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 to: openness, liberalism, cautiousness and sympathy.  Knowing all too well that a client’s personality can make them candidates for different products than what a client’s paper profile would suggest, it is easy to see how in the wealth management space, advisors could use these measures to build deeper human connections with their clients. 

I was also impressed by the fact that Watson shows financial advisors the reasoning behind the machine learning results.  Gaining insights into how Watson arrives at its recommendations empowers advisors to validate the results or add human refinement based on inputs not available to Watson.  In this way Watson can complement the financial advisor. 

It seems that there is even more that IBM is working on that is not in this latest release, so I’m looking forward to what more there is to come.

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 to implement robo advice within a multichannel ecosystem. As discussed in the report, Getting the House in Order: Consolidating Investment Platforms in the Wake of the Department of Labor Conflict of Interest Rule, the ability to deliver consistent advice across channels has become paramount in the new regulatory environment.

This consistency requires a clear view of assets held in house, which in turn implies eliminating product stacks and their underlying technology silos. Of the big four US wirehouses, Bank of America Merrill Lynch has led the way by consolidating five platforms into one. Their competitors are still trying to solve the problem.

Regional banks, with their legacy tech and limited budgets, are going to have a hard time getting this right. Asset managers are eager to help them launch robo platforms, despite the “me too” nature of the banks’ efforts. 

It’s hard to blame these asset managers for wanting to distribute their wares. B2B sales are in their DNA. But I’d point out that their headlong rush to abet bank robo contrasts with their cautious efforts to roll out on their own platforms.

Schwab spent months and millions to launch Intelligent Portfolios. UBS has moved much more slowly, and appears to be using SigFig as a placeholder until it can achieve the technological and service clarity demanded by clients and regulators alike. Fidelity danced with Betterment before rolling out Go through its retail branches. It's tepid if not touch and go.   

I don’t begrudge asset managers for taking their time. They have their own considerations, foremost distribution. That’s why they are enabling bank robo capabilities, even if it's not clear exactly how the banks will manage this. Why not give the teenager the keys to the Audi? But with their own clients, they have to get things right. They have shareholders to answer to, and the stakes are much higher.

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 least in startup world. The commoditization of the portfolio management process, from asset allocation to rebalancing to tax loss harvesting, works in favor of the large incumbents, with their advantages of brand and scale.

Meanwhile, product innovation efforts by independents as described in my Robo 3.0 report have gained little traction. While the robo value proposition (centering on transparency, cost, and user experience) broached by first movers Wealthfront and Betterment and others remains very much in play, incumbents have co-opted the vision.

We're not yet at the point of a fire sale, but the price tag for independent robos is shrinking fast. This is a question of deployment as well as value; among other things, it's become apparent that putting into action a store bought robo is not as simple as plug and play. I'll discuss the robo world challenges facing asset managers, banks and other incumbents in my next post.

FinovateFall 2016, NYC: Day 2

Below is a selection of companies, which demonstrated solutions that can be used in the wealth management space. The Best in Show awards went to: 1) AutoGravity, 2) Backbase (mentioned in my blog post yesterday, FinovateFall 2016, NYC: Day 1), 3) Clinc (profiled below), 4) MX, 5) Swych and 6) Trusona

Envestnet│Yodlee:

Envestnet│Yodlee presented their dynamic intelligence solution. Envestnet│Yodlee walked through an example with a fictional user, Amanda, a 29 year old with $85,000 in student debt. Amanda just received a $15,000 signing bonus.  A chatbot alerts Amanda of the new deposit and provides Amanda with three ways to use the cash: 1) pay down her credit card debt, 2) use the money for emergency savings, or 3) pay down her student loans.

Envestnet│Yodlee has data on 22 million customers in 15 countries. As such, Envestnet│Yodlee has looked at data across all of Amanda’s financial institutions and has data that shows Amanda has stopped contributing to her prior’s employer’s 401(k).  Therefore, Envestnet│Yodlee infers that the $15,000 is not a recurring deposit.

The chatbot offers Amanda detailed information on each of the three suggestions listed above. The chatbot uses Amanda’s financial information and best financial practices to offer additional information on each of the three recommendations. For example, when Amanda asks for additional insight on putting the money away in an emergency account, the chatbot provides information on how much money Amanda needs to cover one, three, or six months of spending based on her habits. 

