How do automation and AI help build trust in financial reporting?

At PwC, digitally upskilled auditors have saved thousands of hours by automating manual processes. Digitally enhancing aspects of the audit also made it possible for PwC to complete client audits virtually with little disruption when offices were shuttered in response to the pandemic, underscoring the power of augmenting human expertise with digital data-wrangling capabilities.

Five ways AI and automation are helping to build trust and enhance audit quality

1. Auditors who build bots to automate repetitive tasks

We’ve all encountered situations where inefficient processes cause unnecessary bottlenecks. Now, auditors have the ability to mitigate these challenges by building custom automations called bots that can handle time-consuming (but necessary) audit tasks. In one case, a tech-trained auditor created a bot that automated the process of reconciling insurance claims in Excel spreadsheets full of pivot tables. The bot accomplishes the same reconciliation in a fraction of the time and reduces the potential for human error. This is a prime example of how PwC’s citizen-led upskilling movement is giving our employees the tools and knowledge to improve their day-to-day work and enhance quality.

2. AI that reads data in a fraction of the time

AI is being dispatched to automatically read and test audit documents, by comparing reported cash balances to bank reconciliations, bank confirmation letters and obtaining foreign exchange and bank credit-rating information from third-party sources. Wherever auditors might have had to manually review and verify information in a repeatable manner is an area where traditional work can be augmented by technology. When properly deployed, a reduction of manual processes reduces the risk of accidental human errors and reclaims hundreds of hours auditors previously spent on those tasks so they can focus on higher-value work.

3. Data-driven risk assessment that right-sizes approach

While most companies keep their data in ERP systems, they haven't always been able to give auditors access to every relevant transaction. Now, though, auditors can gain read-only access to a company’s data, including unstructured data found in contracts and other documents. Access to the full population of a client’s data allows auditors to paint a clearer picture, so they can focus on risk areas and create a responsive audit plan.

4. Better detection of anomalies

The same cognitive technology that can analyze data to reveal risks and guide the audit plan can also expose unusual transactions that can then be dealt with earlier in the audit process. This offers an opportunity to achieve more targeted testing of the financial statements being audited. That’s just one more way technology — and the people who know how to use it — are bolstering audit quality.

5. Data visualization tools bring insights to life

Instead of viewing data in spreadsheets or other static formats, auditors can use responsive visualization tools to see the data means. Data visualization tools take the output from automated processes and offer the opportunity to explore trends or drill down with a click into anything that seems unusual. A company’s finance leaders can stay on top of audit progress using similar tools that make it easy to gauge audit progress and even drill down into financial data to help guide business strategy and decision-making.

In fact, 54% of companies surveyed say they’re using AI to improve decision-making, so it shouldn’t surprise auditors when client companies start expecting to see proof that AI is enhancing the audit experience and audit quality.

A matter of trust

High-quality, accurate financial-statement audits are essential in building stakeholder trust—and tech-enabled audits performed by digitally savvy auditors are already laying the necessary foundation.

Just as important, the AI itself must be trustworthy, which requires more than just being aware of AI risks. You must also take definitive steps to manage AI risk by prioritizing responsible AI. Unfortunately, results from our 2021 AI survey show that although most companies are aware of AI risks, they’re not always doing what’s needed to mitigate them. Half of respondents in this year’s survey said responsible AI tools to improve privacy, explainability, bias detection, and governance were their top priority among AI applications. But when it comes to action, only about a third report plans to take definitive steps toward achieving responsible AI to address these concerns.

Still, solving any business problem starts by recognizing the problem exists — and we’re committed to helping businesses that are embracing AI do whatever is necessary to ensure AI systems are responsibly designed and deployed.