In asset and wealth management (AWM), the digital transformation wave is reshaping the way financial services are delivered. Traditional manual processes are giving way to innovative solutions powered by artificial intelligence (AI). As client expectations shift towards faster response times and personalized services, AWM firms are under increasing pressure to adapt. Recent research indicates that 65% of Americans believe businesses, especially in the wealth management sector, need to enhance customer experience. However, only 15% and 12% of respondents, respectively, feel their brokerage firms and retirement service providers deliver the best user experience.
This blog explores the top use cases of AI in wealth management, shedding light on how organizations can address challenges and gain a competitive edge in this rapidly changing landscape.
The Rise of Robo-Advisors
AI is playing an important role through the introduction ofrobo-advisors. These AI-powered software solutions collect information from users about their financial situation, investment goals, and risk preferences. Also, they offer tailored recommendations, facilitating the balancing of investment portfolios. Advanced robo-advisors can even automate asset investment with minimal human intervention.
For instance, Betterment, a US-based digital investment company, has successfully implemented robo-advisory services since its start in 2008. With over 700,000 users and assets under management exceeding $32 billion, Betterment exemplifies the growing demand for AI-based investment advisors. Projections suggest that the number of robo-advisor users will reach nearly 478.9 million by 2025, with assets under management climbing to $1.2 trillion by 2024.
Customer Request Processing
Overloaded with tasks, AWM firms can struggle to provide timely responses to customer requests, leading to reduced retention and engagement rates. AI-based chatbots come to the rescue by instantly addressing user inquiries and providing round-the-clock support. These chatbots, unlike humans, don’t tire and can handle multiple requests simultaneously. Studies indicate that conversational technology can reduce customer support expenses by 30% and improve staff productivity by answering up to 80% of routine questions.
Integration of AI-enabled chatbots across various communication channels, including websites, asset management platforms, messaging apps, and emails, ensures a seamless and efficient customer request management process.
Compliance Management
Traditionally, AWM firms grapple with paper-based workflows to ensure compliance with various regulations. AI algorithms step in to monitor real-time changes in requirements, generate reports, and notify professionals about regulatory shifts. For instance, EY developed SARGE, acloud-basedAI system, which uses natural language processing to extract investment guidelines from contracts and correlate them with compliance rules. Implementing AI tools like SARGE can lead to a remarkable reduction in compliance costs, up to nearly 75%.
Personalization
AI is revolutionizing customer experience in wealth management by enabling hyper-personalization. Analyzing vast amounts of data, including user behavior, past activities, and transaction history, AI creates a comprehensive customer view. This allows AWM firms to deliver individualized recommendations related to investment, financial well-being, and asset management. Moreover, AI identifies the most effective forms and frequencies of communication for each customer, enhancing the overall personalized service.
Real-world examples include the development of a mobile investment app by Surf, which offers tailored recommendations based on client needs, optimizing marketing campaigns, increasing lifetime value, and preventing churn.
Tax Planning
AI finds application in tax planning, a critical aspect of wealth management. AI compares tax strategies to identify optimal variants for individual customers. AWM firms leverage this technology to view how different tax plans impact returns. By streamlining tax planning processes, AI not only boosts user engagement but also increases retention rates.
Sentiment Analysis
AI and wealth management come together to provide sentiment analysis, offering valuable insights into investment decisions. Machine learning evaluates customer sentiments about assets and market conditions, enabling financial institutions to forecast investment trends. MarketPsych Analytics, for example, uses machine learning and natural language processing to analyze global financial news and social media, providing sentiment indicators related to joy, fear, anger, and optimism. This information helps AWM firms create investment strategies, forecast volatility, evaluate risks, and offer actionable advice.
Conclusion
The adoption of AI in wealth management is not just a trend; it’s a strategic advantage. As the financial services industry undergoes adigital transformation, AI is proving to be a game-changer, offering benefits such as increased efficiency, cost reduction, and improved customer experience. From robo-advisors streamlining investment portfolio management to AI chatbots enhancing customer request processing, the applications of AI are diverse and impactful.
As we look ahead, the collaboration between artificial intelligence and wealth management is set to reshape the industry further. AWM firms that embrace these technological advancements will not only meet evolving customer expectations but also position themselves as leaders in a dynamic and competitive market. The future of wealth management is intelligent, automated, and tailored to the unique needs of each client
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