68% of financial firms say AI in risk and compliance is a top priority

The allure of artificial intelligence (AI) is undeniable. The financial services industry’s potential to streamline operations, enhance customer experiences, and unlock new revenue streams has sparked a “gold rush” mentality. According to KMPG, 68% of financial services firms say AI in risk management and compliance functions is their top priority. The rapid adoption of AI technology opens up exciting opportunities for chief compliance officers (CCOs) to enhance efficiency, risk management, and decision-making. By conducting a thorough AI assessment, they can confidently harness these advancements while effectively managing and reducing potential risks.

Big opportunities with thoughtful AI adoption

Financial institutions are enthusiastically embracing AI, recognizing its potential to transform risk management and compliance, among other mission-critical functions. By taking a proactive approach to understanding AI’s implications, these institutions can unlock tremendous benefits while minimizing risks such as biases, cybersecurity challenges, and regulatory concerns. Thoughtful adoption positions financial institutions to lead with confidence in this evolving landscape.

However, many firms are not properly evaluating the potential risks behind their AI implementations. Investment Adviser Association’s 2024 Investment Management Compliance Testing Survey underscores this concern:

• More than 38% of firms have no formal approach to evaluating when and how AI tools and Large Language Models (LLMs) may be used.
• More than 64% have not taken any action in response to the SEC’s AI-related examination sweeps.
• Nearly 38% of firms have not tested or validated the quality of the output of their AI tools or predictive analytic models.

This premature adoption can have far-reaching consequences. AI systems are only as good as the data that trains them. Biased data can lead to discriminatory outcomes, such as lending algorithms that unfairly disadvantage certain groups. Additionally, the complex nature of AI models can make it difficult to understand how decisions are reached, raising concerns about transparency and accountability.

AI systems are only as good as the data that trains them

Maximizing success with AI use assessment and strategic vendor selection

When integrating AI into financial services, a comprehensive understanding of data, systems, and vendor partnerships can unlock significant advantages while minimizing risks. By thoughtfully assessing AI use and selecting the right vendors, financial institutions can optimize their operations, enhance compliance, and drive innovation. Key considerations include:

• Strategic data usage: Careful evaluation of data sources, accuracy, and relevance is essential for maximizing AI’s potential. By understanding how data will be used—whether analyzing customer data or cross-referencing documents—institutions can make unbiased, well-informed decisions that enhance outcomes and foster trust.
• Enhancing data accuracy, privacy, and security: Enhancing data accuracy helps generate reliable insights and sound decisions. Prioritizing customer privacy and implementing robust cybersecurity measures can safeguard against data breaches and regulatory violations, supporting the responsible use of AI in financial services.
• Strengthening policies and procedures: Updating and aligning current policies and procedures helps institutions effectively govern new technologies. Well-crafted policies can mitigate compliance and regulatory risks, and help firms stay ahead in a dynamic regulatory environment.
• Understanding system approaches: Whether using open-loop (public data) or closed-loop (internal data) AI systems, firms can benefit from recognizing the strengths and limitations of each approach. This awareness is essential for reducing vulnerabilities and biases, and promotes more balanced and reliable AI outcomes.
• Securing AI systems: Implementing AI with robust security protocols can protect against unauthorized access and manipulation. This proactive approach can help financial institutions maintain a secure environment, enhancing resilience and confidence in AI adoption.
• Smart vendor selection: Partnering with a reliable compliance vendor is crucial to sustainable and ethical AI implementation. A thorough evaluation process enables vendors to bring reliable data and proven expertise to help identify and mitigate risks before they become critical issues–in turn, safeguarding the firm’s reputation, enabling regulatory compliance, and fostering client and stakeholder trust.

Choosing a trusted vendor with a proven data source and robust risk management framework can help identify and mitigate risks before they become critical issues.

Navigating the AI regulatory waters

Governments and regulatory bodies are starting to implement frameworks and guidelines to address the risks associated with the use of AI in financial services, as well as transparency, accountability, and fairness. Compliance with these regulations is crucial to mitigate financial and reputational risks. Some noteworthy regulatory requirements include:

• The UK’s AI Safety Summit: The United Kingdom has been at the forefront of AI regulation, hosting the AI Safety Summit to address the risks and challenges posed by AI. Financial institutions operating in the UK must ”affirm that, for the good of all, AI should be designed, developed, deployed, and used, in a manner that is safe, in such a way as to be human-centric, trustworthy and responsible.”
• The Biden Administration’s AI Executive Order and state laws: In the United States, the Biden Administration has issued an AI Executive Order, highlighting the need for responsible AI development. Additionally, several states are proposing laws to address AI risk management, which financial institutions must monitor and comply with.
• The EU AI Act: The European Union has introduced the EU AI Act to regulate high-risk AI systems. Financial institutions operating within the EU must make a concerted effort to “understand whether they might have any legal obligations under the EU AI Act or whether they may implement the Act solely to make their business stand out as more trustworthy.”

Fortifying AI strategies through compliance best practices

As AI adoption accelerates, financial institutions must prioritize responsible implementation. This requires a deep understanding of how AI systems work, the data they rely on, and the potential consequences of errors or biases.

Compliance professionals play a critical role in fortifying AI strategies and sustaining responsible AI implementation. This includes conducting comprehensive risk assessments, evaluating data sources and purposes, and regularly auditing and testing AI systems. By embracing these best practices, financial institutions can harness the power of AI to drive positive outcomes, comply with regulations, and build a strong foundation for the future.

Finding the right balance

The future of finance depends on striking a balance between innovation and responsibility. By prioritizing responsible AI implementation with the right strategy and policies, CCOs can help their organizations gain operational efficiencies any myriad other benefits of AI while also building customer trust and protecting their reputation. Need help navigating regulatory complexity? Learn how confluence can help.