ADA Fraud Detection Analytics

Question 1

What is Benford's Law primarily used for in fraud detection analytics?

Accepted Answer

To identify unusual digit frequency distributions in numerical data

Answer

Benford's Law states that in naturally occurring numerical data, leading digits follow a predictable logarithmic distribution, and deviations from this pattern can indicate data manipulation or fraud.

Question 2

Which statistical technique is most effective for identifying transactions that fall outside normal patterns and may indicate fraud?

Accepted Answer

Outlier detection

Answer

Outlier detection identifies data points that deviate significantly from the expected distribution, making it effective for flagging potentially fraudulent transactions that fall outside normal patterns.

Question 3

What does a 'ghost employee' scheme in payroll fraud typically involve?

Accepted Answer

Payroll payments made to fictitious or terminated employees

Answer

Ghost employee schemes involve creating fictitious employees or retaining terminated employees in the payroll system to divert unauthorized payments to the fraudster.

Question 4

Which analytical technique compares actual financial results against established expectations to identify potential fraud indicators?

Accepted Answer

Expectation-based analysis

Answer

Expectation-based analysis establishes what results should look like based on historical trends, budgets, or industry benchmarks, and flags deviations that may indicate fraudulent activity.

Question 5

In fraud detection analytics, what does 'transaction velocity' testing examine?

Accepted Answer

The frequency and volume of transactions within a given time period

Answer

Transaction velocity testing examines the frequency and volume of transactions over time, helping detect unusual spikes or patterns that may indicate fraudulent activity such as credit card fraud or expense abuse.

ADA - Audit Data Analytics Certification Practice Test

ADA - Audit Data Analytics Certification Practice Test

ADA Fraud Detection Analytics