Erklärungsansätze für vertragswidriges Verhalten Versicherungsnehmern aus Sicht der ökonomischen Theorie

The two main purposes of this paper are an introduction to the economic analysis of insurance fraud and furthermore a derivation of factors that determine fraudulent behavior of policyholders on insurance markets. Consequently, we analyze the strategic decision problems of insurance companies and the policyholders and identify some factors that can help to reduce fraudulent behavior. In this context we evaluate two derived starting points for the combat against insurance fraud: fraud detection systems and a consequent charge policy of detected defrauders. We illustrate that both points can help to reduce the cost of fraud. Furthermore, we enhance our earlier analysis with respect to the empirical fact that some individuals care about fairness or — in the insurance fraud context — the legitimacy of their actions. Surprisingly, in some market situations these concerns of some policyholders do not lead to a lower fraud probability. Finally, we discuss how and to what extent insurance companies can influence such ethical concerns of policyholders. On that score, we distinguish insurance specific and insurance unspecific factors and their impact on the consumers attitudes towards insurance fraud.     

The Impact of Insurance Fraud Detection Systems

This article analyzes the impact of detection systems in an insurance fraud context. In a noncommitment Costly State Verification setting insurers can only detect fraudulent claims by performing costly audits, and policyholders are overcompensated by the optimal insurance contract. We show that auditing becomes more effective and overcompensation can be reduced, when insurers are able to condition their audits on the information provided by detection systems.     

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.     

Insurance Markets With Differential Information

This article attempts to understand the outcomes when each party of an insurance contract simultaneously has superior information. I assume that policyholders have superior information about specific risks while insurers have superior information about general risks. I find that low-general-risk policyholders purchase insurance, while high-general-risk policyholders are self-insured. Among the low-general-risk policyholders, high-specific-risk policyholders purchase full insurance, while low-specific-risk policyholders purchase partial insurance. When insurers can strategically publicize their information, efficiency is improved because high-general-risk policyholders purchase actuarially fair insurance. The market segmentation is also found based on the general-risk type and the publicizing of information.     

Providers’ affiliation,insurance and collusion

This paper provides a theoretical analysis of the benefits for an insurance company to develop its own network of service providers when insurance fraud is characterized by collusion between policyholders and providers. In a static framework without collusion, exclusive affiliation of providers allows insurance companies to recover some market power and to lessen competition on the insurance market. This entails a decrease in the insured’s welfare. However, exclusive affiliation of providers may entail a positive effect on customers’ surplus when insurers and providers are engaged in a repeated relationship. In particular, while insurers must cooperate to retaliate against a fraudulent provider under non-exclusive affiliation, no cooperation is needed under exclusive affiliation. In that case, an insurer is indeed able to reduce the profit of a malevolent provider by moving to collusion-proof contracts when collusion is detected, and this threat may act as a deterrent for fraudulent activities. This possibility may supplement an inefficient judicial system: it is thus a second-best optimal anti-fraud policy.     

Fraud Classification Using Principal Component Analysis of RIDITs

This article introduces to the statistical and insurance literature a mathematical technique for an a priori classification of objects when no training sample exists for which the exact correct group membership is known. The article also provides an example of the empirical application of the methodology to fraud detection for bodily injury claims in automobile insurance. With this technique, principal component analysis of RIDIT scores (PRIDIT), an insurance fraud detector can reduce uncertainty and increase the chances of targeting the appropriate claims so that an organization will be more likely to allocate investigative resources efficiently to uncover insurance fraud. In addition, other (exogenous) empirical models can be validated relative to the PRIDIT‐derived weights for optimal ranking of fraud/nonfraud claims and/or profiling. The technique at once gives measures of the individual fraud indicator variables’ worth and a measure of individual claim file suspicion level for the entire claim file that can be used to cogently direct further fraud investigation resources. Moreover, the technique does so at a lower cost than utilizing human insurance investigators, or insurance adjusters, but with similar outcomes. More generally, this technique is applicable to other commonly encountered managerial settings in which a large number of assignment decisions are made subjectively based on ‘‘clues,‘’ which may change dramatically over time. This article explores the application of these techniques to injury insurance claims for automobile bodily injury in detail.     

保险公司偿付能力风险信息对称性与市场供求

保险公司偿付能力充足性是保险监管的内容之一,但是这一信息却往往不被投保人所获知,造成保险供给(保险公司)和保险需求(投保人)两方信息的不对称.本文以保险公司存在偿付能力风险为基本假定,以累积性预期理论和风险调整资本收益率构建保险需求和供给模型,分析在信息对称条件下和信息不对称条件下保险需求的变化及其对保险供给和保险公司...     

