When it comes to implementing AI at wealth and investment firms, the process should be seen as a marathon, not a sprint, urges the author of this article.

Compliance is already a difficult task for wealth management, and the arrival of AI takes the challenge up another notch, but on the other hand, AI may also provide new solutions. To discuss the terrain is Kyrstin Ritsema (pictured below), IACCP, executive director, compliance services, Confluence. The editors are pleased to share these views; the usual editorial disclaimers apply about guest writers’ opinions. Email tom.burroughes@wealthbriefing.com if you wish to respond.


Kyrstin Ritsema

Effective use of AI could soon be seen as a prerequisite for business success. The technology is being heralded for its transformative potential across nearly all industries, especially in financial services where competition is high, and innovation is taking off at a record pace.

For asset managers, this technology boom comes at the perfect time. Having faced significant margin pressure and macroeconomic volatility over the past two years, advances in AI are providing firms with opportunities to improve operational efficiencies as an alternative to cutting costs. Applications for asset managers range from regulatory reporting and reducing labour-intensive tasks such as data analysis, to anti-money laundering and cybersecurity.

One area of particular focus for firms is compliance. Indeed, a recent report from KPMG revealed that 67 per cent of financial services firms say that [incorporating] AI in risk management and compliance functions is their top priority.

But in the race for adoption, there is the potential for risks to be overlooked. While the benefits of the technology are clear, firms must proceed with caution to avoid walking into a risk and compliance nightmare. 

Unlocking the benefits
Many organisations are in an AI frenzy, racing to implement new applications to counteract industry headwinds and steal a competitive advantage over their peers. While the attempt to innovate is commendable, there is a risk that some financial institutions are running before they can walk and leaving themselves vulnerable to a range of possible risks, including biases in decision-making, cybersecurity vulnerabilities, and exposure to regulatory actions. 

According to the Investment Adviser Association’s 2024 Investment Management Compliance Testing Survey, over 38 per cent of firms have no formal approach to evaluating when or how AI tools are being used. Additionally, 64 per cent have not taken any action in response to the SEC’s AI-related examination sweeps. 

The implementation of AI should be seen as a marathon, not a sprint. Premature adoption can have far-reaching consequences, and all outcomes must be carefully considered to avoid potential pitfalls – ensuring the safe, unbiased and transparent use of this emerging tech.

Accuracy
Data is the engine behind AI, making the type of data, and how this data will be used, an important aspect to consider in any AI strategy. Systems are only as good as the data that trains them, and this must be acknowledged to avoid producing flawed insights or decisions. 

Biased or false data can lead to discriminatory outcomes, disadvantaging certain groups and ultimately, hampering business decisions. To avoid this, sources must be understood, and data relevance assessed, helping to alleviate the associated risks. 

Security
Data protection and security strategies must be a top priority. AI unlocks a complex web of security risks and robust strategies are needed to prevent unauthorised access and manipulation. Consumer privacy should come first, so firms should always weigh the risks and benefits of using customer data for AI, supporting the responsible use of AI in financial services.

Governance
When adopting new systems, financial institutions must review their existing policies and procedures to determine their alignment with AI systems. Policies that are outdated or incomplete may fail to effectively regulate AI applications, potentially exposing institutions to compliance and regulatory risks. Well-crafted policies can mitigate compliance risk and help firms manage the ever-changing regulatory landscape. 

Regulation
To support the increased implementation of AI and address the risks, governments and regulatory bodies have begun producing and implementing regulations, frameworks and guidelines. 

All businesses must ensure that they keep abreast of the latest AI regulations within the markets in which they operate to mitigate any financial and reputational risk of non-compliance.

AI best practices
As AI adoption continues to accelerate, financial institutions must emphasise responsible implementation. This demands a comprehensive understanding of how AI systems function, the data they use, and the potential impacts of errors or biases.

Compliance professionals act as a key pillar in responsible and robust AI strategies. Compliance is not a once and done task; risk assessments must be conducted regularly, data sources evaluated routinely, and the auditing and testing of AI systems prioritised. 

Through regular assessment and monitoring, financial institutions can harness the power of AI to produce positive outcomes, comply with regulations and drive forward business success. 

Proceed with care
The successful implementation of AI requires striking a balance between innovation and responsibility. While the desire to move fast can be strong, understanding limitations, adhering to regulations and implementing robust practices are important steps in an organisation’s AI journey. 

A robust AI strategy will weigh up the opportunities and risks effectively, prioritising the responsible use of this powerful technology, building customer trust all while reaping the business benefits of promoting long-term success.