How AI Can Help Improve Accounting Accuracy

From automating data tagging to maintaining consistency, AI is improving the accuracy of financial reporting. In this piece, we share how AI-powered tools can help accountants avoid costly mistakes and focus more on delivering strategic insights to clients.

In accounting, accuracy isn’t just about getting the numbers right—it’s about understanding the story behind them. 

As an accountant, your clients rely on you to make sense of the shifts in their financials, and that means every detail matters. 

However, given the volume and complexity of financial data that teams have to manage, even small mistakes can cause big headaches. 

This is where artificial intelligence (AI) in accounting can make a real difference by automating data tagging and helping ensure that the work you produce is both correct and consistent. 

In this article, we’ll look at how AI accounting technology is making it easier to maintain accuracy without sacrificing the strategic insights that your clients count on.

Accuracy: The key to explaining “why”

As an accountant, your job goes beyond simply recording transactions.

For instance, when looking at a financial statement, it’s not just about knowing how much money a company made or spent but also about understanding and conveying the reasons behind those changes. 

Think about it this way: your client isn’t paying you to repeat what’s already on their bank statement. They need you to explain why their expenses increased last month or why a certain revenue stream grew.

To do this effectively, you need to know that your data tagging is accurate and correctly categorizes every transaction, vendor, and department. 

Ultimately, this tagging allows you to provide meaningful insights and advice to customers.

The more accurate the data tagging, the better you can answer questions like, “Why did R&D expenses spike this quarter?” or “What caused the sudden increase in operational costs?”

Conversely, inaccurate or inconsistent tagging makes it difficult to provide these explanations, potentially leading to misunderstandings or even financial missteps.

The role of AI in boosting accounting accuracy

Next, let’s discuss how AI fits into all of this.

At Truewind, for instance, we leverage AI accounting technology to help accountants ensure accuracy in two key areas: coverage and consistency.

1. Coverage: Automating data tagging for better accuracy

When we talk about coverage, we’re referring to how comprehensively transactions are tagged and categorized. In accounting, this means ensuring that the vast majority of transactions—ideally 80 percent or more—are accurately explained in terms of their financial impact.

AI plays a pivotal role in achieving this. By using it for every applicable transaction, we can tag multiple dimensions with incredible efficiency, including more advanced attributes such as class, department, and location. 

For example, consider vendor identification. In traditional bookkeeping, identifying the vendor for every transaction and entering it into the system can be tedious. However, if you skip this step, you lose critical data that can hinder future analyses.

On the other hand, AI automates this process, recognizing vendors by analyzing transaction texts and historical patterns and conducting online searches when necessary.

By doing so, AI saves time and ensures that future transactions involving the same vendor are consistently tagged, preserving accuracy over the long run.

2. Consistency: Maintaining historical accuracy

Beyond coverage, consistency is another cornerstone of accuracy.

In order to explain why financial changes happen, you need to ensure that transactions are categorized in a consistent way over time.

Imagine that you’re dealing with a LinkedIn subscription. You could classify this as “dues & subscriptions” or “marketing & ads.”

Either classification could be correct, but the key is aligning with how similar transactions have been previously categorized.

Here, AI accounting technology can help by referring to historical patterns and providing the most relevant context from your ERP system.

If the history shows inconsistency in how certain transactions have been categorized, AI can flag these discrepancies for human review and ensure they’re corrected moving forward.

This hybrid approach—using AI to catch issues while involving human oversight—verifies that your data remains accurate and reliable.

The consequences of inaccuracy

Accuracy is more than just a nice-to-have. Inaccurate financial data can lead to significant consequences, from underpaying or overpaying taxes to submitting incorrect reports to regulatory bodies. 

The result? Potential fines, delayed reports, and damage to your client’s reputation.

Moreover, accuracy is essential for accountability. As an accountant, your clients rely on you to provide precise financial data supporting audits, board meetings, and investment decisions. 

Inaccuracy undermines that trust and can lead to financial mismanagement or legal issues.

Using AI safely and effectively

For those concerned about AI's reliability and its involvement in financials, it’s important to clarify a common misconception: AI doesn’t make all the decisions on its own.

At Truewind, we recognize that AI is just one piece of the puzzle. While AI accounting technology can automate routine tasks and enhance accuracy, it works alongside established checks and balances, helping ensure the safety and reliability of your financial data.

Here’s how we validate that AI in accounting is used safely and efficiently to maintain the highest levels of accuracy:

1. Limiting and mitigating hallucinations. Rather than attempting to eliminate hallucinations entirely—which isn’t possible—the more pragmatic approach is to focus on limiting and mitigating their impact. This ensures that AI outputs stay within an acceptable range of accuracy without straying into irrelevant or incorrect conclusions.

2. Leveraging relevant context from knowledge graphs. To govern the accuracy of AI-generated answers, we utilize a knowledge graph to provide the most relevant context for large language models (LLMs). This helps confirm that the AI’s outputs are based on informed, context-driven data and stay within the appropriate boundaries.

3. Applying rigorous accounting rules. Our software applies stringent accounting rules to validate the outputs of AI models. We take this one step further for certain types of outputs by using an additional LLM specifically designed to evaluate the factual accuracy of AI-generated data.

4. Human oversight is the final check. Finally, we make sure that human accountants are part of the process. This human-in-the-loop approach provides an essential layer of quality control, certifying that any inconsistencies or errors are addressed before the data is finalized. This oversight also helps reinforce AI learning for future improvements.

Why accuracy should be a top priority

In conclusion, accuracy is the foundation of accounting, and AI is quickly becoming essential for enhancing and maintaining it. 

By automating data tagging and ensuring consistency, AI allows accountants to focus on higher-level tasks—like advising clients and delivering strategic insights—without sacrificing the quality of the financial data.

Ultimately, by safely and efficiently integrating AI accounting technology into our processes, we can help accountants achieve the accuracy and reliability they need to deliver better results for their clients.

Interested in learning more about Truewind and our AI-powered solutions? Chat with our team to get started. 

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