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Maximize value across wealth customer journey through insights

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The competitive landscape of wealth management industry is evolving very rapidly by a range of forces including an increasingly diversified client base with much higher expectations, hybrid advisory model powered by technology, regulatory change, geopolitical volatility and aggressive fintech with efficient digital business models.

The leading wealth management firms are gearing towards a future-ready enterprise. Some of the key strategic goal includes,

  • Improve customer experience
  • Improve the use of data insights in business decision-making
  • Improve operational efficiency, service reliability, cybersecurity, reduce cost etc.
  • Continue to invest on digital technologies - cloud, data analytics, artificial intelligence etc.
  • Strengthen business partners ecosystem

Wealth firms are embracing hyper personalization in context of client’ life goals and looking forward to offering customizable solution including innovative products such as crypto funds, direct indexing, private equity etc.

For many wealth firms, the top priorities are to harness data, use advanced analytics and generate actionable insights with a real-time understanding of the customer and the business to shape-up integrated business decisions. Firms are rebuilding their tech stacks and embracing advanced analytics to personalized wealth management services. Some of the use cases include,

1) Client onboarding

Client acquisition and onboarding includes client discovery, risk profiling, account opening and onboarding. Firms are using analytics for lead generation and share-of-wallet modeling.

  • Merrill Wealth Management launched Merrill Advisor Match, a research-based, digital platform that connects people seeking financial advice with a Merrill financial advisor who best fits their preferences and needs. Matches are based on several dimensions that are explored through a digital questionnaire, which include personality traits, the client’s approach towards problem solving, to how a prospective client would like to meet and interact with their advisor and how often, preference on how they communicate with their advisor, as well as how decisions about investing and planning are made.
  • LPL Financial has partnered with SmartAsset to offer lead-generation tools to the independent broker/dealer's advisors (Vendor Affinity Program). SmartAsset matches investors with fiduciary financial advisors and advisors can filter potential clients based on preferences like asset levels and geography

2) Personalise and improve quality of investments

Wealth firms offers a wider range of solutions, from the simplest products (equities, mutual funds, exchange traded funds) to complex higher-yielding investments (private markets, venture capital, pre-IPO, and structured products). Advisor must be equipped with analytical tools that help clients make complex investment decisions.

  • Charles Schwab advisors have ability to import their clients' accounts into the analytics engine, allowing them scan funds and portfolios for themes, exposures, and holdings as easily as they use a Google search engine. Advisors can use the semantic search capabilities across their accounts; for example, if a client is concerned about exposure to China, the advisor can enter "exposure to China" and the client funds that have high exposure to that country will rise to the surface.
  • Broadridge launched ESG Analyzer, a web based ESG disclosure and data analytics benchmarking tool that delivers timely, high-quality, cost-effective, transparent data and insights. It offers an intuitive dashboard to view all ESG metrics and compare data with peers and allows to build an impactful ESG strategy.

3) Client engagement

Client engagement and deepening relationships includes personalized research, portfolio management, client segmentation, recommendation engines (next best actions). There are also opportunities to use behavioral analytics to de-bias investment decisions i.e., transform behavioral data into advisor recommendations. Firms are aspiring to personalize customer journeys using data insights across the value chain.

  • UBS introduced a new analytics tool for ultra-wealthy clients in the US with a consolidated and real-time picture of their entire portfolio across various assets and liabilities such as traditional, non-traditional, and illiquid assets.
  • Raymond James launched data-driven actionable insights. The application, named ‘Opportunities,’ is intended to prompt adviser-client communication. The advisers can view opportunities across their entire book of business or focus on specific client relationships or opportunity types.
  • Schwab Advisor Services partnered with DNA Behavior to assist its advisors in reviewing behavioral insights to build better portfolios. Other firms that have used DNA Behavior’s solutions include Raymond James and John Hancock.
  • HSBC U.S. Private Banking selected Addepar, as its consolidated client performance reporting platform. It provides critical tools, such as comprehensive portfolio views and in-depth analytics, to optimize the client experience.
  • Advisor Stream, a provider of marketing and lead generation capabilities to advisors, is using client data and AI (Artificial Intelligence) to power personalized client communications. The platform keeps learning as clients interact and deliver highly personalized content.

4) Flexible pricing model

The wealth managers need to build in flexible pricing models aligned to clients’ needs at every stage of their lives. An increasingly common pricing model is for clients to negotiate a flat fee based on the value of their investments. While embracing new revenue model wealth firm must use data analytics to create new efficiencies and equip advisor with nextgen analytical tools to increase its client base

  • Avaloq, launched a unique data analytics solution for wealth managers to quickly gain transparency on the impact of bespoke pricing for individual clients. It allows firms to evaluate the impact of potential discounts and communicate with clients in a prompt manner to strengthen client relationships and loyalty.

Conclusion

Most wealth management firms have already embarked on a data analytics journey and are at distinct levels of maturity but have not fully realized the potential of data insights. With customers at the core, wealth management firms must evaluate whether the data insight capability allows them to connect with customers with compelling value propositions in a highly personalized manner. Firm must empower the financial advisors with NextGen analytical tools to deliver superior wealth management services to clients and drive business growth.

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This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.

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