Celent’s Innovation and Insight Day: Wealth and Asset Management Stream

Celent’s Innovation and Insight Day: Wealth and Asset Management Stream

We are only weeks away from Celent's 2017 Innovation and Insight Day where we will explore how players in the financial services market are leveraging technology in innovative ways in order to differentiate themselves in an increasingly competitive and challenging marketplace. We will be featuring a number of case studies, discussions, and deep-dives into topic areas surrounding innovation and focusing on themes, such as:

  • Customer Experience
  • Products
  • Emerging Innovation
  • Operation and Risk
  • Legacy Transformation

This is the first year we will have a Wealth and Asset Management (WAM) breakout session where we will cover a range of topics around innovative solutions and trends in WAM.  The agenda can be found here: Wealth and Asset Management (WAM) Program and will be presented by analysts from the Celent Securities & Investments and Wealth & Asset Management teams:

  • David Easthope, Senior Vice President, Securities & Investments
  • Brad Bailey, Research Director, Securities & Investments
  • Kelley Byrnes, Analyst, Wealth & Asset Management
  • John Dwyer, Senior Analyst, Securities & Investments
  • Ashley Globerman, Analyst, Wealth & Asset Management
  • Arin Ray, Analyst, Securities & Investments
  • William Trout, Senior Analyst, Wealth Management
  • James Wolstenholme, Senior Analyst, Wealth & Asset Management

I particularly look forward to sharing research around the evolving wealth management landscape as the core client base shifts from baby boomers to millennials. While much ground has been covered from the perspective of wealth managers to meet the digital needs of nextgen clients, wealth managers continue to be behind the curve in their digital offerings.

How are wealth managers and vendors responding to the paradigm shift in the development and execution of services and products to meet millennials’ distinct expectations?

This is just one example of the many topics that we will discuss at I&I day – we hope to see you there!

 

New Year New Tech New Research

New Year New Tech New Research
In your new year resolutions, did you pledge to understand more the technology that scares you? Or at least the one that some people (aka analysts like me) claim will replace you? If the answer is “No” and you are working in the field of Investment Research, whether producing, consuming or distributing it, then you may want to read our latest report Start Coding Investment Research: How to Implement MiFID II with Robots and AI.

I get paid to write research on fintech so theoretically I am not the tech scared type though I am the first one to control screen time at home. I know we have more and more competition from free research you can all find at your fingertips on the internet, and from cheaper research that leverages outsourced resources crunching a lot of data, but so far we are keeping up probably because our clients think we provide insight that those competitors do not provide yet.

I know however that we have competitors that have technological platforms that distribute their technology in a more user-friendly way with podcasts and fancy databases, that write their research in a more automated way and that you can consume easily because you pull the information with selective search technology that knows what you want and how much you can pay for it.

So before the holiday season, to make sure we were all going to start this new year with the right information in hand, I did look into what artificial intelligence and robotic process automation tools will be doing to research; not exactly my kind of markets fintech research, but more specifically to Investment Research, those written recommendations about equity or bonds or macroeconomic environments to help the buy side make investments.

The result is very honestly scary and exciting at the same time. These new  technologies are maturing at a time of big regulatory change in Europe, MiFID2 is finally kicking in and that means the unbundling of investment research cost from the execution costs the brokers and banks charge their buy side clients. Some buy side will keep using them and be happy to pay that fee, some clearly will start looking at other solutions that will have to propose a different business model provided by banks or by new market players, based on technology.

In our recent report we do look exactly at that: new business models and live case studies that have already been implemented in investment research production, distribution and consumption. Enjoy.

The Under-Tow in the Data Lake

The Under-Tow in the Data Lake

The word on the street is big data, data lakes leading to insight, uncovering the hidden opportunities within your massive trunks of data. All true but the majority of the buy side, asset managers, asset owners are still desperately struggling with getting their fundamental data in order.

Over 80% of AMs are $100billion AuM and below and 60% are $50 billion AuM and below, many of these AMs are progressing on solidifying their IBOR (Investment Book of Record) foundations. IBOR and the IBOR Services Matrix (see Inside the Matrix: The Future of IBOR) is still the architectural goal but not yet a necessity for all levels of the asset managers.

