IASIU CIFA key terms

A professional who examines data, transactions, and behaviors to identify, investigate, and document potential fraudulent activity, often supporting litigation or insurance claims.

An indicator or pattern that suggests possible fraud but does not by itself prove it, used to prioritize further investigation.

A model explaining fraud as the convergence of pressure, opportunity, and rationalization, helping analysts assess risk and motive.

The documented chronological record of who handled evidence, when, and how, ensuring its integrity and admissibility in legal proceedings.

A structured record listing each item of evidence, its source, collection date, and storage location, used to maintain chain of custody.

The process of identifying data points, transactions, or behaviors that deviate significantly from expected patterns, often signaling potential fraud.

A data point that lies far outside the typical range of a dataset, which may indicate error, manipulation, or a genuine unusual event.

A statistical principle stating that in many naturally occurring datasets, leading digits are not uniformly distributed but follow a predictable logarithmic pattern; deviations can suggest fabrication.

The process of checking data for accuracy, completeness, and conformity to rules or expected formats before analysis.

A technique for visually or mathematically mapping relationships among people, organizations, accounts, and transactions to reveal hidden networks.

The disciplined practice of questioning assumptions, evaluating evidence objectively, and considering alternative explanations before drawing conclusions.

The tendency to seek, interpret, and recall information that supports existing beliefs while ignoring contradictory evidence, a common pitfall in fraud investigations.

A structured method of formulating a testable explanation and evaluating it against data to determine whether it is supported or refuted.

A systematic approach to identifying the underlying reasons for a problem or control failure, rather than merely addressing its symptoms.

An iterative questioning technique that asks 'why' repeatedly to drill down from a symptom to its fundamental cause.

Raw, unprocessed facts, figures, or observations that can be recorded, stored, and analyzed to produce information.

Data that has been processed, organized, or interpreted so that it is meaningful and useful for decision-making.

Data organized into a predefined format, such as rows and columns in a table, making it easy to search and analyze.

Data lacking a predefined model or format, such as free-text documents, emails, images, or audio, which often requires special tools to analyze.

An organized collection of data stored electronically and structured for efficient retrieval, management, and updating.

A database object that stores data in rows (records) and columns (fields), representing a single entity type such as transactions or customers.

A single column in a database table that holds one type of attribute for each record, such as date, amount, or customer ID.

A single row in a database table that contains all the fields for one instance of the entity, such as one transaction.

A field or combination of fields that uniquely identifies each record in a table and cannot contain null values.

A field in one table that refers to the primary key of another table, establishing a relationship between the two tables.

A structured sequence typically including problem definition, data collection, cleaning, exploration, modeling, interpretation, and communication of results.

The process of detecting and correcting errors, inconsistencies, duplicates, and missing values in a dataset to improve its quality before analysis.

An initial phase of analysis using summary statistics and visualizations to understand data distributions, patterns, and anomalies before formal modeling.

An interactive Excel tool that summarizes, groups, and cross-tabulates large datasets, allowing quick exploration of totals and trends.

An Excel function that searches for a value in the first column of a range and returns a corresponding value from another column in the same row.

A flexible Excel lookup combination that uses MATCH to find a position and INDEX to retrieve a value, often preferred over VLOOKUP for its ability to look left and resist column insertion.

An Excel function that sums values in a range based on multiple criteria, useful for aggregating transactions by date, vendor, or category.

An Excel function that counts the number of cells meeting multiple criteria, often used to detect duplicate or repeated transactions.

The process of identifying identical or near-identical records, such as repeated invoices or payments, which may indicate error or fraud.

A chart that groups numerical data into bins and displays the frequency of values in each bin, revealing distribution shape and outliers.

A graph plotting one variable against another to reveal relationships, clusters, or outliers between two numerical measures.

A visual representation of entities as nodes and their relationships as edges, used in link analysis to expose fraud networks.

A statistical measure of the strength and direction of a linear relationship between two variables, not implying causation.

A measure of how many standard deviations a data point lies from the mean, useful for flagging unusual transactions.

Structured Query Language, a standard language for querying and manipulating relational databases.

The SQL command used to retrieve data from one or more tables, specifying columns, filters, and sort order.

A SQL clause that filters rows returned by a query based on specified conditions.

A SQL operation that combines rows from two or more tables based on a related column, such as a primary and foreign key.

A SQL clause that aggregates rows sharing common values into summary rows, often used with aggregate functions like SUM or COUNT.

A general-purpose programming language widely used in data analysis for its readable syntax and libraries such as pandas and matplotlib.

A Python library providing data structures like DataFrame and Series for efficient data manipulation, cleaning, and analysis.

A two-dimensional, labeled data structure in pandas resembling a spreadsheet or SQL table, with rows and named columns.

An interactive web-based environment for writing and executing code, visualizing results, and documenting analysis in a single shareable document.

The process of identifying and merging records that refer to the same real-world entity across different datasets, often using matching algorithms.

The graphical representation of data using charts, graphs, and maps to make patterns, trends, and outliers easier to understand and communicate.

A visual interface that consolidates key metrics and charts into a single view, enabling monitoring and quick decision-making.

The ability to convey findings clearly and persuasively to varied audiences through writing, speaking, and visual aids, tailoring message and detail to the listener.

A concise overview of a report's key findings, conclusions, and recommendations, written for decision-makers who may not read the full document.

The practice of combining data, narrative, and visuals to communicate insights in a compelling and memorable way.

The practice of combining data, narrative, and visuals to communicate insights in a compelling and memorable way.