Technology in auditing plays a central role in shaping the future of the profession. My KPMG colleagues from around the world have highlighted the impact of AI, Big Data, continuous auditing, and blockchain technology on ESG assurance.
As auditing becomes more complex, the demand for innovations in the international audit landscape is increasing. These emerging audit technologies help ensure consistency and compliance across global markets
Advancements in technology are redefining the audit profession, driving efficiency, transparency, and accuracy in ways previously unimaginable. From the integration of artificial intelligence audit to the adoption of blockchain technology, these innovations are transforming the audit landscape.
Additionally, cloud computing in audits and predictive analytics in audits are playing a crucial role in reshaping audit profession. Together, these advancements enhance the value that auditors deliver to their clients.
At KPMG Switzerland, we are driving digital audit transformation by exploring its potential. We translate this potential into tangible value for our clients.
We invest in cutting-edge technologies and platforms to enhance our audit processes. One example is the KPMG Clara platform, which allows us to seamlessly integrate these innovations. This helps us stay ahead in a rapidly evolving landscape
Big data for audits is transforming the profession by helping auditors identify trends and assess risks, including those due to fraud. This improves accuracy and enhances the auditing process.
Blockchain provides a transparent and tamper-proof record of transactions, making it a game-changer for auditing. It enhances transparency and ensures data integrity, making it invaluable for audits involving nonfinancial disclosures such as environmental, social and governance (ESG) metrics.
The role of blockchain in audits is expanding as auditors use it to verify data at its source. This ensures accuracy before the information is added to shared ledgers. The technology enhances nonfinancial data collection and strengthens trust in ESG reporting. By creating a traceable and immutable record, it helps track key metrics like carbon emissions and supply chain practices.
Smart contracts in auditing can further streamline compliance by automating agreement execution and ensuring that audit conditions are met in real-time. Artificial intelligence in financial reporting complements blockchain by enhancing data analysis and risk detection. Together, these technologies are driving efficiency and deeper insights in audit processes.
Over the years, cloud-based auditing and Application Programming Interfaces (APIs) have improved access to client data. This advancement unlocks the potential for real-time auditing and enhances the efficiency of audit processes. Auditors can now analyze financial transactions and controls more frequently and in real time.
This improves collaboration with clients and ensures seamless data access. This shift from point-in-time to continuous auditing and continuous monitoring enables faster issue detection and resolution. It allows clients to make timely adjustments as needed.
One inspiring example is the use of real-time fraud analytics in a client’s purchase-to-pay process. The system automatically pulls data from SAP and updates PowerBI-based dashboards with 20+ Key Risk Indicators.
As a result, the client can quickly detect potential fraud and monitor compliance with internal purchasing policies. This approach provides ongoing assurance and helps clients address issues proactively.
ML-Powered Predictive Analytics is transforming risk management by enabling auditors to forecast potential risks and make informed decisions. Machine Learning's Role in Risk Assessment lies in its ability to identify patterns within vast amounts of data, providing auditors with actionable insights. By leveraging data analytics in auditing, auditors can detect anomalies, predict emerging risks, and focus on high-priority areas that require scrutiny.
Our collaboration with MindBridge showcases how AI-powered algorithms, including unsupervised machine learning techniques, recognize unusual patterns in client data. These techniques highlight anomalies, helping auditors conduct sharper risk assessments in audits. These tools enhance precision and make the audit process more efficient. They reduce manual errors and allow auditors to focus on complex, judgment-based tasks.
For example, machine learning (ML) enhances risk assessments by analyzing historical trends and making more accurate predictions. This ensures auditors focus on the most critical aspects of the audit process. These practical applications of machine learning (ML) enhance predictive analytics in audits and improve overall efficiency. They enable auditors to deliver deeper, forward-looking insights to clients.
Automation tools are fundamentally reshaping audit workflows by streamlining repetitive tasks and improving overall efficiency. Robotic Process Automation (RPA) enables auditors to automate data extraction, sampling, and general ledger analytics. This frees up time for auditors to focus on judgment-based tasks.
Machine Learning optimizes Audit Automation by identifying patterns, automating anomaly detection, and enhancing fraud detection efforts. KPMG’s partnership with MindBridge demonstrates this in action. The collaboration leverages AI-powered algorithms and machine learning (ML) techniques to analyze transaction data. This helps detect anomalies and deliver precise risk assessments.
By reducing manual intervention, these innovative auditing tools significantly improve the speed and accuracy of audit workflows. This allows auditors to focus on high-value activities.
Emerging technologies are not just theoretical concepts but practical tools driving real-world impact. Case studies demonstrate how innovations like AI, blockchain technology, and predictive analytics are enhancing audit quality and efficiency.
For example, KPMG Clara integrates these technologies to streamline processes, deliver insights, and improve collaboration with clients.
While the benefits of audit technology are immense, its adoption comes with challenges. Data security, the skills gap, and implementation costs are key concerns for both auditors and clients. However, these challenges also present opportunities.
By investing in training and STEM education, the profession can bridge the skills gap and drive innovation. Additionally, advanced tools like RPA and AI streamline operations, improve audit quality, and enhance decision-making. This ultimately delivers greater value to clients.
The future of audit technology is evolving with innovations like smart contracts, API-driven auditing, and process automation in auditing. These technologies enhance efficiency and allow auditors to focus on judgment-intensive tasks.
Machine learning (ML) will be a key driver of audit innovation, revolutionizing the profession by integrating data analytics and automation. ML-powered solutions will enable auditors to predict risks, including those due to fraud, and streamline processes with greater accuracy and speed. These advancements will also support real-time decision-making, aligning with the trend towards real-time auditing.
Would you like to better understand how technology is revolutionizing audits? Talk to us and learn more about AI, Continuous Auditing, Big Data or ESG Assurance. We’re happy to answer your questions.
