New Report: Changing the Landscape of Customer Experience with Advanced Analytics

Today’s financial consumer enjoys unprecedented information and choice, both in terms of channels and access to third party or crowdsourced opinion. Higher expectations support (and in part reflect) the skepticism that to a large degree defines the Millennial generation. These expectations underscore a fundamental shift in the power balance between the client and wealth manager, one reinforced by regulation such as the US Department of Labor conflict of interest rule

The ascendance of the client should be a call to action for wealth managers. As I discuss in a new report authored with my Celent colleagues Dan Latimore and Karlyn Carnahan, wealth management firms need to operationalize insights from new data sources, and bring servicing models up to date with their more sophisticated understanding of the client.

Campaigns and next best sales approaches that have worked in the past (or at least well enough to encourage firms to invest man hours in their design and execution) must be brought into the digital age. Too often these campaigns are a blunt hammer: they are built to sell product and ignore the evolving needs of the individual client, as well as the multiplicity of digital touch points useful to reach him or her. It is hardly surprising that the client reacts negatively to the presumption inherent in these offers.

Introducing The Cognitive Advisor

Last week I published a report on a topic that has interested me for some time: the application of artificial intelligence (AI) technology to the wealth management business. To date, neither Celent nor its industry peers have written much about this topic, despite clear benefits related to advisor learning and discovery. This lack of commentary, and the industry skepticism that underlines it, reflects successive waves of disappointment around AI, and more recently, competition for research bandwidth from other areas of digital disruption, such as robo advice.

Another inhibition relates to taking on an industry shibboleth. How to reconcile AI or machine intelligence to the hands on, high touch nature of traditional wealth management? This challenge is real but overstated, even when one reaches the $1 million asset level that has defined the high net worth investor. Indeed, the extent to which wealth management is a technology laggard (in general, but also when compared to other financial services verticals) highlights the opportunity for disruption.

In particular, AI offers a means to circumvent the dead weight of restrictions presented by antiquated trust platforms and other legacy tech, a weight which reinforces advisor dependence on spreadsheets and other negative behaviors. As is set out in the report, it is precisely the combination of new behaviors and technologies that can help surmount the finite capabilities of the human advisor.

Central Bank-Issued Digital Currency

I just published a new report titled Central Bank-Issued Digital Currency: Assessing Central Bank Perspectives of DLT and Implications for Fiat Currency and Policy Stimulus.

The future of DLT appears inextricably linked with the future of banking & capital markets and given the significant impact that central banks are having upon finance, the perspectives of this critical constituency warrants careful examination with respect to such a game-changing technology.

On 28 September 2016, the Financial Services Committee met with Federal Reserve Chair Janet Yellen at the Semi-Annual Testimony on the Federal Reserve’s Supervision and Regulation of the Financial System. Yellen informed the committee members that blockchain could have very significant implications for the payments system, and innovation using these technologies could be extremely helpful and bring benefits to society.

This is further evidence of the significant and growing interest of central banks in DLT, but what is much less understood is how such technology could transform the role of central banks and commercial banks. Central bank-issued digital currencies present an opportunity to re-architect the financial system to achieve key central bank objectives. The perceived benefits include a new payments system, granular data on key macroeconomic variables, expansion of the policy stimulus toolkit, and improved prudential regulation.

Central banks themselves seem at an important juncture as they appear to be reaching the limits of their current policies — whether or not they are will only be determined with hindsight. In the meantime, in this report we delve into the mindset of central banks through analysing their extensive back catalogue of research to gain critical insights into the policy framework they may adopt going forward and how advances in technology may increasingly play a part.

This is the second in my current series of three reports on distributed ledger technology:

  • The first report considered DLT with gold (Micro Gold);
  • This report considers integrating DLT with Central Bank-Issued Digital Currency (CBDC);
  • The final report will compare fiat currency, Micro Gold, and cryptocurrencies as competition for payments systems, storing value, and money itself continues to rapidly unfold.

Guidance, not advice

Last week Merrill Lynch announced the launch of its long awaited Guided Investing robo advisory platform. Investors get access to a fully automated managed account for only $5,000, compared to the $20,000 required for call center driven Merrill Edge.

A new type of hybrid model

It’s interesting that Merrill Lynch would launch another managed account platform at this point, given the narrow gap between the two program minimums. But industry wide fee compression underscores the importance of cost savings, and with Merrill Edge’s best growth behind it, even a call center is expensive compared to a digital first approach.

I say “digital first” because Guided Investing clients can still get access to a human advisor. In this case, however, the advisor delivers (in the words of a Merrill spokesman) “guidance” and “education”, and not investment advice. Advisors are able to explain product choice as well as why and how a portfolio is rebalanced, for example. Such capabilities reinforce the Merrill message that its portfolio models are not just algo driven, but managed by the CIO.

Compliance friendly

The compliance friendly terms “guidance” and “education” give another clue to Merrill’s intentions. Like BlackRock and other asset managers discussed in my previous post, Merrill wants to get ahead of the DoL rule and fill the advice gap that will be left by the rollout of a uniform fiduciary standard across both the qualified (retirement) and taxable investment spaces. It’s worth pointing out that Merrill announced its decision to stop selling commission based IRA accounts the same week it launched Guided Investing.

