Successful Audit Data Analytics For Managers Agenda

Seminar: ID# 1005031

Agenda

• Challenges with traditional audit process
• Industry benchmarks/guidance
• Success stories and common benefits
• Using pilot projects to demonstrate value
• Developing the case for investing in audit analytics

• Which software tools belong in your toolbox and when?
• Do your policies and practices support sustainability?
• Are you developing analytics for the audit, or developing analytics that support your future and assist the audit?
• What role does everyone play in the analytic process?

• Approaches for integrating analytics across the entire audit process
• Identifying key drivers for pursuing DA
• Developing short- and long-range goals
• Developing a strategic plan for DA implementation

• Obtaining “buy-in” from stakeholders
• Effective negotiation with IT
• Dealing with the “prior audit budget” barrier
• Addressing brainstorming ruts
• Strategies for outsourced and cloud-based processes

• Planning the optimal skill mix
• Organizing the team
• Working with internal and external partners
• Developing and maintaining data analytics skills
• Staffing and workforce planning
• Performance management
• Enabling creativity

• Scanning for opportunities to automate
• Generating and prioritizing analytic ideas
• Profiling business data for data quality assessment and process understanding
• Data analysis for learning as well as detection
• Prototyping business rules for 1st and 2nd lines of defense
• Choosing between ad hoc, repetitive and continuous methods

• Market landscape of major audit analytics technologies
• Considerations when choosing analytic software
• Multi-year technology roadmap and licensing plan
• Integrating the technology “eco-system” for increased value DA Program Governance

• Strategy and implementation planning
• Data governance: the right data at the right time in the right format
• Prioritizing the analytics portfolio
• Developing KPIs and measuring program performance
• Policies, procedures and user enablement

• Management’s role in analytic development process
• Analytic planning and design
• Data access and validation
• Coding and script development
• Testing/quality assurance (QA)
• Implementation and optimization
• Process differences for ad-hoc vs. continuous testing

• Maturity models and benchmarking
• Leveraging available resources
• Tactical planning to ascend maturity levels

• Continuous auditing vs continuous monitoring
• Strategy considerations
• Effect on audit process
• Changes to data extraction and analytic logic