Published by Wanda Rich
Posted on July 31, 2024
5 min readLast updated: January 29, 2026
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By Anoop Karumathil Melethil, Vice President – Marketing, Maveric Systems Limited
By Anoop Karumathil Melethil, Vice President – Marketing, Maveric Systems Limited
AI is profoundly reshaping the wealth management industry, driving changes that go far beyond operational efficiencies to encompass customer experience and business transformation. PWC’s 2023 Global Asset and Wealth Management survey, showcases a surge in robo advisory platforms to US$6 trillion by 2027, highlighting this transformation.
AI technologies are increasingly being adopted across front, middle, and back-office functions. However, their most significant impact is seen in the way they enhance advisor-client relationships. Enhanced advisor-client relationships lead to improved retention rates and expanded wallet share. Sweeping changes in unique investment needs, differing risk appetites, and rapidly changing preferences for investment asset classes are driving the accelerated adoption of AI.
Increasingly, we observe a shift in the High Net Worth Individual (HNI) and Ultra High Net Worth Individual (UHNI) segments, which now include younger generation investors who are digital natives and expect timely investment advice through their preferred channels. This necessitates the ability to provide accurate and real-time market insights as applicable in the customer context based on risk profiles and preferences in a true omnichannel way. Towards this, wealth management firms are increasingly reimagining the customer journey, applying relevant AI-led self-service or advisor-supported intervention modes at appropriate places in the investment cycle. In addition, AI-based models provide the ability to sift through tons of information, map it based on customer persona, and personalize it to suit both the channel of delivery as well as relevance. Consequently, wealth management firms are reimagining the customer journey by applying relevant AI-led self-service or advisor-supported decision models at critical investment cycle points. Additionally, AI-based models facilitate the sifting through large amounts of information, mapping it to customer personas, and personalizing it for both delivery channels and relevance.
Wealth advisors increasingly use AI to guide clients’ financial outcomes through timely investment nudges and improving the customer experience by adopting gamification strategies, employing useful behavioural interventions, and enhancing mobile experiences. Self-learning, hyper-personalized financial plans are becoming a reality with AI systems.
A key area supported by AI is the self-service platform for investment decisions. From robo-advisory platforms to chatbots assisting in securities trading, AI has taken personalized investment advice to the next level. Examples include IndexGPT from JPMorgan Chase and AIVMAX from HSBC, which help customers manage diversified investment portfolios based on their financial conditions.
AI equips advisors with powerful tools that provide accurate data and insights, allowing for a holistic view of their client’s portfolios and financial circumstances. Maveric Systems’ Digital Transformation in Wealth Management report, outlines a notable initiative – Tifin.AI, launched jointly by FinTech Tifin and JP Morgan. This innovation platform enables FinTech’s to develop AI-powered wealth management solutions, providing portfolio insights to advisers and supporting alternative investments and employee benefits management. Other examples include FMG, an AI-powered content personalization engine that assists advisers with writing blogs and social media posts; Hearsay Systems, which summarises content; and Catchlight, a prospecting solution that enables advisers to send auto-generated and personalized emails to prospects and new clients.
As the number of digital-native investors grows, there is an increasing demand for digitally savvy advisors. High-quality conversations between advisors and clients hinge on the availability of dashboards, real-time market insights, and quick access to client investment portfolios. A key application of these technologies is to provide next-best-action recommendations generated by analyzing clients’ risk profiles, investment patterns, and up-to-date market data.
While AI can generate valuable insights, conversational AI and NLP platforms are crucial in crafting relevant responses and helping advisors gauge client sentiment to deliver appropriate advice. This capability might also necessitate transitioning from ongoing communication channels like WhatsApp to more immediate, video-based platforms when the urgency of investment advice demands it.
One of the most significant benefits of AI is its ability to free up advisors from time-consuming administrative tasks. AI, ML, and NLP technologies combined with Optical Character Recognition (OCR), have made the automation of client onboarding and other routine tasks easier, thereby reducing the time and errors associated with manual processes. They also drive the optimization of client portfolios at the back end, along with the analysis of the risks associated with them. Furthermore, they can automate back-end trade processing by accurately applying investment rules to client transactions.
Wealth management firms have also been using machine learning models to rebalance investment portfolios in line with real-time market situations with minimal advisor intervention. These models can also predict market volatility and risks in an ongoing manner, calling advisor intervention only when required. In addition, fraud detection systems strengthened by AI help analyze transaction patterns in real time and flag anomalies constantly.
Applying AI across various facets of wealth management has enabled advisors to dedicate more time to client interactions. This increased focus on client relationships strengthens bonds and builds trust. They further help tailor communications and services to individual client preferences, boosting client retention and increasing assets under management (AUM). By anticipating client needs and delivering personalized advice, advisers can nurture loyalty and encourage clients to entrust more of their assets. As AI continues to evolve, its impact on wealth management will deepen, offering new opportunities for innovation and enhancing client satisfaction.
Wealth management is a financial advisory service that combines investment management, financial planning, and other financial services to manage an individual's or family's wealth.
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans, enabling them to perform tasks such as decision-making and problem-solving.
A robo-advisor is an online platform that provides automated, algorithm-driven financial planning services with little to no human supervision, typically at a lower cost than traditional financial advisors.
Client retention refers to the ability of a company to keep its customers over time, often measured by the percentage of clients who continue to use a company's services.
Gamification in finance involves applying game-like elements, such as rewards and challenges, to financial services to enhance user engagement and improve customer experiences.
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