Compliance and economics are powerful (and mutually reinforcing) motivations. Especially when the economics are not just about cost savings, but about the chance to develop a whole new client segment. Guided Investing represents not just another robo platform, in short, but an effort to lower delivery costs and fill out the range of options Merrill offers clients, particularly younger and self-directed ones.

Merrill believes (correctly, in my view) that this type of managed investment solution will be as ubiquitous as mutual funds within five years, and so it has no choice but to move forward. Vanguard finds itself at the same crossroads, which is why the firm’s plan to launch a fully automated robo platform (as a complement to its $40 billion AUM Personal Advisory Services hybrid program) is probably the industry’s worst kept secret.


Shining light on the thinking at BlackRock

It’s clear that there’s more than a little chutzpah behind BlackRock’s demand for tougher regulatory oversight of robo advisors. This post probes the thinking behind it.

Does BlackRock, with FutureAdvisor in hand, want to shut the door on new robo entrants? A desire to forestall such competition would suggest a level of fear that I do not think exists. (Among other things, the robo narrative has moved past the independent or 1.0 stage). BlackRock’s main concern seems to be that the sloppy hands of existing competitors might result in regulatory sanction on everyone, and so put the hegemony enjoyed by BlackRock and its asset manager competitors at risk.

Neither faster, nor better, nor cheaper

While BlackRock may have paid $150 million for FutureAdvisor, I don’t think the firm believes it owns a better mousetrap. FutureAdvisor may have an innovative glide path feature (which may explain why FutureAdvisor has an older clientele than its robo competitors), but tax loss harvesting, 401(k) advice, “try before you buy” functionality and other core capabilities have become table stakes in robo world. If anything, BlackRock may believe that its proprietary ETFs (characterized by low tracking error and a broad product base, e.g., Japanese fixed income) outshine the plain vanilla offerings of Schwab and Vanguard, although this argument is undercut somewhat by the firm’s recent decision to drop fees.

Asset managers in the catbird seat  

Like the ETF business, robo advisory services have become increasingly commoditized, even as the DoL conflict of interest rule presents a massive tailwind for both. It’s a tricky time for asset managers seeking to shift their offer from manufactured product to advice based solutions.  BlackRock appears to feel it is in the catbird seat, and is perfectly happy to secure its hand and that of its asset manager competitors, all of whom have done well by automating their investments platforms. I’m not saying there’s collusion here, just a noteworthy confluence of interests.  

I’ll talk about the motivations behind the launch of another asset manager-backed robo in my next post.

Coaching the Advisor: Predictive Analytics and NLG

Predictive analytics and natural language generation (NLG) are used throughout the financial services today, but are used less frequently in the case of wealth management. Narrative Science and Yseop are two of the few NLG companies currently selling to wealth managers.  IBM Customer Insight is bringing its cognitive Watson technology to the wealth management industry.  IBM Customer Insight is doing cool things related to behavioral segmentation, encouraging wealth managers to create more robust customer profiles by casting their data net beyond customer income information. More in my blog post here.

There are many use cases for NLG and predictive analytics in wealth management.  For example, predictive analytics can assist with risk management by spotting anomalies in real-time, and therefore, enable advisors to resolve issues faster. NLG can be used to transpose customer data into a short narrative that summarizes a client’s performance.  This narrative could be shared in an email to the client or used by an advisor preparing for an in-person client meeting. 

In my report, Coaching the Advisor: Predictive Analytics and NLG in Wealth Management, I focus on how predictive analytics and NLG solutions can enhance advisor-client relationships, the attributes of competitive analytic solutions, and propose best practices for the modern advisor. I stress the importance of advisors’ establishing genuine connections with their clients in the midst of adopting new analytic tools.

In the next 12 to 18 months, I anticipate wider adoption of these tools in the wealth management industry.

Straddling the Old and the New – Fintech in the Capital Markets

We are sitting at an extraordinary inflection point in the capital markets. The competitive landscape is in flux as competitors find their way through a maze of constraints. The constraints are well known-increasing regulation, rapidly changing market structure, liquidity challenges, and difficult macroeconomic conditions. There is also a feedback loop with the broader economy; many […]Continue reading...

Finally, Behavioral Segmentation for Wealth Management

Yesterday’s IBM Forum for Financial Services showed Watson’s capabilities for wealth management, insurance and banking. The forum coincided with the 2.0 release for Watson’s application in financial services.   The demo session emphasized Watson’s behavioral segmentation capabilities.  The psychographic measures delivered by IBM Customer Insight are impressive.  For example, measures include but are not limited […]Continue reading...

In robo world, B2B = buyer beware

The success of robo advisors in commoditizing the historically manual portfolio management process is proving their Achilles heel, as I noted in my last post. Incumbents have taken over the narrative. Yet the efforts of these incumbents to build, buy and partner with the robos comes with its own risks. Foremost among these is how […]Continue reading...

The Big Bad Robo Halt

Let’s pause. Take a break. No, the big bad robo halt isn’t the Betterment Brexit brouhaha I discussed in the WSJ last week. It relates to the degree to which the hype around robo has dwindled. As detailed in last week’s webinar, robos’ ability to automate previously high touch advisory functions is proving their comeuppance, at […]Continue reading...