Insurance Fraud - Case Study Example

Insurance Fraud Students Name University Affiliation Table of contents Table of contents 2 Introduction 3 Spotting potential fraud and fraudsters 5 Research Methodology 7 Technological issues and observations 7 Conclusion and recommendation 9 References 11 Insurance Fraud Introduction Fraud in the insurance industry has constantly been an enigma to the stakeholders. Today, the insurance industry faces extensive fraudulent cases that are siphoning billions from the very lucrative insurance business. Based on this, there has been numerous studies based on the subject of fraud that have clearly shown the failure points of the customary methods that have been used over the years to detect and contain fraud. Most of the studies done in the past have focused a lot of attention on the identification of fraudulent claims and transactions failing to take notice of the very culprits engineering and driving the fraud cases . It is the realization of this that brought about the alternative structure of understanding the current insurance practices, the changes in the fraudsters strategies, and the most common areas hit out on that not only provide an avenue for fraudsters, but also exposes the industry to a huge risk. In other words, alternatives in tackling fraud cases is shifting focus from individual cases to looking at a broader perspective and painting a true picture of fraud in the industry as a whole. This calls for the application of technology and focusing on fraudsters rather that fraud as a single instance in a firm . This research, therefore, focuses on understanding fraud in the insurance industry from a basic level. In essence, this paper unveils the reasons why fraud is on an all-time high in the insurance industry, factors contributing to fraud in the industry, and the various structures put in place by the industry to curb this vice. To achieve this, first focus will be on fraudsters and how the subject of fraud is approached from a criminal perspective. Firstly, fraudsters can be classified into three distinct categories based on the level of experience and aftermath of the attack. The first category is of opportunities that normally have genuine insurance claim cases with which they use to exaggerate and claim for more than is deserved for such a case. The second category is of the amateur fraudsters that take advantage of a genuine claim but take it further, perhaps by repeating the claim over and over thereby defrauding a firm with a reasonable sum. However these two categories are not as serious as the third and final category which is of the professional fraudsters. These can be taken to do swindling for a living, and as such have a lot of tricks up their sleeves and tend to exploit several loopholes in the insurance industry. Normally, professional fraudsters work as a network of as individuals and they engage in a systematic and persistent pattern to commit insurance fraud. Secondly, attention is shifted to understand why the insurance industry is a constant focus of fraudulent activities. Research clearly pointed to the fact that the existence of numerous loopholes present in the fraud investigation procedures, and a general dislike e of the insurance sector to be the main contributing factors of such cases . These are further heightened by the fact that generally, differentiating genuine claimants from fraudsters more often than not is a very difficult and tedious procedure. For this reason, most insurance forms are either not willing to go through the entire process of lack sufficient resources to undertake takes a full investigation procedure. Additionally, under normal circumstances, even after identifying a fraudulent claim it is increasingly difficult to isolate the individuals as identities are normally, hidden fake or mixed up. In essence, to curb fraud cases in the insurance industry calls for more than just procedures. It calls for a systematic application of regulation, corporation of relevant industry players, and the application of technology to ensure a full proof system is laid out. Spotting potential fraud and fraudsters Setting all these obstacles aside, fraudulent cases in the industry can indeed be detected and rooted out when proper mechanisms are put in place. Fraudulent claims more often than not follow detectable patterns that cause anomalies in the process and are detectable with an experienced eye or system. Basically, this means that the introduction of a stringent claiming procedures can be used as the first line of defense when dealing with fraud cases . These claim procedures can be used to root out the obvious anomalies that suggest a fraud claim. It is at this juncture that insurance investigators come in handy as their experience and skills enable that isolate a good percentage of inappropriate cases and anomalies in case files. After this, each file can then be probed further on an individual basis to ascertain the validity of the claimant and the claim case. In addition to this, firms have also taken the initiatives to incorporate technology into the investigation and claims procedures. Such measures go a long way into investigating the trueness of every claim and have reduced fraudulent cases by a huge margin in the recent past. These strategies bring together the industry players in terms of the insurance firms, regulatory commissions, investigators, and the governing bodies in one collective database and assist in fighting fraud cases as a single unit . This is beneficial l as detection can be done once ad isolation of cases is easier through identification of given behavior patterns. Similarly, repeat cases can be identified, and the issuer of resources is well handled by the collective effort to fight the vice. Such measures have been implemented in the industry with the sole objective of spotting fraudulent cases and identifying fraudsters in the industry in a bit to regulate and curb such claims. This is because, compared to the traditional ways of fighting fraud tin the industry, this method has proved to be effective in rooting out the problem in a blanket sweep. Firstly, it provides a platform for collecting and verifying claimant’s information during the investigation process. Secondly, it allows for investigators and firms to verify the frequency of the claimant making such claims and their consistencies. Finally, the database provides a central repository for all insurance firms to share and store information allowing them to verify even the false identities of claimants . Similarly, techniques have been borrowed on proven techniques of criminal investigations and new technologies and have been incorporated into the insurance fraud investigation to help expose false claimants. These include technologies such as voice stress analysis that have been proven to give accurate and reliable results. Such methods are usually applied after the identification of falsified claim document and as such can be used as the second line of defense in the identification and prevention procedures of insurance fraud. On the same subject, other technologies also exist within the industry that can be incorporated at various levels to assist in fighting fraud. However, such methods are widely untested and accurate results on their performance rate are not documented for purposes of referencing. Additionally, a lot of concern is brought about where the incorporation of a fully technology environment this is because these systems are mostly developed by engineers who have little or no knowledge of the insurance systems and the dynamics of operation. Essentially, these systems may focus so much into spotting these fraud instances and leaves out a crucial aspect which is the user and industry player who deals with these cases and systems on a daily basis . For a perfect of near similar