Machine Learning
Risk assessment tools with machine learning algorithms can flag additional anomalies or risky transactions based on parameters that it "learns" on its own based on the massive learning data sets provided. Further, it provides insights into a company's processes, possibly in real-time, and flags outliers that might not be caught otherwise.
Blockchain
Blockchain solutions combined with data analytics will help with the transactional level assertions. Confirmation procedures would be less necessary if some or all of the transactions are visible on blockchains. Further, with blockchain, auditors can access information in real-time via read-only nodes on blockchains, allowing instant online assessments. This proposal would mean a profound change in the way that audits work.
Further, while there is clear value in the current audit report, the world is changing rapidly and, within that context, there is growing interest in the role audit will play as a fundamental part of the wider financial reporting ecosystem. Investors and society at large are looking for a new model of the corporate audit, one that drives greater transparency and expands beyond financial statements to provide assurance on non-GAAP, non-financial information, including environmental, social, and corporate governance, culture, ethics, viability, and cybersecurity.
As businesses transform the way they collect and process data, the accounting industry must remain a step ahead. That means continuing to invest in cognitive, machine learning and artificial intelligence capabilities to provide organizations with data-driven business insights as well as evolving reporting and regulatory requirements. Embracing digitization and artificial intelligence for high-quality, highly efficient audits, has paved way for massive disruption in the profession. The future of audit is on the precipice of a colossal change and there’s no stopping it now.
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