A recent study by Capgemini underscores the importance of using generative AI by relationship managers to connect with HNWI customers:
Analyst firm Capgemini has come out with an insightful report on wealth management under its World Report Series 2024, titled ‘Intelligent strategies for winning with the ultra-wealthy: Bridge wealth management and family office strengths to fuel growth’. The report discusses 3 scenarios with respect to the global high net worth individuals (HNWI) – ‘Navigate HNWI wealth recovery during uncertain times’, ‘Leveraging behavioral finance to reconnect with HNWIs’ and ‘Ultra-HNWIs: The most lucrative segment to attract and retain’ – and says the question is who can be the best provider of the one-stop-shop service suite needed to best serve the ultra-wealthy.
ROLE OF BEHAVIORAL FINANCE
Discussing how to leverage behavioral finance to reconnect with HNWIs, the report says wealth management firms can make data-driven decisions that are less susceptible to emotional or cognitive biases by leveraging artificial intelligence, as it helps minimize subjective judgments and enhances the accuracy and consistency of wealth management decisions.
Stating that exceptional client experience (CX) is central to wealth management success, the report says CXOs’ top strategic priority for the next 12 months will be to enhance client experience. Personalization is pivotal to client experience, as HNWIs increasingly demand tailored experiences that meet individual preferences, it adds.
The report says while all wealth management firms do some client profiling, many struggle to use the information effectively. “Underutilization prevents a complete 360-degree client view and limits information optimization. Traditional client profiling, which uses primary data sources such as financial statements and transaction history, is practiced industry-wide. However, the use of behavioral and client lifestyle data that provide a 360-degree and deeper picture of investors’ overall attitudes, beliefs, and perceptions is less common. Typical profiles may encompass basics such as income, assets, and investment preferences but overlook critical factors like lifestyle choices, emotions, biases, and long-term financial goals. A complete psychographic profile, including the psychological factors affecting the client, has to rely on behavioral data collected from alternative sources,” it says.
LACK OF PERSONALIZED ADVICE
The report found that 65% of HNWIs are concerned about the lack of personalized advice tailored to their changing financial situation. In short, they seek guidance, especially during market volatility, to ensure they make thoughtful decisions and do not yield to biases. Real-time communication is crucial in helping clients manage biases that sudden, volatile market movements might trigger, the report says.
The report mentions that a generative AI-driven platform has been found to have boosted a wealth management firm’s productivity by providing advisors with augmented assistance, coaching and useful analytics. “Employee surveys indicate average weekly time savings of up to one and a half hours, which translates to substantial overall efficiency gains,” it says, adding the solution has been found to have enhanced client service by freeing relationship managers from administrative burdens, allowing them more time for client interaction and trust building.
The report also found that 75% of wealth management executives believe that AI will significantly impact the industry in the next 1 to 2 years through algorithms and systems that can perform tasks that typically require human intelligence – learning, problem-solving, and decision-making.
The report discusses about behavioral finance and says it assesses how clients react to market fluctuations, their involvement in decision-making, and their level of investment expertise. This behavioral segmentation approach offers a better decision-making framework by incorporating psychological insights into the financial decision process, it adds.
The report also reiterates that behavioral finance is a tool to strengthen clients’ adherence to their investment strategies, which can reduce deviation from investment plans.
NO HUMAN INTERVENTION
It says while traditional data analysis relies on humans to define rules, AI autonomously discovers patterns without human intervention. Additionally, AI can help diversify and rebalance portfolios by evaluating various investment avenues, automatically identifying low-correlation assets, triggering alerts, and suggesting adjustments to align with investors’ objectives – optimizing returns and mitigating risks.
The report predicts that generative AI will likely move to the forefront of the wealth management model, marking a significant shift in how services are delivered and experienced. The study found that 49% of firms it surveyed use AI in some areas, and 73% of them plan to increase adoption at the enterprise level within the next 1 to 2 years. AI technologies are rapidly evolving as effective tools for enabling and supporting critical business functions; but realizing tangible business value requires a deliberate and structured approach to achieve broad adoption – rather than pursuing limited proofs of concept.
It maintains that integrated data, when ingested, can provide meaningful insights by utilizing AI-based sentimental analysis and predictive analytics to identify patterns and trends in seconds or minutes, and consistently and accurately detect behavioral attitudes.
“Sentiment analysis, also called opinion mining, implies the interpretation of emotions from any text-based source, be it a news article, social media post, personal blog content, etc. Interpretation of emotion is the key to enriching behavioral finance by providing a deeper understanding of the psychological factors that influence investment decisions. AI- based sentiment analysis helps financial professionals understand investors’ feelings behind their investment decisions, and it can classify the customer’s sentiment into broad categories like positive, negative, or neutral. Generative AI models can take the analysis one step further. When firms train generative AI on extensive datasets with labelled sentiment, it can gauge market and investor sentiment toward specific assets, industries, or market conditions, identify market trends, anticipate investor sentiment shifts, and uncover potential market opportunities or risks that merit actionable business insights in real time,” stresses the report.
It then concludes that ingesting all the generative AI-powered analysis with existing CRM platforms will lead to a 360-degree customer view, which completes the understanding of the client from every possible angle, along with predictions that can be further implemented to drive real-time customer profiling and portfolio optimization. Creating a unique view of each client and then sending personalized communication at the right time, reflecting their behavioral attitudes and set biases, will help in achieving a greater degree of client intimacy.
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