Exam 2 Flashcards
Data-driven fraud detection
using data, usually through the mining of those data, to identify patterns, anomolies, etc. to find possible fraud symptoms
Accounting errors
Statistical analysis
is a component of data analytics. Statistical analysis involves collecting and scrutinizing every data sample in a set of items from which samples can be drawn. A sample, in statistics, is a representative selection drawn from a total population
Open Database Connectivity (ODBC)
A connector between the front-end analysis and the back-end corporate database
Data warehouse
a repository for data
Benford’s law
the first digit of random data sets will begin with a 1 more often than with a 2, a 2 more often than with a 3, and so on
Digital Analysis
the art of analyzing the digits that make up number sets
Stratification
the splitting of complex data sets into groupings
Summarization
runs one or more calculations on the subtables to produce a single record representing each subtable
Time trend analysis
analysis of prices, quantities, costs, or other values over time
Fuzzy matching
a technique that allows for searches to be performed that will find matches between some text and entries in a database that are less than 100 percent identical
Vertical analysis
compares numbers in the statement from one period to the next
aka calculates percent of total for each line item and look for anomalies. Compares everything in relation to total income.
Horizontal analysis
key financial statement ratios are calculated and changes in these ratios from period to period are compared.
aka time trend analysis
Types of ratios:
- Gross Margin Ratio
- A/R Turnover Ratio
- Profit Margin
- Current Ratio
- Quick Ratio
- Net Profit Margin
What are the 6 data analysis steps?
- Understand the Business
- Identify possible frauds that could exist
- Catalog possible fraud symptoms
- Use technology to gather data about symptoms
- Analyze results
- Investigate Symptoms
Which is the most important step in data analysis?
Catalog Possible Fraud Symptoms
Types of Fraud Symptoms:
Accounting Errors, Internal Control Weaknesses, Analytical Errors, Extravagant Lifestyles, Unusual Behaviors, and Tips and Complaints.
Difference between errors and frauds:
Errors are usually carried throughout the data set, so an auditor can usually see errors using a statistical sample, but frauds are like a needle in a haystack and may only be present in a couple transactions.
When should you use Benford’s law?
Just use it as a sanity check.
Methods for Gathering Data:
- Open Database Connectivity
- Text Import
- Hosting a Data Warehouse
The most important and often overlooked step:
Getting the right data, in the right format, during the right time.
What is the least effective method of financial statement analysis?
Comparing account balances from one period to the next.
Data analysis techniques:
- Outlier investigation
- Time trend analysis
- Fuzzy matching.
Vulnerability Chart
a tool that explicitly considers all aspects of the fraud