In finance, AI is being used in accounts payable and invoicing, to extract data and perform quality checks. In corporate reporting, AI can source information from the company’s public statements and facilitate fraud analytics and analysis of balance sheets and performance.
The benefits of AI include:
- Speed and efficiency: AI processing speeds are far beyond human capability, and the technology is available 24/7.
- Continuous improvement: through machine learning, AI learns and improves upon the tasks it has been asked to perform.
- Time savings: AI carries out repetitive and monotonous tasks, freeing up people to focus on activities that require judgment, creativity or deep thought.
AI can also provide valuable insights. It can process, structure and analyze large amounts of data effectively, so it comes into its own when there is too much information for a human to consider on a consistent and thorough basis.
But AI applications also come with risks that companies need to mitigate, involving compliance, technology, data and financial reporting. To help avoid these risks, businesses using AI should ask themselves a number of questions:
- How can we be sure that our AI system is performing as intended and does no harm?
- Does our AI system comply with regulatory requirements?
- What governance or control frameworks are available to assess the sufficiency and effectiveness of our AI system?
- Does our AI system have strong controls over security, availability and data confidentiality?
- Do we have stakeholder engagement across IT, risk and business teams?
By having a clear view of the governance around AI, organizations can maximize the potential of the technology and minimize the risks.
