The AI transformation in wealth management

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A glimpse into the future

ARTIFICIAL INTELLLIGENCE is no longer a futuristic concept. It’ s poised to reshape how we live, work, and interact. The wealth management industry is no exception, standing at the cusp of a transformative era driven by rapid advancements in AI. A recent Statistics Canada report reveals that approximately 60 percent of Canadians could see their jobs transformed by AI, with those in the financial sector facing particularly high exposure. This underscores the urgency for wealth management professionals not only to understand AI but to also embrace its potential actively . By doing so, they can adapt to the changing landscape, gain a competitive edge, and enhance client service. “AI should not replace financial advisors,” emphasizes Maxime Dumas, principal researcher at the Croesus Lab, a

Croesus provides innovative, high-performance, and secure wealth-management solutions that include portfolio management systems, portfolio rebalancing tools, and application programming interfaces (APIs). These solutions empower wealth-management professionals to improve their productivity, enhance their client relationships, make informed decisions, and maximize the management of their assets under management. Croesus’s mission is to provide a superior experience to its clients, users, partners, and employees and to affect the community positively. With more than 200 employees in its Montreal, Toronto, and Geneva offices, Croesus has won several industry awards for being a high-quality solutions provider and an outstanding employer.

AI’s potential in wealth management

Personalized client experiences

“AI should not replace financial advisors. It should empower them – simplify their work by automating repetitive tasks and freeing them to focus on client relationships and strategic decision-making”

Maxime Dumas, PRINCIPAL RESEARCHER, Croesus

leading research center for innovative financial technologies. “It should empower them, simplify their work by automating repetitive tasks and freeing them to focus on client relationships and strategic decision-making.” To truly grasp AI’s transformative power, we need to move beyond the hype and explore its practical applications in wealth management.

• Hyper-personalized client experiences AI could analyze vast amounts of client data – including financial information, risk tolerance, and even personal preferences – to create highly personalized investment strategies and communication styles. This would enable advisors to tailor their services to each client’s unique needs and goals. • Streamlined portfolio management AI-powered tools could automate tasks like portfolio rebalancing, tax-loss harvesting, and risk management, freeing up advisors to focus on strategic planning and client interactions. This would lead to more efficient and optimized portfolio management.

• Enhanced client insights AI could sift through complex data to uncover hidden patterns and insights, enabling advisors to anticipate client needs and proactively address potential concerns. This would allow for more proactive and insightful client service. • Efficient onboarding and compliance AI could automate client onboarding processes, reducing manual effort and improving data accuracy. It could also assist with compliance tasks, such as transaction monitoring and fraud detection, ensuring regulatory adherence and risk mitigation. Unlike previous technologies that often required specialized skills, generative AI can be readily used thanks to its ability to understand natural language. “Newer AI models can understand and generate natural language with remarkable ease,” says Dumas.

behavior without the associated risks,” explains Dumas. “This enables us to innovate safely, testing models in scenarios that simulate the complexities of real markets.” Finally, the cost associated with developing and maintaining sophisticated AI models can be a significant hurdle. Firms can often gain a considerable advantage by partnering with a technology provider actively developing and implementing its own cutting-edge AI solutions.

“At the Croesus Lab, we’re excited to see where generative AI will lead us,” says Dumas. “Challenges remain, but our focus is on empowering advisors. We’re exploring innovative ways to do this safely and effectively.” The evolution of AI in wealth management is ongoing, with new advancements and applications emerging rapidly. Emerging technologies like quantum computing hold the potential to further transform the industry, enabling even more sophisticated analysis and optimization. “We’re not using quantum computing yet, but we believe it could be the next big thing,” explains Dumas. “The Croesus Lab is collaborating with industry leaders and conducting

proof-of-concept projects to understand the technology and prepare for when quantum computing is ready to deliver practical results.” Dumas believes the future of wealth management is inextricably linked to AI and other emerging technologies. Firms that embrace these advancements while remaining mindful of the challenges and ethical implications will be well-positioned to thrive in this new era of intelligent wealth management.

Unveiling AI’s true potential

The future of wealth management

Published October 7, 2024

“AI excels at understanding and processing information within a given context. Be precise in your requests and provide as much information as possible to ensure the AI understands your needs”

Maxime Dumas, PRINCIPAL RESEARCHER, Croesus

AI complements human expertise by enhancing capabilities, it does not replace it. It is not a substitute for judgment.

Keys to a successful partnership

While AI’s potential is immense, it’s crucial to acknowledge the challenges and ethical considerations associated with its implementation. Addressing these requires a cautious and thoughtful approach. “We need to thoroughly understand these technologies,” says Dumas. “Before bringing AI solutions to market, we must ensure they provide accurate information and avoid any negative consequences for advisors or clients.” One of the key challenges is the issue of bias and accuracy. AI models can inherit biases present in their training data, leading to unfair or discriminatory outcomes. Ensuring AI models provide accurate and contextually relevant information is paramount. Another significant challenge is linked to data security. Developing effective AI requires training on large, high-quality datasets. To address this, the Croesus Lab works on synthetic database generation. Synthetic data enables the development and testing of AI models in environments closely resembling real-world conditions without compromising client data privacy. It also helps mitigate biases present in real-world data, leading to more robust and reliable AI solutions. “Synthetic data allow us to create data that mirrors real-world

The true power of AI in wealth management lies in its ability to complement human expertise. By embracing a collaborative approach, wealth professionals could leverage AI to enhance their capabilities and deliver exceptional client experiences. “AI excels at understanding and processing information within a given context,” Dumas explains. “For example, you can provide a document and ask the AI to summarize or highlight key points. This works effectively because you’re giving the AI all the necessary information. The more context you give the model, the better the results. Be precise in your requests and provide as much information as possible to ensure the AI understands your needs,” he advises. Dumas emphasizes that lack of context is indeed AI’s Achilles’ heel. “AI will likely never replicate the nuanced understanding and empathy of a human advisor,” he explains. "For example, during a financial crisis, it’s crucial to adapt your response to the client’s specific emotional and financial context. We don’t think AI will ever be able to do it the way humans can.” Dumas also highlights the limitations of AI when it comes to answering specific, complex questions, particularly those requiring nuanced judgment or specialized expertise. While AI can efficiently process information and identify patterns, it may struggle with queries that demand deep understanding of financial markets, risk assessment, or individual client circumstances. This reinforces the essential role of human advisors in providing personalized guidance and interpreting information within the broader context of a client’s financial goals and life situation.

Navigating the challenges and ethical considerations

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Streamlined portfolios

Enhanced client insights

Efficient onboarding

Human-AI collaboration

Provide AI with as much information as possible. The more context, the better the results.

Context is key

Clearly define your requests to ensure the AI understands your needs.

Be specific

Break down complex tasks into more manageable steps. This helps AI focus and produce more accurate results.

Guide the model’s thinking

Don’t settle for the first answer. Provide feedback to guide AI toward a better response. The model isn’t bad just because it didn’t answer right the first time.

Refine your results

AI may struggle with nuanced financial questions requiring deep expertise. Rely on your own knowledge and experience for complex client needs.

Complex issues need humans

AI is set to transform various facets of wealth management, with potential applications ranging from client onboarding to portfolio optimization. Here are some key areas ripe for transformation:

Human-AI collaboration: a winning combination

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