Chapter 6 Flashcards
(18 cards)
Why should Data Analytics be applied to audits?
It increases coverage while reducing overall audit length
Three parts of Audit Procedures
Nature
Extent
Timing
Nature
Why we perform audit procedures
Extent
How much we can test in an audit
Timing
How often procedures should be run
Descriptive Analytics Examples (READ)
Age analysis
Sorting
Summary statistics
Sampling
Age Analysis
Groups balances by date
Summary Statistics
Mean, median, min, max, count, sum
Diagnostic Analytics Examples (READ)
Z-Score
Benfords Law
Drill Down
Clustering
Exact and Fuzzy Matching
Sequence Check
Stratification
Benfords Law
Identifies transactions or users with nontypical activity based on the distribution of first digits
Drill Down
Explores the details behind the values
Exact and Fuzzy Matching
Joins tables and identifies plausible relationships between
Sequence Check
Detects gaps in records and duplicates entries
Stratification
Groups data by categories
Examples of Predictive Analytics (READ)
Regression
Classification
Probability
Sentiment Analysis
Examples of Prescriptive Analytics (READ)
What If Analysis
Applied Statistics
Artificial Intelligence
Benefits of Data Analytics (READ)
Automated data extraction and reconciliation
Continuous monitoring and real time analysis
Sampling optimization
Anomaly detection
Predictive analytics for forecasting
Duplication and error detection
Generalized Audit Software Examples
Excel and IDEA
