ML-assisted auditing
https://www.compact.nl/en/articles/using-machine-learning-in-a-financial-statement-audit/
Machine-learning techniques can be split into two (4) classes, unsupervised learning and supervised learning
( --> Reinforcement and Generative AI )
the auditor would like a dashboard with no more than six different ratios that collectively summarize the financial performance of the client :
liquidity : Ability to generate cash
solvency : Ability to pay debt
profitability : Ability to earn money ( Cost analysis )
asset utilization : Ability to use asset
Return on invested capital : ROI for invest capital
financial market: Stock Exchange
A similar approach has been taken to classify journal entries
Identifies the main transaction streams within a company, like purchases, sales, payments, receipts, payroll, fixed asset additions, etc.
typically a financial statement account that the auditor wants to examine, and a set of predictors, financial or non-financial data that the auditor believes has a plausible relationship with the dependent variable.
depreciation charges against the historical cost of fixed assets
interest expense against the balance of long-term debt
or a margin analysis between revenue and cost of sales
logistic regression
A loan rating is an ordinal variable ranging from AAA (the best rating) to F (the worst).
journal entry testing
The algorithm is trained on large volumes of transactional data, some of which are fraudulent, and others are not
Data pooling
Audit evidence
Data accuracy
Familiarity with statistical models
Innovation cost
Finance Statement Introduction
https://www.investopedia.com/terms/f/financial-statements.asp