The power of AI to transform financial reporting

ChatGPT, Gen AI, Machine Learning – just to name a few buzzwords – are new technologies that are already indispensable in our daily lives. Artificial Intelligence (AI), as a general term encompassing this vast field, is playing an increasingly important, if not irreplaceable, role in both private and professional environments and in a very cross-cutting manner.

But here we want to narrow the focus and look at what is happening in financial reporting because of AI implementation, as this is one of the areas currently undergoing a significant transformation that will deepen further in the near future. Through the use of AI, financial reporting processes are streamlined, insights are generated more accurately, and reaction times are accelerated. In general, this translates into greater efficiency and a reduction of errors (if it is applied correctly).

Companies are recognizing the trend toward AI implementation. According to one of the latest studies published by KPMG on the use of AI in financial reporting and auditing (which surveyed 1,800 financial executives from the world’s leading economies), three-quarters of companies are already using or implementing AI in financial reporting, and it is expected that, within the next three years, usage will increase to 99%. Another survey published by McKinsey & Company, from 2024, indicates that 65% of respondents, globally, are already using AI in at least one business unit; compared to one-third, who said so during 2023.

This trend is supported by the budget allocated to AI adoption, as indicated in the KPMG report, led by the technology, media and telecommunications sector, which currently invests 10.8% of its total budget in AI, followed by the manufacturing sector with 10.1% in AI-related spending; and leaving an average, for the rest of the sectors, of 9.9% of the total budget, allocated to AI.

Globally, private investment in AI between 2013 and 2022 amounted to approximately 248,000 million in the United States, up from 95,000 million in China. In comparison, within the European Union, the leaders were Germany with 7,700 million dollars and France with 6,600 million dollars.

Reconsider traditional approaches

This global movement is pushing organisations to rethink traditional approaches to business processes, adopting tools that improve the accuracy of data results while reducing costs.

Artificial intelligence can automate repetitive reporting tasks, detect potential financial trends based on historical data, and even analyse text passages in financial reports. One of its greatest advantages in the accounting area is its ability to identify unusual patterns in large data sets, which helps detect fraudulent activities such as unauthorised transfers, accounting irregularities and misappropriation of assets at an early stage.

Among the clearest advantages are the increased ability to predict trends and impacts thanks to increased data accuracy and real-time risk analysis. These benefits drive demand for AI adoption in financial reporting processes and offer stakeholders better insights and greater confidence in their data.

In this context, the role of financial professionals is evolving away from manual data verifications to the benefit of AI-driven analysis interpretation. Human experience is applied more effectively to ensure accurate financial reporting and sound decision-making.

Despite all the benefits of an AI-backed process, there are always risks when using this new technology.

Ensure the quality of training data

Bias and “hallucinations” in AI algorithms can lead to misinterpretations of financial data, which could cause inaccurate reporting. For example, a poorly designed algorithm might not detect fraudulent activity due to biased training data. As AI also relies on pre-trained input data, there is always the risk of incomplete or low-quality entries, leading to unreliable results. Therefore, data quality must be ensured and the input process carefully managed to avoid unreliable results.

In addition to the technical and data-related risks mentioned above, there is another variable to consider, that is, the greater risk of cyber-attacks: Data breaches increased globally by 72% between 2022 and 2023. This can result in significant costs for the affected entity. In Spain, for example, the average cost of a cyber-attack is $12,400, which underlines the importance of using this technology effectively.

Also, the affected entity may suffer reputational damage, especially if the cyberattack exposes personal and sensitive customer information, highlighting the need for strong legal controls over data privacy regulation when using AI in business. Therefore, customer security and data protection requirements must be ensured in any event, together with statistical validity and model accuracy, to achieve reliable results.

The future of financial reporting is promising with the integration of artificial intelligence. Far from replacing professionals, AI will elevate their role, allowing them to focus on higher-value tasks, such as interpreting complex data and providing strategic insights, among others. And it will empower them to discover patterns and anomalies that would otherwise go unnoticed, ensuring greater accuracy and reliability in financial reporting through more efficient, secure and insightful processes.

Author: Paul Berenguer (Business Innovation Manager at Bové Montero)