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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 Oct. 29, 2026 (see below)
A data scientist is working with a team of upper level managers to develop a strategy for creating an enterprise analytics program. What critical success factor would help ensure the organization obtains the most value from its data?
Interested in experimenting with analytics, a manufacturing company hires an analyst to see how the capability can be developed within its organization. The analyst is getting started and recognizes the need to show value from the onset of their work to gain upper management's trust and future funding. What action will accomplish these objectives?
The best action for the analyst to show value from the onset of their work is to develop a meaningful question that can be answered with data the company already has in its possession. This way, the analyst can demonstrate the potential of analytics to solve relevant business problems, without spending too much time or resources on data collection or market research. The question should also be aligned with the organization's strategy and goals, and provide actionable insights for decision making12. Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 202: Data Science for Business, Foster Provost and Tom Fawcett, 2013, p. 14.
What is the relationship between a Customer entity and an Order entity, where a customer entry will be present in the Customer entity only if they have made an order?
The relationship between a Customer entity and an Order entity, where a customer entry will be present in the Customer entity only if they have made an order, is a zero-to-one relationship. This means that for each record in the Order entity, there can be either zero or one record in the Customer entity that is related to it. This implies that the Order entity is optional for the Customer entity, and the Customer entity is mandatory for the Order entity12 Reference: 1: A Guide to the Entity Relationship Diagram (ERD) - Database Star 2: Developing an Application - Oracle
An insurance company has seen an upward trend in winter-related accidents over the past three years. The company has just completed an analytics study to better understand the primary reasons for these accidents and assess how many of the drivers were using winter tires. This analysis will help the company decide how to move forward with drivers not taking precautionary measures during winter. What type of analysis will help in determining the primary reasons and percentage of those drivers with winter tires?
Descriptive analytics is a type of analytics that summarizes and visualizes the data to provide an overview of what has happened or is happening, such as the trend of winter-related accidents over the past three years, or the percentage of drivers using winter tires12. Diagnostic analytics is a type of analytics that explores and analyzes the data to understand why something has happened or is happening, such as the primary reasons for these accidents, or the factors that influence the drivers' decisions13. To answer the question, both descriptive and diagnostic analytics would be needed to provide the relevant information and insights for the company. Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 182: Business Analytics: Data Analysis & Decision Making, S. Christian Albright and Wayne L. Winston, 2015, p. 53: Data Science for Business, Foster Provost and Tom Fawcett, 2013, p. 13.
A research marketer is interested in collecting information about the spending habits of families in North Americ
a. Concerned about the volume of data required to conduct the research, they choose to use sampling. The dataset is sourced using all credit card transactions from a leading North American credit card company for Quarter 1 of the prior year. The sample used is:
The sample used in this case is biased, meaning that it is not representative of the population of interest. The population of interest is the families in North America, but the sample is drawn from only one source of data: the credit card transactions from a leading North American credit card company. This sample excludes the families who do not use credit cards, or who use other credit card companies, or who use other payment methods. Therefore, the sample is not random or fair, and it may introduce sampling bias into the research results12 Reference: 1: Sampling Methods | Types, Techniques & Examples 2: Sampling Bias - an overview | ScienceDirect Topics
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