Many are not yet up to an IBOR level architecture and still dealing with more basic EDM (Enterprise Data Management) realities. A significant number of AMs are dealing with implementing solid data management and data governance across their portfolios and funds, don’t yet demand millisecond real-time but are operating in a near-time environment, that is operationally sound and cost sustainable.

Now the good news is that as AMs and increasingly institutional asset owners can take advantage of superior vendor solutions and bypass non-differentiating EDM issues. There is certainly little reason, in this day and age, for AMs to attempt to build their own EDM structures. Vendor products can provide core ETL (Extract Transform Load) processes and perform the core standardization, editing and cleansing of the data. Eventually this will all become utilities but for now it is still needs to be dealt with firm by firm.

Data lakes are phenomenal but before the majority of the buy side AMs and asset owners are primarily utilizing their data lakes they are feverishly executing the initial layers of data management and governance to stay market competitive.

Capital One Rolls Out a Bank Built Robo

Capital One Rolls Out a Bank Built Robo

In a blog post yesterday I took automated advisors to task for the black and white way (advisor-assisted “hybrid” model versus “digital only”) they have framed the robo debate. Imagine my surprise when I saw that Capital One’s brokerage arm had launched a platform addressing this very complaint.

The Capital One robo combines a digital interface with telephone access to advisors. It’s an advanced take on the hybrid models offered by Personal Capital and Vanguard, both of which use digital technology (iPads, smartphones and other interfaces) to enhance and scale the contribution of the individual advisor.

What these models do not do is digitize advice delivery. Yes, they deploy algorithms to develop risk based portfolios, but firms have been doing this for ages. The defining characteristic of robo (as opposed to automated) advice is the removal of the real life advisor.

Robot with Benefits

The Capital One robo or robot is a step in that direction in that it automates the entire portfolio manufacturing process, while giving investors the options of getting a wise uncle (or aunt) on the phone to discuss it. This process spans risk profiling and portfolio construction on the front end to compliance and funding at the back.

Needless to say, clients pay for the privilege, to the tune of 90 basis points. This is not much less than the average US advisor charges for his services, and it is a given that other firms will replicate this model, and at half the price. In the meantime, give Capital One kudos for being the first US based bank (Bank of Montreal, whom I discuss in a recent report, was the first in North America) to roll out a homegrown, pure play robo advisory platform.

The battle for the soul of exchange-based equity trading?

The battle for the soul of exchange-based equity trading?

The recent statements by Nasdaq regarding the possible use of a trading delay by the proposed IEX Exchange puts the spotlight on a battle for supremacy not just between rival exchanges, but very different philosophies regarding what the ultimate role of exchanges in the global capital markets should be. The established exchanges, willingly or unwillingly, represent the status quo in terms of how exchanges should function. IEX on the other hand hopes to represent the interests of those trading participants who believe that they have been left behind in the race for speed in today's capital markets, especially the retail participants and the smaller buyside. It seems like an inevitable outcome in the aftermath of the global financial crisis, which has stoked the debate on economic inequality and the unfair advantage that a select group of trading participants have over others due to their advanced technological capabilities and use of highly sophisticated financial products. 
Getting back to the objections raised by Nasdaq over the SEC proposal that any delay of less than a millisecond could qualify as immediate, which would enable IEX to operate in the way it wants, there is certainly some substance in Nasdaq's argument. The SEC would have to come up with a solution that is acceptable to both sides, and does not leave it vulnerable to legal challenges. It is going to be an interesting couple of months for industry obervers as they follow the debate over the fairness and validity of the SEC proposal, and the decision on the IEX application.

Future architecture: All roads lead to Cloud

Future architecture: All roads lead to Cloud

Present vs. Future-State Architecture

Our frenetic activity of client meetings, briefings, conferences, and events heated up in the last few months. We recently spoke to audiences in New York, London, and Tokyo.

The present environment of cost-cutting, evaluation of profitability, capital efficiency, and compliance implementation is consuming much management attention and IT budgets. Operational efficiency and operational risk mitigation are top of mind.

However, across our client base and network of financial institutions and vendors, there is also a continued desire to understand emerging technologies like blockchain/DL and artificial intelligence. Many of you are expressing a strong interest in our opinions on the future state of the technology architecture in parallel with these day-to-day operational considerations.

