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Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: . Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.
SAS 99 defines fraud as an intentional act that results in a material misstatement in financial statements. There are two types of fraud considered: misstatements arising from fraudulent financial reporting (e.g. falsification of accounting records) and misstatements arising from misappropriation of assets (e.g. theft of assets or fraudulent expenditures).
Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...
It is widely used in the financial sector, especially by accounting firms, to help detect fraud. In 2022, PricewaterhouseCoopers reported that fraud has impacted 46% of all businesses in the world. [1] The shift from working in person to working from home has brought increased access to data.
Health care fraud includes "snake oil" marketing, health insurance fraud, drug fraud, and medical fraud. Health insurance fraud occurs when a company or an individual defrauds an insurer or government health care program, such as Medicare (United States) or equivalent State programs. The manner in which this is done varies, and persons engaging ...
Forensic data analysis (FDA) is a branch of digital forensics. It examines structured data with regard to incidents of financial crime. The aim is to discover and analyse patterns of fraudulent activities. Data from application systems or from their underlying databases is referred to as structured data.
Data auditing is the process of conducting a data audit to assess how company's data is fit for given purpose. This involves profiling the data and assessing the impact of poor quality data on the organization's performance and profits.
An IT audit is different from a financial statement audit.While a financial audit's purpose is to evaluate whether the financial statements present fairly, in all material respects, an entity's financial position, results of operations, and cash flows in conformity to standard accounting practices, the purposes of an IT audit is to evaluate the system's internal control design and effectiveness.