Three hidden risks in wealth management personalization...and what to do about them
Read time 4 minutes
In this blog post:
- The Big Picture: From cosmetic tailoring to client-centric personalization
- Risk #1: Settling for superficial personalization
- Risk #2: Imposing “big brother” personalization
- Risk #3: Delivering piecemeal personalization
- Building a personalization backbone
From time to time, we’ll share our deeper point-of-view (read: longer blog posts) on jetstream trends in wealth management. These points-of-view pieces are informed by the many conversations our team is having with the c-suite and innovation leaders at large wealth management firms.
In this post, I zoom out to the big picture of personalization in wealth management and how to manage three key risks in the next phase of the grand “advice transformation” journey.
The Big Picture: From Cosmetic Tailoring to Client-Centric Personalization
Zooming out to the big picture, the financial services institutions (FSIs) that “get it” are on a larger transformational arc from product-centric organizations to customer-centric organizations. At a more practical level, that usually shows up as multi-year advice transformation or digital transformation initiatives. We’re just now moving out of the early innings of this game.
The early innings were largely about technologies that brought efficiency to existing processes – both back and front office. Things like digitizing paperwork, automating processes, launching mobile apps, building client portals, and doing some cosmetic tailoring (= superficial customization of client comms, statements, web experiences, etc.) These early stages still weren’t particularly client-centric—they were largely about streamlining and making incremental improvements to existing products and client journeys.
The middle innings we are moving into now are more about deeper personalization and differentiation – they demand a strategic view and c-suite involvement. Data, decision science (machine learning, AI), behavioral economics, human centered design—will all play a prominent role in the middle innings. We believe you’ll start to see more separation here between the incumbent FSIs who truly take a client-centric approach (+ the start-ups that were born that way) and the rest of the pack.
FSIs will face three key risks in pursuing the deeper, more client-centric personalization that is the centerpiece of these middle innings.
Risk #1: Settling for superficial personalization
Many FSIs will aim too low, and end up with a personalization approach that isn’t differentiating. Ultimately, it’s because the data on which they are personalizing isn’t itself differentiated. Most of the time, it will be “found” data—demographic data, transactional data, descriptive data. These kinds of data describe “what”s – what you could observe about clients. All FSIs have access to these kinds of data, whether their own or bought via third parties.
Winning FSIs will push beyond these superficial “what”s to get to “why” data—these kinds of data get at the motivations behind clients’ observable behaviors, and are therefore more powerful as roots of personalization. They help FSIs understand more quickly and precisely everything from product fit to the best path to achieving behavioral alpha with any given client.
Moreover, “why” data are typically not found, but created. They come from observing the decisions clients make across a series of artfully constructed scenarios. Because they are created, they are proprietary and differentiating, and thus more enduring as a source of information advantage.
Risk #2: Imposing “Big Brother” personalization
This risk boils down to client trust – building it, keeping it and deepening it. As soon as FSIs get beyond the cosmetic personalization of the early innings, and into the personalization of products, robo-advice and recommendations that can meaningfully affect client’s financial wellbeing, the trust factor ratchets up exponentially.
The risk is that FSIs pursue an Amazon-like, Big Brother personalization, building recommendation and personalization engines on deep AI. That’s well and good for low risk, transparent products like books, dog food and household goods. But financial products can meaningfully affect customers’ financial wellbeing and are themselves more of a “black box”. To boot, FSIs are typically coming from a place of lower trust than the Amazons of the world.
Therefore, winning FSIs will find ways to build trust by “showing their work” to clients – in other words, spelling out how the insights about the client led to the personalized product recommendation or robo advice. And they’ll need to do this while being respectful of clients’ fleeting attention spans.
The most effective way to show the work and build trust is by giving clients agency in the personalization process. Incorporate interactive experiences for them to show you their underlying preferences through decisions they make, and then tell them how their decisions affected the personalized products, advice, education, and experiences you go on to deliver to them. It’s a posture of partnership, not paternalism.
Risk #3: Delivering piecemeal personalization
Rarely is there a single owner of “personalization” in large FSIs. More commonly, various groups that touch the client journey in different places will deliver their own form of personalization, often based on “what” data. The risk is obvious – piecemeal, unsynced personalization that feels disjointed to the client across their journey with an FSI.
Enlightened FSIs will take a more integrated approach. They’ll look to economic and decision sciences for consumer utility frameworks to underpin and bind together their deeper personalization efforts. Think of it as a personalization backbone, bringing together a root set of “why” data on clients – goal priorities, risk preferences, time preferences, social (ESG) preferences – that builds a holistic picture of what’s important to clients, their motivations and the drivers of their behaviors.
Sidenote: “What” data will still be part of personalization, but it will hang off the “why” backbone and be used to refine personalization efforts.
Moreover, they’ll gather this root “why” data at the household level, ensuring partners (and family members, where applicable) are an integral part of the holistic picture underpinning personalization. Further, they’ll be thoughtful and parsimonious in engaging clients to keep root personalization data current, so that they’re personalizing to who the client is today, rather than who they were a year ago or when they were first onboarded.
Building a personalization backbone
Having a personalization backbone of this holistic “why” data sets up a more insightful and compelling view of a client’s current state, so that a better future state can be created in partnership with the client.
Creating this personalization backbone requires a unique combination of skills and experience. It brings together deep competencies in decision science, behavioral economics and human centered design. Some FSIs may run deep in one, possibly two, of these areas, but rarely all three.
For our part at Capital Preferences, we’re keen to help and swap notes on all things personalization…if our point-of-view strikes a chord, drop me a line at firstname.lastname@example.org.