AI In Finance

Demystifying AI Governance and Control for Finance - eBook Excerpts | Part 1

Written by Elaine Nowak | Dec 18, 2023 10:54:44 PM

Auditoria has published our latest eBook “Demystifying AI Governance and Control for Finance A Guide to AI Governance.”

In Part 1 of 4 of our social and blog posts, we’ll introduce AI governance, explore misconceptions of AI, and share the imperative of governance for AI adoption.

Introduction to AI Governance for Finance

AI governance is paramount for finance professionals in corporations due to the significant impact of AI on financial decision-making, risk management, and regulatory compliance. Effective governance ensures that AI systems used in finance are transparent, reliable, and operate within ethical and legal boundaries. This is especially critical given the sensitivity of financial data and the potential for AI to influence essential financial outcomes.

Proper governance mitigates risks associated with data privacy, algorithmic biases, and potential financial fraud. It also aids in aligning AI applications with corporate objectives and ethical standards, ensuring that AI-driven decisions are justifiable and accountable.

Moreover, as regulatory bodies increasingly scrutinize AI applications in finance, adherence to robust AI governance helps corporations avoid legal repercussions and maintain their reputation.

In essence, an AI governance framework is a key tool for finance professionals to harness the benefits of AI while safeguarding against its risks, ensuring responsible and sustainable use in the Office of the Chief Financial Officer.

Misconceptions of AI

The movie and TV industry has had a long history of creating robot characters that are brimming with human-like intelligence. Kit from Knight Rider, C-3PO from Star Wars, or Commander Data from Star Trek are just a few examples of benign, helpful technology machines designed to support humans, capable of incredible feats, and filled with a vast catalog of fast-flowing knowledge. And then we have the killer 4

artificial intelligence that wants to replace and destroy humans, such as Ultron from Marvel, HAL 9000 from a Space Odyssey, or the black-clad gunslinger from West World.

On the other hand, we also see AI portrayed as the solution to any problem, capable of creating entire worlds, running a white-clad utopia, or fulfilling humans every wish.

But AI is neither a ”killer robot” nor a “magic lamp” with all the answers. It is not alive.

It is a software application written by humans to mimic human intelligence.

Machines are not sentient beings, and they lack the capacity for self-awareness and emotions. This means that machines do not have the desire to take over the world or any other motive, for that matter.

The truth is that the development of AI is heavily regulated, and its use is subject to strict ethical and legal guidelines. AI is designed to enhance human life, not to replace it or even destroy it. While there may be concerns over the misuse of AI, these are addressed through robust regulations and oversight.

Whatever way Hollywood portrays AI and robots, in the real world there are incredible advantages to using robots and artificial intelligence to help solve some of the challenges that hamper humans at home and work.

The Imperative of Governance for AI Adoption

In exploring the advantages of AI, we need to be sure our AI is reliable, accurate, and explainable. And that is where governance plays a key role.

AI Governance is a system of rules, processes, frameworks, and technological tools employed in an organization to ensure that the use of AI aligns with the organizational principles, legal requirements, as well as social and ethical standards. The central function of AI governance is to ensure the ethical and responsible development and use of AI. In finance, where sensitive data is handled daily, it is even more important.

AI governance should be part of an organization’s governance landscape and intertwine with IT governance, data governance, and general governance. Safe operation of an AI system is delivered when the following is present:

  • Responsible design, development, and deployment practices
  • Clear information to deployers on responsible use of the system
  • Responsible decision-making by deployers and end users
  • Explanations and documentation of data sources, output, and risks

AI Governance Frameworks

To help organizations in their quest for advanced technology, some type of governance framework should be used to ensure ethical and responsible AI use.

There are quite a few frameworks already in existence, and there are also organizations that provide guidance and help for how to best understand and protect companies in their use of AI. A company could even create their own AI framework that is a combination of a few frameworks and methodologies.

Sample Frameworks

Federal AI Community of Practice - Artificial Intelligence Governance Toolkit. This framework addresses privacy and governance at both the organizational and system levels. It provides suggestions for determining the right stakeholders to engage, and the types of privacy questions to ask at each phase of development.

https://coe.gsa.gov/docs/AICoP-AIGovernanceToolkit.pdf

Singapore’s Model AI Governance Framework. The Singapore model, developed to help organizations adopt AI responsibly and effectively, considers AI implementation relative to human beings’ role in its use.

https://www.pdpc.gov.sg/-/media/files/pdpc/pdf-files/ resource-for-organisation/ai/sgmodelaigovframework2. pdf

Organization for Economic Co-Operation and Development (OECD) 2022 Framework. Created for the Classification of AI systems from the OECD Digital Economy Papers.

https://oecd.ai/en/ai-principles

The Artificial Intelligence Governance And Auditing (AIGA) AI Governance Framework. This framework is based on scientific work conducted as an academy-industry collaboration.

https://ai-governance.eu/ ai-governance-framework/

Fill out the form and download your complimentary copy of the Auditoria.AI eBook.

"Demystifying AI Governance and Control for Finance - A Guide to AI Governance"