Описание
Business Training Audience
Business Owners
Board of Directors
Head and Specialists of the Internal Audit Service
Senior Executives
Head of the IT Department
Head and Specialists of Internal Control
Head and Specialists of Risk Management, Security, and HR
This business training on internal audit and the application of artificial intelligence (AI) in internal audit will help you solve practical problems:
Learn artificial intelligence technologies (AI, ML, NLP) that can be integrated into the internal audit process for automation, risk prediction, and anomaly detection.
Explore the concept of AI-Driven Internal Audit.
Learn to apply basic AI/ML algorithms and tools in auditing.
Understand how AI helps identify risks and anomalies.
Learn to develop a roadmap for implementing AI in your service.
Master AI Governance approaches and digital audit ethics.
Main topics of the business training:
Digitalization and the role of AI in internal audit. Audit
Goal: To understand the transformation of the internal audit function under the influence of digital technologies.
Topics:
Digital Transformation of Auditing: From Manual Analysis to Intelligent Auditing
The Concept of Data-Driven Audit and AI-Driven Audit
The Potential of Artificial Intelligence in Auditing: Data Analysis, Forecasting, and Automation
The Role of the Internal Auditor in a Company’s Digital Ecosystem
International Trends and Examples of AI Implementation in Auditing (PwC, KPMG, Deloitte, EY)
Interactive: Diagnostics of the Digital Maturity of the Internal Audit Function
Fundamentals of Artificial Intelligence and Machine Learning for Auditors
Goal: To gain a basic understanding of the principles and algorithms of AI/ML applicable to auditing.
Topics:
What is artificial intelligence, machine learning, and deep learning?
Types of machine learning: supervised, unsupervised, reinforcement learning
Key algorithms: classification, clustering, regression, anomaly detection
Stages of working with data for ML models
The concept of explainable AI (XAI)
Workshop: Visual example of data analysis and risk clustering
Using AI in key internal audit processes
Goal: Show how AI is integrated into each stage of the audit cycle.
Topics:
Planning Stage: Automatically Identifying High-Risk Areas Based on Data
Audit Stage: Intelligent Analysis of Transactions and Event Logs
Reporting Stage: Generating Audit Conclusions and Texts Using NLP
Monitoring: Continuous Auditing with Elements of Machine Learning
Using Chatbots and Cognitive Agents for Audit Requests
Workshop: Case Study: «AI Model for Detecting Suspicious Transactions»
AI Tools and Technologies for Internal Audit
Goal: To become familiar with practical tools and platforms.
Topics:
Tool Overview: Python (scikit-learn, TensorFlow), Power BI AI, Azure AI, Google AutoML, IBM Watson
AI modules in GRC and ERP systems (SAP, Oracle, 1C)
AI dashboards
Integrating AI with Data Analytics and RPA
Example of using LLM (Large Language Models, ChatGPT) to analyze audit report text
Workshop: Demonstrating the use of Power BI with AI functions for audit analytics
Fraud and risk detection using AI
Goal: Learn to apply AI algorithms for anti-fraud and risk analytics.
Topics:
Fraud Detection Models: Supervised vs. Unsupervised Learning
Anomaly and Behavioral Analytics of Employees and Customers
Predictive Audit Analytics
Cases: Fraud Detection, Payroll Fraud, Expense Fraud, IT Access Risks
Integration of AI and Segregation of Duties (SoD) Control
Workshop: Setting Up an Anomaly Detection Model (Example with Excel or Python)
Implementation and Management of AI in the Internal Audit Department
Goal: Develop a strategy for the implementation and management of AI technologies.
Topics:
Internal Audit Digitalization Strategy and Roadmap
The «AI Governance» Approach — Managing AI Ethics and Risks
Preparing Data, Competencies, and Infrastructure
Training Auditors in New Digital Skills
KPIs and Performance Metrics for AI Projects
Workshop: Developing an AI Implementation Plan in Your Company
The Future of Internal Audit: AI, Automation, and Humans
Goal: To develop a vision for the future digital audit model.
Topics:
Transforming Auditor Roles and New Competencies
AI + RPA + Data Analytics = Smart Audit
Balance Between Automation and Professional Judgment
Ethical Aspects of AI in Auditing
The Role of Internal Audit in Assessing and Reviewing a Company’s AI Systems
Interactive: Discussion: «Can AI Replace an Auditor?»
Duration: 2 days
