Internal Audit with Data Analytics
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The document discusses the evolving role of internal audit (IA) functions from primarily providing assurance on business processes to delivering deeper insights through data analytics. It emphasizes the importance of analytics in risk management, enabling organizations to identify and address risks promptly, and improving the overall internal audit process. The implementation of advanced analytic techniques is seen as essential for meeting the expectations of management and enhancing the value provided by internal audit functions.
Internal Audit with Data Analytics
- 1. -By CA Mitesh Katira Mob : +91 983377556 E-mail:mitesh@apdoshi.com
- 2. • Traditionally, internal audit (IA) functions focused on providing core assurance around business process risk and controls. • But with increasing market volatility and complexity, IA is being asked to deliver insight and value beyond assurance—particularly in the areas of strategy execution, emerging risk, and the rising use of data analytics. • Data Analytic tools plays a vital role in risk assessment and derivation of deeper insights into the organization. Internal Audit
- 3. Risk Management • Provides them with more — and more timely — information that can be used to make decisions and take action to raise and report those risks. • This, in turn, gives management the ability to monitor and mitigate these risks promptly • To execute more timely quantitative and qualitative risk-related decisions. Assess Risk Control Risk Review Control Identify Risk
- 4. Avoid Eliminate / Withdraw Reduce Optimize / Mitigate Share Transfer / Outsource Retent Accept / Budge Risk Management • Risk management is one of the leading areas in which organizations choose to apply analytics. • Analytics provides better “radar” on risk via the application of exploratory and predictive techniques, as well as through the automation of routines that speed up the evaluation of risk. • Helps companies identify and address current and emerging risks more quickly
- 5. What Data Analytics is…? • Analytics is not a technology; it’s a concept. It refers to the use of certain technologies, skill sets, and processes for the exploration, evaluation, and investigation of business operations. • To drive planning, gain insight, and optimize the internal audit lifecycle. • Makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management to drive decision making. • Analytics methodology, analysis tools, performance management, descriptive statistics, exploratory data analysis, confirmatory data analysis, as well as data management. • Provides hindsight, insight, and foresight.
- 6. Why Data Analytics …? • Traditional internal audit methodologies have served their purpose well for decades. • However, as the business landscape for most organizations becomes increasingly complex and fast paced, there is a movement toward leveraging advanced business analytic techniques to refine the focus on risk and derive deeper insights into the organization. • Leading Internal Audit functions are embracing recent enhancements in data mining technology and data visualization tools to deliver results more dynamically in response to risk, dive deeper into organizational data, and deliver profound fact- based insights. • Business analytics holds incredible promise to enhance the internal audit process. • Key to delivering on this promise is asking the right questions, embedding analytics into the culture of the Internal Audit function, and aligning the analytics implementation with the planning process and overall organizational operational and strategic objectives.
- 7. Optimization Predictive Modeling/Forecasting Randomized Testing Statistical Analysis “What’s the best that can happen?” “What will happen next?” “What happens if we try this?” “Why is this happening?” “What actions are needed?” “What exactly is the problem?” “How many, how often, where?” “Why did it happen?” Alerts Query/Drill down Ad-hoc reports Standard reports Predictive and Prescriptive Analysis (the “so what”) Descriptive Analysis (the “what”) DegreeofIntelligence The Value of Information
- 8. Perhaps one of the best challenges that the internal audit process faces today is the expectation of the C-suite and Audit Committee, that Internal Audit should support the business by delivering deeper insight and greater value more efficiently and effectively. Some of the challenging expectations of Internal Audit include: • Being more efficient and achieving more with less • More effectively identifying and responding to risk • Delivering more robust and effective analysis of key issues • Providing more meaningful actionable insights • Driving Change within the business The Solution to these challenges lies in the application of analytic techiques to the Internal Audit Process. Indeed, we believe that analytics will be transformational for Internal Audit The Value of Information
- 9. • No or Limited capabilities •Ad-hoc Activities resulting in unpredictable performance • Success is based on individual competence and not on repeatable processes A Maturity Model for Audit Analysis • The Organization Exhibits a basic set of capabilities • Processes are rudimentary and loosely woven • Success is repeatable with similar application and scope, but not consistent across organization • Capabilities are Developed and adopted consistently • Capabilities are used to drive some audit activities • Management defines goals and objectives for standardized processes and confirms they are communicated • Capabilities are Developed and adopted consistently • Capabilities are used to drive some audit activities • Management defines goals and objectives for standardized processes and confirms they are communicated • Capabilities are well defined and institutionalized • The Department has differentiated itself based on its capabilities • Continuous improvement methodologies are used to adapt to future changes Efficiency,Insight
- 10. Case Studies