Aufdeckung von Versicherungsbetrug bei Kfz-Schäden mit Hilfe des Benford-Tests

The German Insurance Association estimates a yearly amount of damage of € 1.5?bn to German motor vehicle insurance companies because of systematic fraud by insurance holders. It is supposed that about 10% of submitted claim applications contain manipulated data, therefore insurance companies are forced to complete a detailed and cost intensive case-by-case review of each single application. An alternative method to detect fraud in empiric data is the method of digital analysis based on Benford’s law. The Benford method uses a mathematical law of specific logarithmic distribution attributes of first digits. According to this approach, the data of a Benford set confirm with the expected digit distribution, if the data is not manipulated, whereas fraudulent interventions lead to a deviation from Benford’s law. Hence, until now there has not been any investigation whether the Benford method can also be applied on insurance data. The present article analyses a dataset consisting of more than 120,000 damage claim applications to answer this question as well as to identify the impact of specific characteristics on the probability of fraud contained in claim applications, such as the repair of the vehicle in a franchised or an independent workshop, the vehicle brand or the examination by insurance companies experts. Indeed it could be shown that Benford’s Law is only applicable on second digits of insurance data, but delivers very strong results here: All results of the considered characteristics could be verified by plausible arguments. For this reason insurance companies can benefit from making use of the Benford method to identify those claim applications with a high probability of fraud, which should then be reviewed in more detail so that resources can be allocated in a much more cost efficient way.     

Resistance (to Fraud) Is Futile

This article studies a static principal–agent model of insurance fraud using a costly state verification approach. In an economy where there are two types of agents, the Truths, who always report the true state of the world, and the Dares, who dare misreport the true state of the world, I show that no separating contract exists. Furthermore, if the proportion of Dares is large enough, then the pooling contract, the amount of fraud and the number of agents found to have committed fraud are independent of the Dares' exact proportion in the economy. Finally, I show that investment in prevention can be useless if the proportion of Dares is large enough, which means that investing in prevention becomes a waste of resources. This last result holds when the proportion of Dares is large. When their proportion is small, investing in prevention reduces fraud.     

Outlier detection in healthcare fraud: A case study in the Medicaid dental domain

Health care insurance fraud is a pressing problem, causing substantial and increasing costs in medical insurance programs. Due to large amounts of claims submitted, estimated at 5 billion per day, review of individual claims or providers is a difficult task. This encourages the employment of automated pre-payment controls and better post-payment decision support tools to enable subject matter expert analysis. This paper presents how to apply unsupervised outlier techniques at post-payment stage to detect fraudulent patterns of received insurance claims. A special emphasis in this paper is put on the system architecture, the metrics designed for outlier detection and the flagging of suspicious providers which may support the fraud experts in evaluating providers and reveal fraud. The algorithms were tested on Medicaid data encompassing 650,000 health-care claims and 369 dentists of one state. Two health care fraud experts evaluated flagged cases and concluded that 12 of the top 17 providers (71%) submitted suspicious claim patterns and should be referred to officials for further investigation. The remaining 5 providers (29%) could be considered mis-classifications as their patterns could be explained by special characteristics of the provider. Selecting top flagged providers is demonstrated to be a valuable as an targeting method, and individual provider analysis revealed some cases of potential fraud. The study concludes that, through outlier detection, new patterns of potential fraud can be identified and possibly utilized in future automated detection mechanisms.     

Insurance guaranty fund—what good is it?

In this paper, we analyze under which conditions a self-supporting insurance guaranty fund can be beneficial for the policyholders in an incomplete market. Within the analyzed setting, we find out that in general, if existent, the potential advantages from its introduction cannot be fairly divided among the participating insurers. Thereby, we have to expect systematic wealth transfers between the policyholders of different insurance companies. We introduce a framework for utility-based fund charges as a solution to this problem.     

Under What Conditions Is an Insurance Guaranty Fund Beneficial for Policyholders?

In this article, we derive conditions in an imperfect market setting, under which the introduction of a self‐supporting insurance guaranty fund improves the position of the policyholders. When a guaranty fund is advantageous given homogeneous firms in the market, all policyholders benefit from it to the same extent, if they have the same underlying risk preferences and are charged identical premiums. In a more realistic heterogeneous setting, the introduction of an insurance guaranty fund is in general no longer beneficial for all policyholders in the same manner. Hence, systematic wealth transfers take place between the policyholders of different insurance companies. As a possible solution, and in order to counteract this effect, we introduce a framework for utility‐based fund charges.     

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.     

Consumer risk perceptions and information in insurance markets with adverse selection

Standard models of adverse selection in insurance markets assume policyholders know their loss distributions. This study examines the nature of equilibrium and the equilibrium value of information in competitive insurance markets where consumers lack complete information regarding their loss probabilities. We show that additional private information is privately and socially valuable. When the equilibrium policies separate types, policyholders can deduce the underlying probabilities from the contracts, so it is information on risk type, rather than loss probability per se, that is valuable. We show that the equilibrium is “as if” policyholders were endowed with complete knowledge if, and only if, information is noiseless and costless. If information is noisy, the equilibrium depends on policyholders' prior beliefs and the amount of noise in the information they acquire.     

