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Successful Audit Data Analytics For Managers Agenda

successful-audit-data-analytics-for-managers
Seminar: ID# 1005031
successful-audit-data-analytics-for-managers

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
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