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Driving business impact in wealth management leveraging AI

Published: September 22, 2021

Driving business impact in wealth management leveraging AI

The wealth management industry is forced to undergo a massive transformation as financial advisers are directly affected by new norms due to the COVID-19 situation. Asset managers need to switch affiliation towards digital strategies to ensure their customers are satisfied during and post-crisis. Wealth management organizations are heavily focused on data transformation and data-driven insights. With the current advancement of technologies, anything which emits a digital signal has become an asset for data science. The exponential growth of data platforms and AI-based decisioning help investment firms quickly and efficiently spot patterns to support data-backed decisions. All pieces of information, including research notes, stories,  news, chats, social media, and third-party data, need to be overlaid with structured first-party information to provide richer reports and insights.

According to Gartner, “Two-thirds of wealth management leaders say that the industry is likely to look very different in three years compared to today… however, only 40% say that their firms are prepared to make the necessary and meaningful changes required for future success.”

Large scale disruptions in the wealth management industry are due to the:

  • Exponential global growth in the mass affluent and high net worth (HNW) segments
  • Increased global nature of wealth and investment opportunities
  • Intergenerational wealth transfer of older generations transferring their wealth to their heirs
  • Change in investment influences where younger heirs are getting influenced by the digital era and have different investment philosophies
  • Likely shift for younger heirs to use  inherited wealth to firms that provide services aligned with their expectations
  • Evolving preference of the customer shifting towards passive investing
  • Mandatory focus on cybersecurity in the digital age
  • Need for virtual financial advisors in the “new normal.”
  • Changing makeup of the ultra-high net worth (UHNW) class 
    • Now more billionaires are in Asia than in the U.S., but U.S. billionaires still hold more wealth which may change.
  • Saturated product categories and unoptimized product-channel mix

Although wealth management firms acknowledge the reality of these challenges, they have been conservative with digital transformation for multiple reasons. The pandemic has triggered institutions to pursue growth and better client services by leveraging data analytics. Wealth management firms can address all of the above by strengthening their current data platforms and enabling them to support smarter insights, smarter interfaces, and smarter interactions.

Smarter insights

The key to rich engagement and experience is a deep understanding of the customer. Firms are flooded with unprecedented volumes of data from every possible way. It’s essential to harness the raw data and turn it into insights. A powerful insights engine provides data science and AI-based extreme personalization to power compelling interactions and inference-driven contextual navigation. As the impact of the digital era modernizes a new generation of customers, the art of social listening has proven its power in data harvesting for many social media and networking channels. The third-party data harvested by these channels have been treasured for providing greater insights. Wealth advisors should be empowered with the art of “self-rewiring” tools and utilities that adjust to different market situations and adjust offerings and service models as per the investor’s needs. 

The wealth management industry is consistently behind the curve in leveraging technology at its forefront, as most of them have their own algorithmic analytics to support their investment decisions.  With leading wealth management firms investing heavily in advanced analytics and data management, there are multiple products that provide out-of-the-box insights around product penetration, client segments, and advisor books. Many customers prefer to leverage firms that have revolutionized their customer emerging technologies and revolutionized data growth with real-time data growth. 

As a first step, wealth management firms can develop more descriptive and predictive analytics that combine internal data across the institution., retail, consumer, digital, and marketing. Once the model has been developed and starts providing better insights, then firms can overlap it with external datasets to create a completely new insightful dataset; By combing the power of both external and internal data, there are multiple insights-driven across customer span, including:

  • Social listening
  • Sentiment analysis
  • Hyper-segmentation
  • Dynamic pricing engine
  • Product recommendation 
  • Churn analysis
  • Customer lifetime value (CLTV)

Smarter interactions

Next-gen customers prefer to have an engagement layer that ties together the various facets of customer interaction to deliver a personalized, highly interactive experience of on-demand, contextual, and conversational engagement. 

The role of data and insights has changed the nature and delivery of financial advice in a significant way. For example, industries like tax preparation and trading have moved from human advisors to AI advisors, which heavily depend on historical data and market factors. We’re also seeing a rush to “Robo Advisory” firms that completely rely on data to provide customized investment strategies. 

The market is consistently evolving, with many FinTech players moving it the extra mile by providing goal-based advice, business succession planning, and other client identifiers. Millennials prefer firms with a balanced view of their customers’ desired offerings and the feasibility to enable them by augmenting the desired solution using proprietary technology. 

To compete with robo-advisor driven FinTech’s, wealth management firms would need to enable their customers with self-service options like:

  • A seamless bot interface
  • Actionable notifications and calls to action
  • Transactions analytics 
  • Analytics on responses and interests

Smarter inference 

Customers prefer personalized landing pages based on insights, including relationships, transaction history, profiling, and suggestions based on similar customers. Data-driven decisioning systems can help wealth management firms understand the client information globally, understand their profitability goals, and help organize options to drive better relationships. As many advisors are slowly adopting new-age tools, including mobile channels and social media platforms, to reach customers, the adoption of human and science-based advice is growing among the younger generation.  

The smarter navigation contextualized based on the current interaction, including mood, tone, and context, and overlaying relationship insights to navigate to offerings, content, or a human relationship manager  leads to a science-based effective assessment like:

  • Tonal analytics
  • Real-time sentiment analysis
  • Digital Experience Hub

These assessments drive impactful client acquisition and retention and provide better human-grounded client advisory services. 

Reach new-age customers by transforming wealth management with AI

Wealth management is moving into the digital era to meet customer demands. Financial advisors should be empowered with the power of data and advanced analytics to deliver key business insights around client segments, advisor books, product penetration, and training program effectiveness.  Advisors need new intel and more sophisticated methods to personalize and provide new insights to clients, including new ways of engaging new clients, managing existing client relationships, and managing risks. Considering the above, AI/ML is no longer an option, but critical survival needs for wealth management firms. 

While most wealth management firms currently use a fairly simple analytics-based management information system (MIS) and reporting system, the recommendation is that firms develop more descriptive and predictive analytics. These analytics should combine internal and external and structured and unstructured data to create more in-depth and insightful client profiles. This enhanced insight will allow firms to assess existing or potential new clients’ propensity to purchase various products and services, their lifetime value, investment style, and risk tolerance.

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