FINANCE Auditing with ML

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

Barriers and roadblocks

Data pooling

Audit evidence

Data accuracy

Familiarity with statistical models

Innovation cost