Finance
5 ways wealth managers can use big data to improve the client experience
Global Banking & Finance Review®
Company
By Ashley Whittaker, President, Global Sales at FundCount
The data wealth managers rely on for day-to-day client decisions, from market and pricing information to portfolio performance and flows, already requires robust infrastructure and compliance measures and can easily strain resources. So, welcoming new data sources into the client experience at wealth management firms is often met with resistance. When considering big data – large, unstructured, and rapidly changing data sets collected from an ever-expanding litany of sources – the handwringing really begins. Big data can be overwhelming for all levels of a wealth management office. Legacy technology often isn’t equipped to handle big data, management may not have clear KPIs to leverage massive data sets, and advisors do not have the time to brainstorm how a new, complex data source may aid their clients.
Yet, most financial professionals recognize that there are competitive advantages to be obtained through an information edge. This is particularly true in wealth management, where empires have been built and lost on the ability (or failure) to correctly interpret the constant stream of data produced in capital markets. To be competitive, the modern wealth manager must wield big data competently. As the quantity of information accelerates, successfully leveraging big data means wealth managers must stay focused on the end goal, meeting complexity with simplicity and focus. In this article, we will direct our attention to the client, with five specific areas where wealth managers can use big data for a better client experience.
Performance conversations with clients are a crucial test of a wealth manager’s ability to relate to their customers, educate clients about the market and financial planning, and demonstrate the advisor’s value. This is usually a positive interaction when the markets are up. Contextualizing the performance of a client’s portfolio that has lagged the market, though, is never easy. Big data can help in this key interaction.
Data aggregation can provide the advisor with a greater understanding of a client’s financial situation, investment goals, risk tolerances, and preferences to prepare for performance conversations. Moreover, big data allows deeper explanations of the portfolio’s performance characteristics, which can help develop trust during turbulent markets that leave clients shaken. Big data allows for more accurate benchmarking based on a client’s asset allocation and security selection. Often, seeing performance compared to the right benchmark can help clients feel that their performance is aligned with their strategy and expectations, even during greater periods of volatility.
Investors, particularly high-net-worth clients, are becoming more sophisticated and demanding increasingly customized portfolios. However, attempting to invest a client’s portfolio based on individual needs doesn’t always lead to a truly custom-tailored portfolio. A wealth manager’s limited data, biases, and unique processes can make portfolios start to look similar, sometimes unintentionally.
Customizing portfolios is an ongoing process, and big data can help. Leveraging large data sets can aid wealth managers when they analyze client preferences for better initial asset allocation decisions. Then, when making security selections, robust investment screens can allow wealth managers to expand and dissect a larger investable universe. A fixed income portfolio, for instance, can be tailored more specifically to a client’s duration and credit quality preferences when a larger volume of bonds is available for selection. Big data also allows for better tools to ensure the portfolio remains customized and uncorrelated to other portfolios or indexes over time.
Articulating a wealth manager’s investment process is much easier with the data to back it up. Big data can help uncover inefficiencies in a firm’s investment management, such as the order entry and trade execution process. It can help aggregate portfolio performance data and provide the basis to analyze firm-wide performance against key benchmarks while identifying performance outliers. Big data can also provide better opportunities for tax-loss harvesting. The client experience improves when wealth managers create efficient and consistent investment processes to deliver optimal performance using big data.
Reacting to adverse market events often requires quick decision-making among multiple specialties. Having limited information for those decisions increases risks. Big data can help fill information gaps in real time, and even provide earlier warnings as market events begin to unfold. The benefits of risk management extend to compliance monitoring, where big data can help create more effective risk controls with less manual analysis required.
Building a data-centric operational foundation focused on the customer experience can benefit from the use of big data. Information about customer trends, prospect behaviors, and sales interactions can point to specific areas that firms can improve, and big data can help firms calculate the ROI of such improvements. Beginning with client acquisition, onboarding, and KYC processing, aggregated data can aid in creating an efficient operation with as little disruption for the client as possible. Big data can identify areas of improvement in ongoing client touch points (such as web and office support), asset movement and transfers, and monthly or quarterly reporting, helping wealth managers map out a seamless customer journey that leads to sticky assets and future referrals.
Before wealth managers integrate AI and big data into their work, they must ensure their existing capabilities are sufficient to support this new reality while maintaining a high level of effectiveness and efficiency in the current process. This is especially critical in areas such as reporting, financial control, and operational excellence. At FundCount, we recently conducted a study and found that 80% of financial operators and wealth managers do not measure their effectiveness, which puts any new technology implementation at risk. To combat this issue, we created a Family Office KPI tool so wealth managers and their clients have an opportunity to assess their performance and efficiency compared to industry benchmarks and understand where changes must be made to take the next steps to adopt big data.
Big data refers to large, complex data sets that traditional data processing software cannot manage. It is characterized by high volume, velocity, and variety, and is used to uncover patterns, trends, and insights.
Wealth management is a financial advisory service that combines investment management, financial planning, and other financial services to meet the needs of affluent clients.
Risk management involves identifying, assessing, and prioritizing risks followed by coordinated efforts to minimize, monitor, and control the probability or impact of unfortunate events.
Investment management refers to the professional management of various securities and assets to meet specified investment goals for the benefit of investors.
Customer experience encompasses all interactions a customer has with a company, from marketing to sales and customer service, aiming to enhance satisfaction and loyalty.
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