As technology advances and AI become more common within enterprises, the number of Finance teams that utilize the powerful insights that AI and machine learning can provide is increasing quickly. While AI is undoubtedly benefiting financial operations, there is still a risk in blindly trusting the recommendations, insights, or predictions AI provides.

Why?… Because when we don’t fully comprehend how our AI algorithm (or process)is making decisions, we cannot optimize all that AI has to offer. This leads to potential biases, errors, and costs caused by AI.

I know what you’re thinking… AI is extremely complex and opaque to the majority of humans. How are we supposed to understand its decision-making processes, insights, predictions, and more?

The answer? Explainable AI (XAI).

What is XAI?

Just the term “artificial intelligence” on its own is intimidating to most, and now we are adding another word? Don’t worry, it is much simpler than it sounds. In fact, it’s “explainable.” (pun intended)

XAI is a new and emerging area attempting to focus on increasing the transparency of AI processes. The overall goal of XAI is to help humans understand, trust, and effectively manage the results of AI technology.

XAI optimizes the use of AI in your environment through an in-depth model and data investigation of your current AI system(s). The results are what all Finance teams and companies like to see: increased efficiency, decreased costs, and improved business decisions.

AI Used by CFOs and Finance Teams

If you work as a Finance professional, you may understand the concept of artificial intelligence but aren’t sure how Finance teams are leveraging it.

Let’s look at some examples of common AI models used for financial operations that can positively benefit from XAI:

  1. Predictive Analysis – Accurate forecast predictions are essential to any business, and represent a vital role of finance teams. For example, predictive analysis can help Finance Managers predict optimal pricing for different age ranges. AI allows the Finance team to predict how competitors will react, how customers will respond, and where risks may arise.

XAI can increase the accuracy of these predictions and forecasts through the detection of biases or errors. It also provides the Finance team with a better understanding of why/how the projections are made so they can trust the results.

  1. Fraud Detection – Due to AI’s ability to analyze trends and patterns, it can also detect when there is an anomaly in the pattern, which can represent fraud or suspicious financial activity.

A considerable amount of time and resources are spent on follow-up investigations of flagged activity. With XAI, Finance teams can reduce costs and improve efficiency by having a more dependable detection of fraud and suspicious activity, decreasing unnecessary follow-up investigations.

  1. Accounting – AI eliminates repetitive tasks from the daily workload of Finance teams with automated processes of gathering, sorting, and visualizing pertinent data. This frees up time for Finance teams to focus on more productive tasks and drive the business forward.

When tasks are automated, it is crucial for the Finance team to trust that the automated AI system is operating correctly. XAI increases user trust with an in-depth analysis of the AI-generated results, correcting any errors or biases and providing the team with an understanding of how the AI works so that CFOs and Finance Managers can trust these systems with their financial operations.

Covid-19, Finance, and XAI

The global pandemic is causing business environments, customers, competitors, and data to change. As stated earlier, AI detects trends and patterns in data. With the behavioral changes caused by Covid-19, your data is bound to be largely different than in past years. Will your AI adjust appropriately? Or, will it become obsolete? XAI will ensure your AI investment adjusts to this difference by improving the accuracy of predictions, fraud detection, and financial operations related to AI.

Conclusion

AI is an immense benefit for Finance teams and companies, so the adoption of AI is growing quickly. This is no surprise considering the results of increased efficiency, reduced cost, and improved business decisions.

However, with this new technology, there is a level of distrust due to the inability to comprehend how AI makes decisions. In fact, 67% of the business leaders taking part in PwC’s 2017 Global CEO Survey believe that AI and automation will impact negatively on stakeholder trust levels in their industry in the next five years.

Large companies such as Capital One and Bank of America are already leveraging the benefits of XAI. Many companies and Finance teams will need XAI to understand the insights, solutions, and predictions provided by AI and machine learning systems. The adoption of XAI is more important now than ever.