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  2. 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).

  3. 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.

  4. Tanagra (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Tanagra_(machine_learning)

    Tanagra is a free suite of machine learning software for research and academic purposes developed by Ricco Rakotomalala at the Lumière University Lyon 2, France. [1] [2] Tanagra supports several standard data mining tasks such as: Visualization, Descriptive statistics, Instance selection, feature selection, feature construction, regression, factor analysis, clustering, classification and ...

  5. Rexer's Annual Data Miner Survey - Wikipedia

    en.wikipedia.org/wiki/Rexer's_Annual_Data_Miner...

    Rexer Analytics’s Annual Data Miner Survey is the largest survey of data mining, data science, and analytics professionals in the industry. It consists of approximately 50 multiple choice and open-ended questions that cover seven general areas of data mining science and practice: (1) Field and goals, (2) Algorithms, (3) Models, (4) Tools (software packages used), (5) Technology, (6 ...

  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. e-QIP - Wikipedia

    en.wikipedia.org/wiki/E-QIP

    e-QIP form of John O. Brennan. e-QIP (Electronic Questionnaires for Investigations Processing) is a secure website managed by OPM that is designed to automate the common security questionnaires used to process federal background investigations. e-QIP was created in 2003 as part of the larger e-Clearance initiative designed to speed up the process of federal background investigations conducted ...

  8. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.

  9. Argus – Audit Record Generation and Utilization System

    en.wikipedia.org/wiki/Argus_–_Audit_Record...

    The audit trail has traditionally been used as historical network traffic measurement data for network forensics [5] and Network Behavior Anomaly Detection (NBAD). [6] Argus has been used extensively in cybersecurity , end-to-end performance analysis, software-defined networking (SDN) research, [ 7 ] and recently a very large number of AI/ML ...