IBM Customer Insight:

IBM Customer Insight, the second IBM product to be demonstrated at FInovate, is a dedicated cloud system.  It provides cognitive insights derived from third-party sources, customer transactional and behavioral data.

The Finovate demonstration showed what a regional manager at a bank would see when using IBM Customer Insight. The fictional regional manager, Harry can use IBM Customer Insight to predict customer attrition, mortgage churn, overdraft, and large deposits. Also, Harry can use IBM’s system to study the sum of a customer’s life events. Harry can look at one life event, such as a relocation to get information on other possible life events, like purchasing a home or retirement.

M1 Finance:

M1 Finance, a portfolio management tool, announced their public launch at FinovateFall 2016.  Their product allows users to create, organize and automate their investment portfolios.  An individual can choose to create a default M1 portfolio or create their own portfolio. M1Finance has three default portfolios: 1) Savings, 2) General, and 3) Retirement.  The portfolios are all displayed graphically as a pie chart.

In the presentation, the M1 Finance Savings portfolio was selected.  A user can then choose to edit the savings portfolio investments.  For example, a user can search the investments in the savings portfolio for FANG stocks (Facebook, Amazon, Netflix, and Google) and opt to group those stocks together.  The user can track this FANG group separately and even choose to increase the weighting of the FANG stocks.  Every slice of the pie is a visual representation. For example, if the perimeter of the FANG stocks are not be in line with the rest of the pie’s perimeter it indicates the FANG weighting is over/under target allocation.

M1 Finance is available on the web, android and iOS.  In the presentation, M1 Finance said they do not charge rebalancing commissions.

Qumram:

Qumram demonstrated how “digital business and compliance can co-exist.”  Qumram records every digital interaction, plays them in movie form, and stores the videos for as long as is required by regulation.  Currently the product is used by UBS globally.

In today’s demonstration, the Finovate audience witnessed an interaction between an advisor and a client on WhatsApp. The fictional client was Patrick, who wants to invest $30,000.  After the advisor’s conversation with Patrick concludes, the conversation is recorded and automatically categorized with the client’s name, advisor’s name and products mentioned, e.g., LinkedIn (LNKD). 

Clinc:

Clinc is another dynamic intelligence solution.  The application responds to conversational language. For example, in today’s demonstration, the demonstrator said, “I am thinking of getting something to eat after Finovate in NYC. Can I afford $150 on dinner?”  The application responded with the user’s monthly average spending on eating out.  The application also added that if the user were to spend $150 on dinner tonight that the user would still be 10% below their average monthly spend. Additionally, with the use of the Clinc app the user can move some money between accounts.

FIS:

FIS discussed their new card-less cash technology. The FIS presenter showed that an individual can retrieve cash from an ATM without inserting a card.  A user can save their preferences on their mobile device. For example, if a user usually takes out $40 at a time, then that preference can be saved. When at an ATM, the user can select card-less cash as an option. The user then scans the QR code on their mobile device. 

FIS also showed that when a user approaches an ATM that is behind a locked door, the user can open the door with their mobile device. Lastly, FIS demonstrated that with their technology allows a user to send money via Amazon’s Alexa. The demonstration closed with a video of the individual in India collecting the money from an ATM located in India. 

With the addition of FIS’ latest partnership there will be 100,000 ATMs with card-less cash optionality.  Additionally, card-less cash works at participating grocery stores, convenience stores and pharmacies.

 

 

 

FinovateFall 2016, NYC: Day 1

This is my first year attending a Finovate conference. This year many of the companies claim to solve one of two problems: fraud or lengthy existing processes to comply with AML/KYC laws.  Additionally, there are several companies that facilitate collaboration and co-browsing between representative and consumer, or in the case of wealth management, advisor and client.

Below are companies that have products that touch – some more closely than others – the wealth management space:

Trulioo, one of the verification companies, was memorable for the fictional characters used, “Ryan Lochte” and “Michael Phelps”.  Michael Phelps checked out when Trulio selected six of his credentials to validate out of over 200 possible data sources that could be used to verify users.  Ryan Lochte did not check out when the same process was used. The presenter joked that Ryan may not be able to open an account with a Brazilian start-up. Trulioo stressed its ability to work in over 50 countries and as such, highlighted that it would be a good vendor for companies looking to expand globally.

