Continuous auditing and monitoring are processes that use technology to provide real-time assurance and oversight of transactions, controls, and IT systems. Instead of conducting retrospective, periodic audits, CA/CM allows for the automatic extraction and analysis of data as transactions occur. This enables the early identification of irregularities and risks, facilitating proactive risk mitigation and enhancing the accuracy and efficiency of information systems in both private and public sectors.

CA/CM utilises various technologies to achieve its real-time capabilities. This includes data analytics, machine learning, and automated controls. For instance, the project with the City of Burbank used Python for data pre-processing, Microsoft PowerBI for data visualisation and dashboard creation, and Microsoft Power Automate for robotic process automation (RPA) to automate reporting and alerts. The integration of exogenous variables (external data) and generative AI (like GPT technology) is also being explored to enhance predictive capabilities and combine qualitative and quantitative information.

Based on the early development of continuous auditing, the core elements include recorded metrics (measuring system data), standards (benchmarks for comparison, including acceptable variance), and analytics to identify deviations. When recorded metrics exceed the acceptable variance from the standard, an alert is generated. Modern systems also incorporate exogenous variables (external data) to provide broader context and predictive power.

The sources highlight several applications, particularly in government accounting. The project with the City of Burbank focuses on using CA/CM to mitigate risks related to fund balance deficits, overspending against budgets, and errors or irregularities in month-end and year-end balances, ultimately reducing the risk of misstatement in financial reports. Another project with the state of Santa Catarina in Brazil uses CA/CM for procurement monitoring, comparing internal purchase prices with external sources like Amazon to detect potential fraud or significant variances.

Implementing a CA/CM system in government accounting typically involves several steps. First, identifying clear objectives is crucial, as this guides the entire process. Second, data needs to be extracted from the ERP system, ideally automatically. Third, this raw data requires pre-processing (cleaning, transforming, and structuring) into a format suitable for analysis. Fourth, the processed data is loaded into a platform where the CA/CM system is designed. Finally, dashboards, reports, and alerts are designed and automated to provide users with real-time insights and notifications of anomalies or risks.

Implementing CA/CM offers significant benefits, such as providing real-time assurance, allowing for proactive risk mitigation by identifying issues early (e.g., overspending before the year-end), improving efficiency by automating manual testing, and enhancing transparency and accountability. In the public sector, where the objective is often effective service delivery and responsible use of public funds rather than profit, CA/CM can help ensure funds are managed effectively, budgets are adhered to, and financial reporting is accurate and timely.

The integration of generative AI is seen as a significant future direction, allowing for the combination of qualitative and quantitative data to create more sophisticated monitoring capabilities. This could include harnessing information from social media to gauge public perception of service quality (e.g., street cleanliness, infrastructure issues). Future applications in the public sector could involve multi-dimensional reporting beyond traditional financials, including budgetary, infrastructure, service quality, and ESG metrics. However, challenges include ensuring data accessibility (though public sector data is often more readily available than private sector data), adapting standards over time, preventing attempts to manipulate the system (e.g., gaming price alerts), and requiring courageous leadership willing to make findings publicly available.