Chapter 6 Data-driven Fraud Detection

Data-driven fraud detection:

• Identifies possible fraud suspects

• Looks for errors in databases

• Monitors unusual behaviors

• All of the above

SQL stands for:

• Systematized Queueing Language

• Structured Queueing Language

• Structured Query Language

• None of the above

____ ______ _____ _________ is a method of detecting fraudulent activities by analyzing large amounts of data using advanced analytics techniques.

(Type your answers in CAPITAL LETTERS.)

Detecting and responding to possible frauds that could exist immediately can minimize or prevent losses.

• TRUE

• FALSE

Which of the following techniques uses Artificial Intelligence to make risk rule suggestions:

• Data Mining

• Machine Learning Algorithms

• Data Quality

• Statistical Analysis

The following are the importance of ongoing monitoring and analysis in data-driven fraud detection, EXCEPT:

• Shortage of skilled professionals

• Timely detection of anomalies

• Adaptability to evolving fraud patterns

• Data quality assurance

If a search reveals that an employee and a vendor have the same telephone number, this result may indicate that:

• Employees may be establishing dummy vendors

• Vendors are overcharging for goods purchased

• Contractors are billing the wrong dates

• A vendor is receiving kickbacks

Which of the following is true for accounting anomalies?

• They represent intentional sabotage controls

• They are primarily caused by lack of training

• They are problems caused by failures in system, procedures, and policies

• They represent fraud and normally result in legal action begin taken