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IIBA CBDA Exam Questions
- Topic 1: Financial Transactions and Fraud Schemes: This section evaluates your understanding of fraudulent financial transactions in accounting records. You'll need to showcase your knowledge of fundamental accounting and auditing principles, various fraud schemes, fraud deterrence through internal controls, additional relevant accounting and auditing topics.
- Topic 2: Law: This portion examines your grasp of legal frameworks used in prosecuting fraud cases. It also assesses your awareness of the legal implications involved in conducting fraud examinations such as elements of criminal and civil law, evidentiary rules, and legal rights of defendants and plaintiffs.
- Topic 3: Investigations: This domain assesses your proficiency in essential investigative techniques for gathering evidence and identifying fraud perpetrators and it covers effective interviewing strategies, methods for obtaining statements, accessing and utilizing public records, techniques for tracking illicit financial activities Recognizing deceptive behavior, and crafting comprehensive investigation reports.
- Topic 4: Fraud Prevention and Deterrence: In this segment, candidates are tested for their knowledge of fraud motivations and preventive measures such as theories of criminal behavior, characteristics of white-collar crime, patterns in occupational fraud, strategies for fraud prevention, conducting fraud risk assessments, ethical standards as outlined in the ACFE Code of Professional Ethics.
Free IIBA CBDA Exam Actual Questions
Note: Premium Questions for CBDA were last updated On Feb. 19, 2025 (see below)
An analyst is performing regression analysis and reviewing the results. They would like to rescale the variables in the model to more clearly reflect the relationship between the regression coefficients. Which technique could be used to rescale the variables?
A data scientist is analyzing a dataset to determine if there is a strong relationship between two variables. A measure of covariance is done. Which of the following graphs indicate Zero Covariance between variables?
Covariance measures the directional relationship between the returns on two assets. A positive covariance means that asset returns move together while a negative covariance means they move inversely. Zero covariance indicates that the returns on the two assets move independently of each other. In the context of a scatter plot, zero covariance is represented by a plot where the points do not show any upward or downward trend but are rather scattered randomly on the graph with no discernible pattern.
Graph 4 displays such a pattern where there is no apparent relationship between the variables on the x and y axes, indicating that there is zero covariance between them.
An analyst is doing a clinical study on the value of analyte among a large population of healthy people. The analyst is going to use a Gaussian Distribution to share the results. Which of the following represents a Gaussian Distribution?
The Gaussian distribution, also known as the normal distribution, is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In graph form, the Gaussian distribution will appear as a bell curve, which is the case with option A. It is characterized by its bell-shaped curve and is defined by the mean () and the standard deviation (). It is a common assumption for the distribution of independent, randomly generated variables.
A data scientist is analyzing a dataset to determine if there is a strong relationship between two variables. A measure of covariance is done. Which of the following graphs indicate Zero Covariance between variables?
Covariance measures the directional relationship between the returns on two assets. A positive covariance means that asset returns move together while a negative covariance means they move inversely. Zero covariance indicates that the returns on the two assets move independently of each other. In the context of a scatter plot, zero covariance is represented by a plot where the points do not show any upward or downward trend but are rather scattered randomly on the graph with no discernible pattern.
Graph 4 displays such a pattern where there is no apparent relationship between the variables on the x and y axes, indicating that there is zero covariance between them.
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