Artificial Intelligence

AI Applications in Accounting

NLP, RPA, Fraud Detection, Tax Analytics, and Continuous Auditing for Accountants

3 CPD credits on completion
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Certificate on completion
Downloadable resources
Self-paced learning

About This Course

Course Information

This course explores practical applications of artificial intelligence in accounting and finance. Our experts discuss how AI techniques such as machine learning, natural language processing and robotic process automation can be applied to enhance or automate tasks like financial reporting, auditing, tax compliance and fraud detection. Learn strategies for identifying high-value use cases for AI in your organisation and the key steps to implement accounting-focused AI solutions successfully.

Certificate on Completion

This course is made up of videos, questions and additional reading materials and accounts for 3 units of CPD . One unit is the equivalent of one hour of learning. A certificate will be issued once you have completed all 3 units. Each unit represents one hour of learning.

Course Sections

This CPD course is made up of the following sections:

  • AI Applications in Accounting (Multiple Videos)
  • Quizzes and short assessments (Quiz)
  • Additional reading materials on AI Applications in Accounting
  • Course completion survey
  • CPD Certificate issued once the course is completed

What You Will Learn

  • Explain how named entity recognition (NER) extracts structured data from unstructured text using dictionary-based, machine learning, and hybrid approaches
  • Describe how robotic process automation (RPA) functions through its three stages: training via screen capture, attended or unattended operation, and orchestration of multiple bots
  • Identify how NLP and ML enable continuous real-time monitoring of transactions, expenses, controls, and policies within an entity's information system
  • Evaluate the role of AI in tax compliance, including automated tax return preparation, expense classification as allowable or disallowed, and reconciliation of accounting and taxable profits
  • Distinguish between supervised and unsupervised ML models used in fraud detection, including their application to wire transfers, expense claims, and payroll monitoring
  • Assess the risks introduced by AI automation, including adversarial attacks, false positives and negatives, data quality issues, and bias in training datasets
  • Describe how a 51% attack on blockchain systems enables double spending and why computational power concentration threatens distributed ledger security

Who This Course Is For

  • Accountants and auditors looking to understand how NLP, RPA, and ML apply to financial reporting, auditing, and tax compliance tasks
  • Finance professionals responsible for internal controls who want to learn how AI enables continuous real-time monitoring
  • Tax practitioners interested in automating return preparation, expense classification, and compliance using AI tools
  • Audit professionals exploring how AI changes sampling, evidence verification, and fraud detection in practice

Prerequisites

  • Working knowledge of financial reporting, auditing, and tax compliance processes
  • No prior AI or programming experience is required; the course focuses on practical applications rather than technical implementation

Frequently Asked Questions

Course Details

CPD Credits3
CertificateYes

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CPD certificate on completion
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