The number of high-net-worth individuals (HNWIs) grew by 5.1 per cent, and their wealth rose by 4.7 per cent globally year-over-year in 2023, according to the World Wealth Report 2024, released by Capgemini, a Paris-based information technology services and consulting company.

In the Asia-Pacific (APAC) region, India recorded a 12.2 per cent growth in HNWIs in 2023, and their wealth was up by 12.4 per cent. The report covered HNWIs in the Asia-Pacific, the Middle East, Europe, North America, and Latin America.

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Better macroeconomic factors have helped grow HNWI’s population and wealth. Globally, individuals’ cash holdings reduced from multi-decade highs to normalised 25 per cent. For diversification, investors invested in alternative assets, up from 13 per cent to 15 per cent.

With the growing wealth, the report said, asset allocation shifted from wealth preservation to growth. Two out of three HNWIs are keen to invest in private equity to tap growth. Also, just one per cent of the total UHNWIs globally hold over 34 per cent of their wealth.

Around 78 per cent of UHNWIs believe value-added services are necessary, and some 77 per cent want help from wealth management firms to transfer wealth among generations. The study highlights that artificial intelligence can help provide more personalised advice to their clients.

Biases Impact Decision-Making

Around 65 per cent of the respondents globally said investment biases, such as marriage, divorce, retirement, etc., influence their allocation decisions besides market volatility and geopolitical uncertainties. Biases can result in impulsive decisions, it said.

Six investment biases observed among HNWIs

“Confirmation bias” accounted for 65 per cent of the respondents. It refers to investors seeking information from sources that align with their views.

“Activity bias” had an impact on 47 per cent of the respondents. It refers to grabbing opportunities without much deliberation.

“Disposition effect” refers to a situation when investors don’t want to dispose of a bad asset; some 45 per cent of the respondents have had this bias.

“Risk aversion” refers to investors who are “too conservative” to seize opportunities, which accounted for 39 per cent.

“Anchoring bias” refers to investors who stick to past decisions without re-evaluation, which comprised 34 per cent.

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“Overconfidence” bias is a situation where investors invest based on their predictions, which accounted for 33 per cent.

In the Asia-Pacific region, including India, showed lower biases compared to the global percentage, with only 49 per cent and 41 per cent of HNWIs impacted by “Confirmation” and “Activity” biases, respectively, according to the report.

AI’s Role In Decision-Making Process

Artificial Intelligence (AI) can help investors deal with their biases in four ways.

Financial Planning: According to the study, AI algorithms can analyse data from primary (financial transactions) and alternative sources (social media, etc.), as well as behavioural biases and emotions, to understand investors’ diverse needs and create a holistic profile.

Risk Profiling and Allocating Assets: The report states that AI can help clients’ micro-segmentation based on their preferences and create more precise risk profiles. It will lead to better financial management through informed decisions.

Portfolio Creation: AI can provide deep insights through its advanced algorithms and help create a portfolio by making informed decisions and swift execution. The report said, “AI can help rebalance portfolios by evaluating investment avenues, automatically identifying low-correlation assets, triggering alerts, and suggesting adjustments to align with investors’ objectives.”

Client Communication: AI can help enhance personalised communication, such as real-time alerts of life events and market events, to advise clients during uncertain conditions.

Finally, a tailored, personalised plan can boost client confidence. According to the report, “75 per cent of wealth management executives believe AI will significantly impact the industry in the next one to two years through algorithms and systems that can perform tasks that typically require human intelligence—learning, problem-solving, and decision-making.”