AI Risk Management for Accountants
Bias Detection, Transparency, Data Ethics, Workforce Impact, and AI Governance for Accountants
About This Course
Course Information
This course covers strategies and tools to address risks from artificial intelligence in accounting and finance. Discuss ethical issues such as bias, privacy, job disruption, and governance frameworks to promote responsible AI development and use. Explore methods for detecting and mitigating trust, transparency, and accountability issues as AI becomes more integrated into accounting functions and daily workflows. Learn why risk management and oversight are crucial to realising AI’s benefits.
Certificate on Completion
This course is made up of videos, questions and additional reading materials and accounts for 2 units of CPD. One unit is the equivalent of one hour of learning. A certificate will be issued once you have completed all 2 units. Each unit represents one hour of learning.
Course Sections
This course is made up of the following sections:
- AI Risk Management for Accountants (Multiple Videos and quiz)
- Additional reading materials on AI Risk Management for Accountants
- Course completion survey
- CPD Certificate issued once the course is completed
What You Will Learn
- Identify sources of AI bias in accounting, including how training data can produce skewed outcomes in expense auditing, credit scoring, and financial reporting
- Distinguish between glass box and black box AI models, and explain why regulatory bodies now favour inspectable, explainable decision-making systems
- Describe explainability tools such as LIME, SHAP, and Anthropic's Constitutional AI, and explain how each reveals the features driving an AI model's output
- Evaluate the six data ethics considerations that apply when AI processes financial data: informed consent, original intended purpose, bias and representativeness, transparency, regulatory compliance (including GDPR), and stakeholder impact
- Explain the security threat of model inversion and describe how data protection impact assessments help prevent AI systems from becoming gateways to data breaches
- Assess which accounting roles face higher automation potential (data entry, invoice processing, bank reconciliation) versus those that remain secure (advisory, strategic planning, client consultation)
- Apply governance framework principles from NIST, the FTC, and the EU, including human oversight, transparency reporting, iterative testing, and pilot-based AI adoption in accounting firms
Who This Course Is For
- Accountants and finance professionals who work with or evaluate AI-powered tools for auditing, reporting, or tax planning
- Audit and compliance professionals responsible for assessing AI-related risks in financial systems
- Practice managers and firm leaders planning the adoption of AI tools and needing to establish governance policies
- Accounting professionals looking to understand how AI will change their roles and what skills to develop
Prerequisites
- A working knowledge of core accounting functions such as financial reporting, auditing, and tax planning
- No prior AI or technical background is required; the course explains all AI concepts from first principles
Frequently Asked Questions
Course Details
Pricing
Invest in your professional development with flexible payment options.
Everything included in your subscription:
Ready to Start Learning?
Join thousands of finance professionals who have advanced their careers with Learnsignal CPD courses.
Enrol Now