results to be realized, it is widely documented that these two have to be in harmony and as such the utilization of newer technologies of fully automated fraud detection systems may be a while before they are a norm in the insurance industry. In other words, when it comes to detecting and uprooting fraud in the insurance industry key thing is to be noted are the daily operations, emerging patterns and the industry dynamics, other than the normal technological and investigation procedures. Research Methodology In garnering up the required data for this research, an ethnographic approach has been applied so as to ensure the results are based on an accurate as possible research. Techniques such as observation, hands on practical experience, and interviewing have been extensively applied through tout the research to develop a step by step procedure and understanding of the insurance practices, and instances of both detectable and hard to detect fraud cases. Similarly, the data has been taken through a rigorous analysis process in order to fully understand the fraud exposure techniques and how best to tackle the loopholes previously exposed by the system. Ethnography as a technique has long term and an intensive nature that paves way for a better understanding of processes and procedures as done by people. Unlike other techniques, ethnography does not simply put across the most obvious thoughts of the interviewees, but rather portrays the actual situation as is handled on the ground. The methodology applied on this research, therefore, applies a variety of techniques and technologies and as such gives a detailed account of the proceeding on the insurance industry. Technological issues and observations As afore mentioned, fraud detection, investigation, and isolation of individual cases heavily relies of appropriate technology with a combination of human efforts. This is because; response to fraudulent claims depends on the accuracy of the data and timeliness of identifying and reporting such cases. Essentially, anomalies need to be detected early enough in the chain of procedures and the investigations have to carried out with near precision if the culprits are to be caught. Additionally, just a mere application of the system and technologies without human effort will results to poor performance as detections may go unnoticed . Discrepancies can occur practically anywhere in the systems and this calls for a lot of keenness especially when handling the voluminous combined databases. Based on the ethnographic studies, a detailed understanding of the performance of technology in most of the insurance firms is presented. In addition to applicable technology, other factors such as customer service standards, proactivity of employees and investigators, efficiency of laid out procedures, and regular audits appeared to affect the identification and isolation procedures. These factors determine the performance of individual firms and the effective identification of fraudulent cases. The reason t this is because they are all involved in the core processes of the insurance industry. The combination of such factors, technology and appropriate insurance procedures is what produces a system that limits on fraud instances in the industry. On a similar note, the most obvious loopholes created by technology seemed to be the use of outdated and pirated software’s that came with a number of errors that overlooked obvious fraudulent claims. Similarly, some of the observations noted during the study allude to the fact that development of new and emerging technologies also play a role in the rising cases of fraudulent claims and it =s fight as well. This is due to their highly spontaneous nature and depending on which side of the “divide” uses such technologies. A definite implication is bound to be noted. This further compound the fact that these technologies need to be tested and deployed in the field to help reduce the fraud claims. However, it has been noted severally that such emerging technologies are effective only on instances where data is digitalized . On the instances where physical paper forms are prevalent it is highly unlikely that the systems would be of any help where fraud detection are concerned. Additionally, the combination of physical forma and a redundant system would only seek to increase the loopholes for fraud while at the same time waste resources in terms of human capital and computers. Finally, none of the insurance firms observed at the time of the study seemed to undertake a fully forensic investigation on the isolated cases. This presents a challenge in that case identifies either through inconsistencies or anomalies by the system require further investigation to go to the root of the problem and even get the fraudsters. In other words, by conducting partial investigations most firms are simply identifying possible fraud cases but are not going a step further to completely root out the problem at hand . However, having said that, the firms that went to the extent of using data mining techniques seemed to fully understand the working of fully functional and automated systems thereby ensuring the entire process is carried to completion. Where further developments to the insurance fraud detection is concerned, a sudden change of the current practices appear far-fetched and difficult to realize due to the fact that the database technology combines a number of sectors and firms onto a shared platform. The collective effort of providing staff and allocation of relevant duties would take a lot more to enact and fully implement. Conclusion and recommendation In conclusion, his research presents fraud in the insurance industry from two different perspectives. First is the old system where firms concentrated of personal portfolios and individual cases. This was a more manual system and left a number of gaping holes that have been exploited by fraudsters time and time again. Secondly, the newer perspective of combined efforts by all industry players is presented as an ideal solution to not only detects fraud cases but also to manage their emergence and finally eliminate them. This is of course with the support of technology and a number of new procedures that would ensure a full proof system is applicable across the board. This in turn would help insurance firms improve their fraud detection capabilities and save on the billions loosed annually by the industry through fraud. 1. The recommendations, therefore, placed forward to achieve such aims are: 2. Enacting workable solutions that would be agreeable with all stake holders and would ensure smooth flow of activities in the industry 3. Apply standard software usable across the board by all firms to ensure consistency of information flow 4. Provide a channel for offering feedback on the progress on individual investigations and cases that would assist in identifying the culprits once and the records to be shared among member firms and stakeholders References Fraud, C. A. I. (2009). Go Figure: fraud data: Retrieved July. Lesch, W. C., & Byars, B. (2008). Consumer insurance fraud in the US property-casualty industry. Journal of Financial Crime, 15(4), 411-431. Miyazaki, A. D. (2009). Perceived ethicality of insurance claim fraud: do higher deductibles lead to lower ethical standards? Journal of Business Ethics, 87(4), 589-598. Phua, C., Lee, V., Smith, K., & Gayler, R. (2010). A comprehensive survey of data mining-based fraud detection research. arXiv preprint arXiv:1009.6119. Šubelj, L., Furlan, Š., & Bajec, M. (2011). An expert system for detecting automobile insurance fraud using social network analysis. Expert Systems with Applications, 38(1), 1039-1052. Tennyson, S. (2008). Moral, social, and economic dimensions of insurance claims fraud. Social Research: An International Quarterly, 75(4), 1181-1204.  Read More