Goal-based wealth management (GBWM), also known as goal-based investing [1], is a relatively new class of approaches to wealth management that focus on attaining specific financial objectives (goals). As opposed to more traditional approaches to wealth management, in which the notion of expected profit and loss (PnL) plays a central role, GBWM revolves around maximizing the probability of goal attainment. Common investment goals include saving for college tuition, retirement, or purchasing a home. Recent years have seen an uptick in the popularity of GBWM [2], particularly through the use of target date funds (TDFs). TDFs, also known as life-cycle funds [3] or target-retirement funds, are mutual funds or exchange-traded funds that provide investors with an asset allocation aimed at fulfilling a target (goal) by a specified target date (e.g. a retirement date).

As a firm and individually, we have been actively studying the use of artificial intelligence (AI) in wealth management--and more specifically how investment advice generated through AI is sought out and applied--for the past three years in its many different applications across the industry. In our view, the wealth management industry is built and will continue to evolve around human relationships, clients' personal values and their most meaningful choices. The question is how advancements in AI could help the wealth management industry even more. I believe that AI can improve the advisor-client relationship significantly through the combination of richer information, meaningful service, and superior efficiency. Earlier this year, financial advisors (FAs) shared with us their beliefs around how to effectively use AI for their day-to-day business.

In Asia, the wealth of affluent and mass-affluent customer segments is growing rapidly, bringing about new opportunities and growth prospects for banks and wealth managers alike in the region. But to tap into this opportunity, services providers will need to embrace technology and digital platforms to not only provide customers the services they expect, but also gain in productivity and efficiency, a new report by global consultancy McKinsey says. The report, titled Digital and AI-enabled wealth management: the big potential in Asia and released on February 02, looks at the region's fast growing household wealth and shares how wealth managers can capture this opportunity by embracing data analytics and artificial intelligence (AI) to reduce costs, increase access for their clients and improve customer experience across the entire lifecycle. In 2021, the wealth pool of households with investable assets of US$100,000 to US$1 million in Asia totaled US$2.7 trillion. That sum is projected to soar to US$4.7 trillion by 2026 as incomes continue to rise across the region, the report says.

This article was provided by Broadridge Financial Solutions. In an industry that is historically characterized by legacy technology, wealth management firms in Canada and around the world now have access to a growing array of sophisticated technology solutions that harness the power of data analytics, artificial intelligence (AI) and machine learning (ML). As investors increasingly demand a high-touch, digital-first experience amid unprecedented market volatility, these technology capabilities are opening up new growth opportunities for wealth managers enabling them to provide advice and content at the right time via the right channels. The benefits of these new technologies kick in for investors and advisors alike even before a client becomes a client. Wealth managers can use data analytics and other technologies to gain insights into the habits and preferences of prospective clients in order to ensure that they are paired with clients are most closely aligned with their approach and values.

For best-in-class artificial intelligence solutions to actually earn that designation, Sindhu Joseph warns that the tools can't be used as "set it and forget it." Joseph, the co-founder and CEO of CogniCor, a California-based developer of an AI-powered business automation platform, reminded those attending her panel on day two of the inaugural Future Proof festival of the massive failure that was Microsoft's Tay. In spring 2016, the AI chatbot, named as an acronym for "thinking about you," was launched and pulled within a day of operation. Its machine-learning capabilities had caused it to spew racist, misogynistic and anti-semitic statements across Twitter, in a spectacular public display of garbage in, garbage out. Just "letting the machine run" without proper human guidance or care is a huge pitfall, said Joseph, who holds a PhD in artificial intelligence and is the inventor of six patents related to the technology. "There's a lot of applications where that works really well.

The financial services industry is buried in paperwork, and the NLP use-cases in banking and insurance grow every year. For the last three years, we've closely followed the application space of AI-based search applications. These applications tend to be broad, and can hypothetically handle nearly any text-related data format, and could hypothetically be used to address nearly any document or data-related use workflow. Over the last 18 months we've interviewed and directly analyzed 15 AI-based search vendors selling into the retail banking sector, including startups like Expert.ai, Our goal was to gain more clarity on how these broad search applications are actually used in practice, and what actual business problems they are addressing.

Advisors are using artificial intelligence to expand access to wealth management insights. Traditional financial plans often required multiple meetings between advisors and clients with frameworks left to stagnate outside the meetings, but the inclusion of AI has allowed that conversation to become continuous, Sam Palmer, managing director and head of strategy, digital wealth planning & advice for JPMorgan Wealth Management, said during a panel discussion at Financial Planning's INVEST conference in June. "What has started with clients having to interact with an advisor, even to be able to trade stocks moving over through access to digital tools and automation, is [now] more tools in the hands of consumers for financial planning and financial health," Palmer said. "We are able now to have continuous monitoring as an individual [and] as a consumer of my cash flow." This eliminates the need for simple one-off conversations with an advisor.

The wealth management business has traditionally been late to adopt new technology, primarily because of caution about security. It took nearly a decade for firms to trust putting data in the cloud. Today, many other industries are leveraging artificial intelligence (AI) to improve processes. The wealth management industry is still using processes that are tedious and manual. But that is about to change.

Given Artificial Intelligence (AI) is widely used across many industries, how does it apply to wealth management? More importantly, is there a common definition of AI for financial services? In speaking with various professionals in the industry, it is clear that most firms employ some version of AI but struggle to define it. With that being said, many are using AI capabilities that have proven to be useful to the advisor-client relationship and overall portfolio performance. AI can help professionals in financial services recognize patterns, apply defined rules, and make better-informed decisions in both operations and relationship management. While AI certainly plays an important back-office role and can improve logistics, we are nowhere near the days of AI completely replacing the role of an advisor.

Over the past year, capital markets firms were understandably hyper-focused on stabilizing client relationships, guaranteeing employee safety, and keeping operations going during the economic uncertainty COVID-19 brought. Efficiency and caution ruled the day. But now we're seeing the pendulum increasingly swing in another direction as firms think about how to accelerate growth again. If the pandemic taught the wealth industry anything, it's how crucial digital technologies are. Wealth management firms are diving into creating a better client and advisor experience using new capabilities powered by data and artificial intelligence (AI).