A financial manager of a major company sits before a strict oversight committee, faced with a single direct question: "How can you prove to us that the artificial intelligence managing your money not only works but does so with utmost precision and without errors?".

This question is no longer just a concept from science fiction movies; it has become a reality we live today. According to financial auditing experts, led by Stuart Rubin from the global firm "Deloitte", answering this question is no longer merely a technical matter, but a true test of the credibility of companies and their strategies.

From "A Dazzling Game" to "The Beating Heart" of Business

In the recent past, artificial intelligence in the financial world was seen as a dazzling addition or a "luxury" that companies boasted about. Today, it has transformed into "the beating heart" that manages everything; from writing reports and summarizing contracts to making critical financial decisions.

Artificial intelligence today speaks with great confidence, writing memos and analyzing complex, unstructured data with intelligence that surpasses older software. This confidence exhibited by the system leads humans to tend to trust and rely on it without thinking, and herein lies the danger, and this is where "financial auditors" intervene.

"Audit Trail": How Do We Trace the Machine?

When a machine issues a financial report, auditors are not only concerned with the final result but ask a more important question: How did the machine arrive at this result?

Here, the term known as "Audit Trail" comes into play. To simplify, imagine that artificial intelligence is a skilled chef who has prepared a delicious dish for you. The auditor does not just taste the dish; they request to see the list of ingredients (input data), the cooking steps (algorithmic processes), and how the cleanliness of the kitchen was ensured (human review).

Therefore, it has become essential for companies to document every step taken by artificial intelligence. There must be a clear record explaining:

  • What data did the program rely on?
  • How did it process that data?
  • How did it handle errors when they occurred?

Human Oversight: The Machine Should Not Be Left Alone

Although artificial intelligence saves tremendous time and effort, automating daily tasks such as invoice matching and monitoring unusual expenses, leaving the machine to operate without supervision is akin to allowing an employee to work without a manager; both carry catastrophic risks.

Therefore, financial experts emphasize the principle of "Human in the Loop". There must be a human element to monitor and review. As systems evolve in the future, companies may automate the monitoring itself, but there should always be a record that humans can read and review when necessary.

Governance: Who Is Responsible If the Machine Makes a Mistake?

If artificial intelligence makes a wrong financial decision, who do we blame? The programmer? The accountant? The manager?

To avoid this chaos, strict "governance" must be applied, which simply means establishing rules that clearly define each person's responsibilities:

  • Finance Department: Responsible for understanding the impact of artificial intelligence on financial reports.
  • IT Department: Responsible for ensuring the system operates technically and securely.
  • Internal Auditor: Monitors the entire landscape to ensure there is no manipulation or malfunction.

The principle of "Segregation of Duties" must also be applied. In other words, the employee who designs the artificial intelligence system should not be the same employee who tests and reviews it. This ensures that the system does not become biased or overlook errors that may be unintentional.

Data Quality: The Food That Drives Decision-Making

Artificial intelligence is like a mirror; it reflects exactly what is presented to it. If the data feeding the system is incomplete or biased, the decisions and reports will necessarily be incorrect. This could lead to legal penalties, a collapse in the company's stock, or a loss of investor confidence. The solution lies in continuously examining data sources, protecting sensitive data, and documenting every inspection for future reference.

Don't Wait for the Storm.. Prepare for It

Documentation and transparency are not just routine procedures to satisfy auditors; they are a lifeline when things go wrong. Good documentation allows companies to step back and understand where the mistake occurred and how to fix it.

Experts' advice to financial managers is clear: "Don't wait for audit night to start looking for answers". Building a transparent and documented environment for artificial intelligence not only ensures a smooth financial audit but also sends a strong message to markets and investors that this company is ready for the future, takes risk management seriously, and does not compromise on excellence and credibility.