# Financial Fraud Detection Based on Machine Learning: A Systematic Literature Review
## 3 Search Results and Meta-Analysis
### Synthesis Results  
This section presents the results of the data synthesis to address the research questions based on the selected papers. Thus, in this section, the research questions designed for the SLR will be answered. 2.1 RQ1: What Are the Different Categories of Fraudulent Activities That Are Addressed Using ML Techniques  
Fraudulent activities vary depending on industry sectors [1; 4; 27]. This section attempts to answer RQ1 by presenting different fraudulent activities that were addressed using ML techniques based on the selected articles. Based on the reviewed articles, fraudulent activities in the financial sector can be broadly categorized into credit card, mortgage, financial statement, and health care fraud. This can be further explained in the following subsections. Figure 3: Number of articles per journal. Figure 2: Summary of articles in a year. Credits are typically used to refer to electronic financial transactions made without the use of physical cash [28]. A credit card that is extensively used for online transactions is a small piece made up of thin plastic material with credit services and customer details [28; 29; 30]. Fraudsters use credit cards to make unlawful transactions that result in massive losses to banks and card holders [31]. Moreover, the invention of counterfeit cards has aided fraudsters in performing illicit transactions more easily. In general, it is regarded as illegitimate to use the card without the proper owners' authorization. By obtaining access to a certain account illegitimately, any transaction that is carried out is considered as fraudulent [29; 30]. Credit card fraudulent activities can be divided into two aspects, namely, offline and online fraud [29]. In offline fraudulent activity, the fraudsters conduct their illicit transactions with stolen credit cards such as genuine card holders, while online fraudsters conduct their activities in online transactions through Internet Online fraud [29; 30]. Fraud in financial statements involves forging financial reports to claim that a company is more profitable than usual [3], avoid the payment of taxes, increasing stock prices, or obtaining a bank loan [32]. It can also be regarded as the confidential records generated by organizations that contain their financial records that comprise their expenses, profits made, income loans, etc. [33; 34]. These statements also comprise some write-ups made by management for discussing business performances and predicted future tendencies [35; 36; 37]. Different financial records provide the financial reality of the organization, which indicates how successful the organization is and assists in checking if the organization is bankable [33; 34]. In addition, financial statement fraudsters deceive the users of financial statements by correcting misstatements to make the organizations appear beneficial. The main purpose of the financial fraudulent statements is to enhance share prices, minimize tax liabilities, attract more investors as much as possible, and access personal bank loans among others [15]. Insurance fraud can be defined as the act of misusing an insurance policy for gaining illegitimate benefits from an insurance business [38]. Usually, insurance is made to protect the organization's transactions or individual's transactions against any financial risks [33; 34]. The main sectors of target by fraudulent insurance claims include healthcare [5; 39; 40] and automobile insurance companies [41; 42]; although home and crop insurance fraudulent also occur [1], however, there is a paucity of the literature on both [16; 43]. It has been estimated recently that the total cost of insurance fraud in the United States is over a billion USD yearly and it is finally passed on to consumers in the form of higher insurance premiums [11]. In order to cover the relevant costs of theft or accidental damages to a car, an agreement between the insurance provider and the insured person or organization is typically involved in automobile insurance claims [44; 42].