Beyond the Bottom Line: How AI is Transforming Financial Oversight

In the rapidly evolving landscape of finance, artificial intelligence (AI) is emerging as a powerful tool for data analysis and fraud detection. Recently, our team was presented with a challenge: to identify potential "problems" in a set of financial data. Armed with an AI-powered specialized data analyst tool, SCOTi®, we embarked on a journey that would reveal the transformative potential of AI in financial analysis.

Uncovering Patterns and Anomalies

As we began to explore the data, patterns quickly emerged. One of the most striking discoveries was the presence of "cliffs" in purchasing prices – unusual concentrations of transactions at specific price points, followed by sharp drop-offs. This raised important questions: Were these patterns indicative of fraud? Were they the result of employees attempting to navigate system constraints? Or had external parties identified optimal pricing strategies?

This observation reminded me of an early career experience at a software company. The founder had priced our graphing software at $495, just below the $500 threshold that typically required additional approval for university grant purchases. This anecdote highlights how seemingly arbitrary pricing decisions can be driven by underlying systemic factors – a concept that AI can help uncover on a much larger scale.

Leveraging GenAI for Comprehensive Analysis

To deepen our investigation, we employed generative AI to develop a list of pertinent questions about potential fraud. We then processed these questions through the data analyst tool, which not only provided answers but also supplied the underlying logic and SQL queries used to reach its conclusions. This approach allowed us to rapidly analyze the data from multiple angles, flagging transactions that warranted further scrutiny.

The speed and depth of this analysis were eye-opening. Within minutes, we had run 20 complex queries, each accompanied by detailed explanations. This experience highlighted both the power and the limitations of AI in financial analysis. While AI can process vast amounts of data and identify potential issues with remarkable efficiency, it ultimately serves to augment human expertise rather than replace it.

Addressing the Spreadsheet Dilemma

Our exploration of AI in financial analysis led us to consider another common challenge in the field: the prevalence of errors in business spreadsheets. A study published in Phys.org found that a staggering 94% of business spreadsheets contain critical errors. This high error rate can be attributed to the complexity of modern financial models, the limitations of spreadsheet software, and simple human error.

Imagine applying AI-powered analysis to these spreadsheets, using a comprehensive library of common error types and best practices. Such a system could flag potential issues, allowing human experts to focus their attention where it's most needed. As new problems are identified and more experts contribute their knowledge, the AI's capabilities would continually expand.

AI as a Financial Grammar Checker

The potential applications of this technology are vast. Just as grammar checkers have revolutionized writing, AI-powered financial analysis tools could transform how we approach financial data. These tools could:

1. Detect potential fraud 
2. Identify inefficiencies 
3. Highlight over-dependencies 
4. Uncover systemic weaknesses 
5. Ensure regulatory compliance 

By leveraging the combined knowledge of countless financial experts, AI can serve as a powerful first line of defense against errors, fraud, and poor business decisions.

The Human-AI Partnership

It's crucial to understand that AI is not replacing human expertise in this scenario. Instead, it's enhancing our capabilities, allowing financial professionals to work more efficiently and effectively. AI excels at rapidly processing vast amounts of data and identifying potential issues, but human judgment remains essential for interpreting results, making decisions, and implementing solutions.

Consider the potential impact on year-end accounting processes. AI could dramatically streamline the work of accountants by flagging potential issues in advance, allowing them to focus their expertise on resolving complex problems rather than hunting for errors.

Conclusion: A Future of Enhanced Financial Management

As we look to the future, it's clear that AI will play an increasingly important role in financial analysis and management. By automating routine checks, identifying potential issues, and providing rapid insights, AI tools will enable financial professionals to work more efficiently and effectively than ever before.

This vision of the future isn't about AI replacing humans – it's about AI empowering humans to achieve more. As these tools continue to evolve, we can look forward to a financial landscape characterized by greater accuracy, transparency, and efficiency. The result will be a more robust and reliable financial system that benefits businesses, investors, and society as a whole.

Written by: Dr Oliver King-Smith is CEO of smartR AI, a company which develops applications based on their SCOTi® AI and alertR frameworks.

Image source: https://img.freepik.com/