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  2. Data analysis for fraud detection - Wikipedia

    en.wikipedia.org/wiki/Data_analysis_for_fraud...

    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.

  3. Statement on Auditing Standards No. 99: Consideration of Fraud

    en.wikipedia.org/wiki/Statement_on_Auditing...

    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).

  4. Forensic accountant - Wikipedia

    en.wikipedia.org/wiki/Forensic_accountant

    Forensic accountants need to have a great deal of access to information regarding the company they are investigating or assisting. The information will determine how much a person actually makes, the worth of a business, if there has been fraudulent activity, who committed the fraud, everyone involved, how much was taken from the company, where the money went, and how much can be recovered.

  5. Health care analytics - Wikipedia

    en.wikipedia.org/wiki/Health_care_analytics

    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 ...

  6. Artificial intelligence in fraud detection - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    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.

  7. Forensic data analysis - Wikipedia

    en.wikipedia.org/wiki/Forensic_data_analysis

    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.

  8. Alcohol Use Disorders Identification Test - Wikipedia

    en.wikipedia.org/wiki/Alcohol_Use_Disorders...

    The Alcohol Use Disorders Identification Test (AUDIT) is a ten-item questionnaire approved by the World Health Organization to screen patients for hazardous (risky) and harmful alcohol consumption. It was developed from a WHO multi-country collaborative study, [ 1 ] [ 2 ] [ 3 ] the items being selected for the AUDIT being the best performing of ...

  9. Data auditing - Wikipedia

    en.wikipedia.org/wiki/Data_auditing

    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.