Successful Audit Data Analytics For Managers Agenda
Seminar: ID# 1005031
Agenda
The Business Case for Audit Analytics- 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
What You Should Know, and Questions You Should Be Asking- 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?
Visioning Your Potential Use of Audit Analytics- 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
Removing Common Roadblocks- 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
The Human Factor: Managing DA Talent- 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
Change Management: Adapting the Audit Process- 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
Technology Planning for Now and the Future- 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 and Oversight of the Analytic Development Cycle- 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
Advancing Your Program’s Maturity to the Next Level- Maturity models and benchmarking
- Leveraging available resources
- Tactical planning to ascend maturity levels
Evolving to Continuous Assurance- Continuous auditing vs continuous monitoring
- Strategy considerations
- Effect on audit process
- Changes to data extraction and analytic logic