保险治理与公司违规——董事高管责任保险的治理效应研究

公司治理机制被认为是影响公司违规的重要因素,然而董事高管责任保险作为一种重要的外部治理机制,是否会影响公司违规尚未得到充分研究。本文研究发现董事高管责任保险显著降低公司违规概率,符合监督效应假说。经工具变量法、Heckman两阶段模型和倾向得分匹配法稳健性检验,上述结论依然成立。影响机制分析表明,董事高管责任保险显著降低了公司违规倾向,显著增加了违规后被稽查的概率,并降低了上市公司的第一类代理成本。对董事高管责任保险的监督职能做进一步分析发现:(1)董事高管责任保险对上市公司经营违规和领导人违规的监督效应更为显著,但对信息披露违规的治理作用并不显著;(2)董事高管责任保险发挥的监督职能与股权属性和保险机构股东治理存在替代效应,与外部审计师治理和董事长CEO二职分离存在互补效应;(3)分组检验结果表明,董事高管责任保险对公司违规的监督效应在外部监管环境较差或者公司内部信息透明度较高的情况下更加显著。本文既提供了保险合约通过公司治理渠道影响公司违规的证据,同时也表明保险机构通过董事高管责任保险为中国资本市场提供了一种较为有效的公司外部治理机制。     

A performance analysis of participating life insurance contracts

Traditional life insurance products, in particular participating life insurance contracts, are often criticized. Their performance is often said to be poor compared to other investment alternatives. Interestingly, this perception appears to persist although very little research has been conducted into the performance of participating life insurance contracts. But are participating life insurance contracts actually bad for policyholders? We conduct a performance analysis based on contracts offered in the German market, in order to provide evidence to support decision making by policyholders.     

Understanding Basis Risk in Insurance Contracts

There is a tremendous amount of resources being tied up in litigation between insurance companies and policyholders over things like the extent of coverage for various loss scenarios or allegedly bad faith delays in settlement payments. The fact that policyholders formally dispute insurer coverage positions or claims payment strategies gives credibility to the idea that mismatches exist between what policyholders expect insurance policies to cover and what the insurance contracts actually provide as loss indemnification. This mismatch essentially represents insurance basis risk, the analysis of which can more accurately reflect the value and overall efficiency of insurance contracts and suggest factors that may influence policyholder dissatisfaction and consequently insurance contract disputes. This article takes a detailed look at insurance basis risk and finds that subjectivity plays a prominent role in its definition. Using Bayesian inference, it is shown how factors can affect the magnitude of insurance basis risk depending on the individual situation in which the mismatch between losses and coverage exists.     

Detecting insurance fraud using supervised and unsupervised machine learning

Fraud is a significant issue for insurance companies, generating much interest in machine learning solutions. Although supervised learning for insurance fraud detection has long been a research focus, unsupervised learning has rarely been studied in this context, and there remains insufficient evidence to guide the choice between these branches of machine learning for insurance fraud detection. Accordingly, this study evaluates supervised and unsupervised learning using proprietary insurance claim data. Furthermore, we conduct a field experiment in cooperation with an insurance company to investigate the performance of each approach in terms of identifying new fraudulent claims. We derive several important findings. Unsupervised learning, especially isolation forests, can successfully detect insurance fraud. Supervised learning also performs strongly, despite few labeled fraud cases. Interestingly, unsupervised and supervised learning detect new fraudulent claims based on different input information. Therefore, for implementation, we suggest understanding supervised and unsupervised methods as complements rather than substitutes.     

Insurance in a Market for Credence Goods

We study the impact of variations in the degree of insurance on the amount of fraud in a physician‐patient relationship. In a market for credence goods, where prices are regulated by an authority, physicians act as experts. Due to their informational advantage, physicians have an incentive to cheat by pretending to perform inappropriately high treatment levels leading to overcharging patients. Our approach aims on the impact on changes in each, patients' and physicians' incentive structure when the proportional degree of coinsurance varies. It is shown that a higher coinsurance rate may lead to either less fraud in the market and a lower probability of patients searching for second opinions or more fraud and more searches.     

基于利益相关者理论的投保人与保险人的博弈分析

目前我国不少保险公司把企业的短期边际利润作为唯一经营目标,保险人与投保人的利益冲突问题不容忽视。由博弈结果分析可知,投保人作为保险企业的利益相关者,其利益的保护和保险企业的长期发展息息相关。如果投保人利益长期得不到有效的保障,投保人会选择退出保险市场,这将影响到保险业的市场占有率、信誉和形象等等,给保险业的长期健康发展带来威胁。