalization of the laws.     

商业银行内部人骗贷舞弊行为与反舞弊机制

商业银行中内部人的骗贷舞弊行为给当事方银行、国家以及人民的财产造成了巨大的损失.本文运用企业舞弊理论,并结合我国2002到2006年间的典型案例,对我国商业银行中内部人的骗贷舞弊行为进行了研究,最后提出了一个系统化的反舞弊机制:(1)确定和宣传正确的管理思想和企业文化;(2)监督和约束高层管理人员;(3)强化内部控制的执行力;(4)建立独立的审计委员会.     

The Impact of No-Fault Legislation on Automobile Insurance

Abstract

Since its inception, the effectiveness of no-fault legislation has been highly debated. Although some research suggests that no-fault laws are effective in reducing costs, other evidence suggests that the current no-fault systems may not meet the original objectives. This study provides a detailed assessment of the relation of no-fault laws and automobile insurance losses for the period 1994 to 2007. By examining total automobile insurance losses along with liability and personal injury protection losses, we are able to determine if and how specific provisions of the laws are related to claims costs. We find a negative relation between the presence of a no-fault law and total losses, which suggests that no-fault systems are associated with lower losses than the traditional tort system. In addition, an examination of no-fault-only states suggests that specific provisions of no-fault laws, such as thresholds and limitations on benefits, have some effect on losses. With the sunset of Colorado’s no-fault legislation in 2003, the recent passage of Personal Injury Protection Reform in Florida, and proposed federal choice legislation, the overall impact of no-fault as well as the specific components of the laws are of heightened importance to consumers, insurers, and lawmakers.     

Insurance Fraud: What makes a case look suspicious?

By many, insurance fraud is believed to be widespread, but little is known about how to detect it. In recent years, some attempts have been made to find indicators for fraud. They are, however, probably hampered when relying on characteristics of established fraud, since the majority of fraudulent cases then remains excluded, leaving many white spots on the map. In choosing a different approach, we let subjects reason freely about insurance fraud, recording and analysing their clues, and comparing them to indicators found in previous research. Our findings show that not only much of available information is largely ignored, subjects tend to concentrate on other aspects than supposedly reliable fraud characteristics and experts fail to fare better than laypeople.