1.1 Introduction
Fraud is the deliberate deception practiced with a view to gaining an unlawful or unfair advantage. The effectiveness of any banking system depends on how secured the system is. The crave for information technology globally has greatly had an influence in our banking sectors. Thus a fest and quick development has erupted in many countries of the world in terms of automation advancement and technology. Such advancement includes the design and implementation of an automated fraud detection system which is witnessed in our various insurance sectors worldwide. In as much as financial sector is concerned, there should be possible ways made to avoid fraudulent from gaining access to the banking and all other insurance sectors. By the introduction of an automated computer base security system, it will aid to eliminate totally the idea and practice of fraud in banking industries.
As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Limitations of the Study and Definition of technical terms.
1.2 Background of Study
Fraud is committed in various fields such as insurance (Ormerod et al. 2010; Li et al. 2008; Atwood et al. 2006), credit card (Weston et al. 2008; Dal Pozzolo et al. 2014), telecommunications (Estevez, 2006), and financial communications (Kirkos et al. 2007; Kotsiantis et al. 2006; Holton, 2009). Insurance fraud is one of the most frequent types of fraud to undertake. This type of fraud can take place in many forms with the simple objective of gaining money (Almedia, 2009). One of these domains is car insurance in which fraudsters (policyholders) setting planned traffic accidents up and file fake insurance claims (e.g. inflating costs) to obtain an illicit benefit from their insurance policy (Ayuso et al. 2011). It has been reported that Almost 21% to 36% of auto-insurance claims contain elements of suspected fraud but only less than 3% of them are prosecuted (Nian et al. 2016).
There are two different types of fraud, including opportunistic, and professional fraud that the second type is committed by organized groups. Although the organized fraud is perpetrated fewer than the opportunistic insurance fraud, the majority of revenue outflow (financial losses) is due to these groups (a White paper, 2012). According to Bolton and Han (2002), fraud detection would be difficult due to many reasons. The first one is, involving high volume of data, which are constantly evolving. In reality, for processing these sets of data, the fast, the novel, and efficient algorithms are entailed. Moreover, in terms of cost, it is evident that undertaking a detailed analysis of all records is too much expensive. Here the issues of effectiveness enter; indeed, many legitimate records exist for every person that an effective method should detect fraudulent records correctly.
Traditional systems for fraud detection are only able to find fraudulent customers (opportunistic fraud), whereas more professional fraudsters will be overlooked (a white paper, Roberts, 2010). In other words, opportunistic fraud is a continuous issue for insurers, whereas the more remarkable challenge comes from professional fraud, and such organized groups of perpetrators impose the greatest cost upon insurers. Fraudulent groups are being arranged by fraudsters in order to employ different individuals for doing some works, and using the newest technologies to be at least one step in front of insurers. They know properly that insurers and law enforcements officials utilize what kind of tools, and information (Smallwood and Breading, 2011). Due to aforementioned reasons, it is imperative for insurance companies to consider relevant methods for finding organized fraud groups, and promulgating them in the future.
1.3 Statement of Problem
Investigation revealed that the detection of insurance fraud has been seriously taken into account in recent years. Although this issue is seen more in practical and functional fields, it is considered in terms of the academic aspects due to its negative effect on insurance pricing and on efficiency of insurance industry. Despite the extensive utilization of data mining algorithms for sorting fraud out, according to (Phua et al. 2005), there are some complexities with regard to nature of data mining techniques that illustrate they might be inefficient in flagging fraudulent activities in future; firstly, a volume of data will fluctuate over time (doubtless that the volume of data will have boomed by near future).
Secondly, the forms and styles of fraud are changing regularly. The third criticism is regarding introducing new patterns of suspicious activities during the near future like professional fraud that will have been generated. In the last decade, social networks play a prominent role in researches on detecting and deterring fraud in various areas such as credit card, Social online, financial trade, Internet Auction, health insurance, etc. (Eberle et al. 2010; Bindu and Thilagam, 2016; Yu et al. 2015; Chau et al. 2006; Akoglu et al. 2013; Chiu et al. 2014; Vlasselaer et al. 2015; Flynn, 2016). It is to this regard that the study desired to design and implement a fraud detection system in computerized insurance firm.
1.4 Aim and Objective of the Study
The aim of the study is to Design and Implement a Fraud Detection System in Computerized Insurance Firm to prevent fraud. In achieving this aim, the following specific objectives were laid out as follows to develop an application software that will:
- Aid in monitoring and controlling of fraudulent activities in an insurance firm.
- Detect fraud and identify the types of fraud in an insurance firm.
- Show the effect in the manpower of the security department because on most occasions charging the manual information system to an automated information system will equally cause redundancy.
1.5 Significance of Study
The study on design and implementation of fraud detection system in computerized insurance firm will be of immense benefit to the entire insurance firms in Nigeria and the computer science department in the sense that the study will educate the above subjects on the types of fraud in the insurance firms in Nigeria. The study will educate them how to design a fraud detection system. The study will also serve as a repository of information to other researchers that desire to carry out similar research on the above topic and to contribute to the body of the existing literature.
1.6 Scope of the Study
The study on design and implementation of fraud detection system will focus on computerized insurance firms in Nigeria and also provides will developed software to automate the new system.
1.7 Limitations of the Study
During the course of this study, many things militated against its completion, some of which are:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Establishment Policies: Establishment policies posed a serious limitation as most staffs are not ready to release information needed for this project work. There were lots of information needed from the staffs of this institution to enhance the study which took them time to release or they did not release at all for security purposes, hence the scope was reduced.
- Research material: availability of research material is a major setback to the scope of the study.
- Frequent power failure: This made the researcher append more money on fuel to ensure sustainable power.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet).
1.8 Definition of Terms
Fraud: Is defined as deception deliberately practiced with a view of gaining an unlawful or unfair advantage.
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