Monday, June 24, 2024

Future of financial auditing

Must read

Auditing and assurance act like a check-up for a business, and ensure that it grows in a healthy way. By verifying the accuracy and reliability of a company’s financial statements, audits ensure transparency and attract investors who rely on the information. Auditors examine a company’s financial statements and after the verification, state that the financial statements give a “true and fair view” of the company’s health. This transparency allows the stakeholders to make better decisions based on the available information.
With the advent of Artificial Intelligence (AI), the auditing landscape is undergoing a transforming change. AI’s ability to process massive datasets is empowering the auditors unusually. As AI can analyse vast financial transactions, contracts, and other data points, it can uncover hidden patterns and irregularities that might escape human auditors.
It is indeed a reality today that AI is enabling the auditors to delve deeper into providing expert advice to businesses, by taking away from them the tedious job of data extraction, verification, and reconciliation.
Transition to insightful auditing
The financial terrain is flooded with massive amounts of data. Almost every organisation across industries generates enormous financial transactions, records, and communications. With manual processes, this valuable data can prove to be taxing for auditors. However, AI empowers the auditors, working as a transforming data analytics engine. Here’s how:

Automates repetitive tasks: Auditing involves sifting through large amounts of data from multiple sources. AI can automate this task using tools that can collect, extract, download, and compile information from different sources. AI can also use techniques like Optical Character Recognition (OCR) to extract text from scanned documents and Natural Language Processing (NLP) to categorise that data.

100% verification instead of sampling based verification: Traditionally, auditors review a statistically significant sample of transaction to assess overall risk. AI can analyse entire data sets, identifying unusual patterns and inconsistencies that might be missed in a sample. This enables the auditors to focus their judgement on the red flags.

Better fraud detection: The use of AI enables the detection of hidden data patterns and inconsistencies. Minor changes in financial ratios and unusual transactions can be identified with advanced analytics and it can also mark out the potential fraud areas.

Analysis of expansive datasets: The vast amount of structured and unstructured financial data can be analysed by AI algorithms seamlessly. The data may include financial statements, business contracts, emails, or social media data. The process, consequently, allows the stakeholders to have a better understanding of the company’s financial performance and potential risks.

Predictive analytics: AI examines the past trends and identifies emerging threats to forecast future risks. The auditors, in the process, get better insights to provide to the companies, along with proactive recommendations.

AI evolving role of auditors
While AI may have automated many tasks in auditing, it doesn’t negate the necessity of human intelligence in it. With the emergence of AI, auditors are better positioned to shift from the role of data processors to strategic advisors. AI enables the auditors to:

Focus on professional judgment: With AI handling the regular tasks, auditors can apply their expertise and judgment to understand complex findings and make better decisions.

Implement critical thinking: While AI can detect potential issues, auditors can implement critical thinking to investigate the root cause and assess the impact on financial statements.

Communicate and collaborate: Auditors can play a crucial role in effectively communicating AI-driven insights to stakeholders, and collaborating with company management to address the identified risks.

Challenges and considerations
The adoption of AI in auditing presents some challenges that need to be addressed:
Data quality and data bias: AI algorithms can efficiently work as per the data they are trained on. However, for reliable audit results, it is crucial to ensure data quality and diminish the potential bias in AI models.

Transparency: Understanding how AI arrives at its conclusions is essential for auditors to provide clear explanations to stakeholders.

Ethical considerations: Along with other challenges, the use of AI in auditing can raise ethical concerns around data privacy, security, and job displacement. Addressing these concerns is important for building trust and ensuring responsible AI implementation.

Future of assurance
There is no doubt that the future of financial auditing is AI-powered. As anticipated, AI will continue to evolve, and offer more advanced tools for risk assessment, anomaly detection, and monitoring. Furthermore, the combination of AI and professionals is geared up to revolutionise the auditing landscape. It will free up auditors to focus on their core strength – professional judgement. This judgement would further be used to provide valuable advisory services to businesses, helping them identify risks, improve controls, and achieve their growth objectives.

(The author, SwethaKochar, is the Founder & Partner,of  PKC Performance Partners)

- Advertisement -spot_img

More articles

- Advertisement -spot_img

Latest article