In the Backbase presentation, the presenter proved to the audience that it is possible to set up a personal checking account in 60 seconds.  Backbase features include: conversational style dialogue to get initial customer details, social security numbers are automatically verified, and official documentation (passport, state ID)  and credit card information can be uploaded with a mobile camera.  Backbase’s customers include Goldman Sachs and ABN Amro.

TokBox and Salemove facilitate collaboration and co-browsing across platforms. Both companies focus on the fact that customers prefer to see the person they are engaging with online (Proof there is another person answering your questions!)  For example, when co-browsing using Tokbox, an advisor can share content with their client, can annotate on the shared screen, and then save the screen to send to their client later.  In addition to co-browsing, Tokbox features include: two-factor authentication, secure recording, and multi-party calls.  

SaleMove allows advisors to login through a portal on a website.  In the case of wealth management, it is designed to run on top of a wealth management firm’s or RIA’s website.  The wealth management firm or RIA can create the business rules for when a customer engages with the website.  For example, if a client that has previously engaged logs on, SaleMove can direct that customer to the same advisor that previously answered the customer’s chat request. Business rules can also be created so an out of office message picks up.

Personetics’ product is a “savings coach” that helps consumers with short-term goals and retirement.  It is a predictive analytics solution with a chatbot.  While it is a consumer banking product now, it is possible to envision it being used in the wealth management space as an add-on tool designed for mass market, mass affluent and/or HNW clients.   The Finovate presenter gave an example of a customer about to go out to eat and the chatbot alerts the customer that they have been spending a lot on restaurants. Or a customer can ask a general question, like “Can I afford this?” Typically the chatbot will ask how much it costs then the user inputs the price. The chatbot will inform the customer how many months of cash-flow are needed to afford the purchase. The user can also check in regularly with the chatbot to see how much they have saved for a specific goal. Lastly, The Personetics presenter mentioned that the product collects feedback while in interaction. For example, the Personetics chatbot will ask the customer if the chatbot is helpful and the customer can respond “Yes”, “Meh” or “Stop sending me these”.   

More to come from Day 2 tomorrow…

 

 

 

How can wealth management firms use LinkedIn to attract retirement assets?

I recently switched jobs and called my financial institution to inquire about moving over the 401(k) I had with my old employer.  This experience led me to consider, “Could wealth managers comb LinkedIn or other sites for indications that a client has recently switched jobs?”  While it is definitely not efficient to study LinkedIn for an hour each day, a computer program or app could be developed to track this information.

A wealth management firm could build a computer program to track current clients’ career moves. The wealth management company would need a LinkedIn page, which most companies already have, and permission from clients to access their data.  A computer program could be designed to store clients’ current job information and alert the wealth management firm of job changes.  While some customers may be reluctant to give permission (opt-out), other customers may appreciate the fact that their financial institution will proactively reach out to them to touch-base after a career move (opt-in).  Many clients are too busy to contact their financial advisor in a timely manner. 

When dealing with client’s financials, it is best if advisors tread cautiously so as not to be viewed as “creepy”.  When reaching out to clients, the advisor should initiate conversation with a more generic offer or say they are simply “checking in”, rather than call with an obvious goal of moving over retirement assets.

Another option to attract clients and prospects would be to create an app with utility or appeal (think Yahoo finance or a competitive portfolio management simulation app) and then require LinkedIn data to join.  Then wealth management firms could get career data on prospective clients too.  The company would have information on anyone who used the app.  In that case, maybe the wealth management firm should focus on a gaming app targeted toward people likely to be in high salary industries?

From a compliance perspective, the above solutions entail monitoring the activity inside an app or the activity of the wealth management firm’s LinkedIn page, which are both easier to track than if individual advisors were to attempt prospecting on LinkedIn. And, while some financial advisors at a wealth management firm may have close connections with some of their clients, it is probable that not every client of every FA informs or consults their FA about retiring or switching jobs. In that case, wealth management firms could explore one of the two options to ensure they do not miss the opportunity to attract the retirement assets of a client that spent a decade receiving a consistently high salary at their prior employer. Both solutions are a way for wealth management firms to get a larger share of the 4.7trillion 401(k) market.

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