In this new era where data is the new oil, traditional audit methods are obsolete. Data analytics are completely revolutionizing the approach to audit. You are either on the data analytics boat or remain on the pier. Pick one.
The End of an Era: Why Traditional Audit is Dead
Traditional audit methodology, consisting of statistical sampling and manual reviews, was effective when used in the world of paper and printouts. But in today's digital ecosystem – where companies process millions of transactions daily, across multiple platforms – this approach can become like searching for a needle in a haystack while blindfolded.
Because annual audits are reactive, they only discover issues once damage has already been done; this lag in providing real-time information is becoming unacceptable among stakeholders.
The Data Analytics Revolution
Data analytics is revolutionizing audit processes, offering capabilities once thought to be impossible. Consider some transformative changes:
Data analytics tools enable companies to instantly examine millions of records within seconds and pinpoint patterns, anomalies and risks with precision. Machine learning algorithms now make predictions of high-risk transactions before they occur while natural language processing identifies compliance issues instantly in thousands of records.
The New Audit Professional: From Sample Tester to Strategic Advisor
The old way: select a sample, perform manual testing, crunch the numbers. The new way: today’s auditors must combine traditional knowledge with data science capabilities. It’s no longer sufficient to understand what the numbers mean, but how to use data analytics to gain business insights that drive business value.
Actionable Takeaways for Audit Professionals
In order to remain relevant in this new era, auditors must adapt and evolve. Here are some actionable takeaways:
- Invest in Data Analytics Training: Upskill the entire team on data analytics. The training program should be comprehensive and cover both technical skills and analytical thinking.
- Upgrade Your Toolkit: Explore and adopt advanced analytics tools such as R, Python, Alteryx, and SQL.
- Implement Continuous Monitoring: Establish systems for real-time data analysis to identify potential anomalies early. Move from annual auditing to continuous monitoring.
- Enhance the Risk Assessment Process: Use data analytics to identify high risk areas. Leverage predictive analytics to forecast potential risks and opportunities.
- Deploy Data Visualization: Don’t show us the data, tell stories with data. Use visualization tools to depict key data insights and trends. Consider tools such as Superset, Tableau and Power BI.
- Collaborate Cross-Functionally: Work closely with cross-functional engineering, IT, data science and finance teams to ensure a seamless integration of data analytics into audit processes.
Audit at a Crossroads
The audit profession is at a crossroads. Traditional audit methods no longer are sufficient. Data analytics has revolutionized the audit process. In order to provide greater value to their companies and stakeholders, auditors must embrace the change and develop the necessary skills and expertise.
About the author: Muema Lombe, CISA, CRISC, CGEIT, CRMA, CSSLP, CDPSE, leads technology audit and data analytics at Airbnb. He has over 10 years of professional experience in external audit, internal audit, technology audit, compliance and security, ranging from Big 4 to high growth tech startups.