From this vantage point, we believe the potential of blockchain technology (including smart contracts), IoT, and artificial intelligence will drive incremental IT spending going forward as solutions are implemented, further uses cases are developed and tested, and ecosystems and IT partnerships are expanded.

All Roads Lead to Rome Cloud

With respect to the future IT architecture, one striking conclusion we've reached is that all roads lead to cloud. For instance, major blockchain use cases are being built atop cloud providers. Technology firms such as AWS, IBM, Microsoft, and others appear to be prime beneficiaries of this frenetic activity, some of which is strategic, and some of which may be simply tactical and later disappear. In addition, artificial intelligence may be best leveraged in the future with data that resides in the cloud as opposed to in siloed business operations. Moreover, wealth managers increasingly are considering cloud-deployed solutions. Even compliance (e.g. RegTech) is increasingly being sold "as a service".

Clearly not all capital markets, wealth management, and asset management operations are cloud-friendly, both now and in the future, but many types of operations will move to the cloud.

We see this happening gradually and powered by availability, greater standardization, and creative vendor offerings across a spectrum (from ITO and BPO to managed services, utilities, and yes … cloud possibilities throughout).

Proof of artificial intelligence exponentiality

Proof of artificial intelligence exponentiality

I have been studying Artificial Intelligence (AI) for Capital Markets for ten months now and I am shocked everyday by the speed of evolution of this technology. When I started researching this last year I was looking for the Holy Grail trading tools and could not find them, hence I settled for other parts of the trade lifecycle where AI solutions already existed.

Yesterday, as I was preparing for a speech on AI at a conference, one of my colleagues in Tokyo forwarded me an Asian newswire mentioning that Nomura securities, after two years of research, would be launching an AI enabled HFT equity tool for its brokerage institutional clients in May –  here it is: the Holy Grail exists, and not only at Nomura. Other brokers have been shyly speaking about their customizable smart brokerage, e.g. how to use technology so that tier5 clients feel they are being served like a tier1. Some IBs are working on that, they just don’t publicly talk about it.

Talking to Eurekahedge last week I realized that they are tracking 15 funds that use AI in their strategy, I would argue there are even more than that because none of those were based in Japan (or Korea where apparently Fintech is exploding as we speak).

All this to reiterate that AI is an exponential technology, ten months ago there were no HFT trading solutions using AI, and we thought they were a few years away but no, here they are NOW. And the same with sentiment analysis, ten months ago they were just a marketing tool, now they are working on millions of documents every day at GSAM. Did I forget to mention smart TCA that’s coming to an EMS near you soon?

Stay tuned for more in my upcoming buy side AI tools report.

Asset managers turn up the volume

Asset managers turn up the volume

There are two ways to make net profits – maintain a high margin and/or sell more volume at lower operating costs.

Asset managers find themselves in a low margin environment so the tactical and perhaps strategic path forward is to find volume at lower operating costs. The recent buy of Honest Dollar out of Austin, Texas by the Investment Management Division of Goldman Sachs is the continued direction of purchasing volume by buy side asset managers.

Overall asset managers are buying up robo advisors, not because they are overly threatened, but to expand the AMs existing client base. With automation AMs can add new clients at a relatively low operating cost and find an expanded demand side for their collective funds and ETFs. Look behind the scenes on any of the nascent robos and you’ll see all AMs product supply.

So the purchase of Honest Dollar is an early indicator that increased volume is in play. As Goldman stated, over 45 million Americans do not have access to employer-sponsored retirement plans. With targeting small businesses with less than 100 employees, utilizing automation and AM supplied ETFs and other funds a volume growing profit base is viable.

A major play of the automation of investment advice is increasing the total addressable market of investment consumers. The democratization of investing is being made a reality by the ready access to technology, but it must also be said that there is no correlation between democracy and actual wealth accumulation.

Being smart with artificial intelligence in capital markets

Being smart with artificial intelligence in capital markets

Artificial Intelligence (AI) is the new buzzword to talk about on the street. Financial institutions need to embrace AI, as we have explained in our January report, or else they risk to lose competitiveness or be coded by the regulators more than they can do it themselves.

I am in NYC next week to share Celent’s view on AI for capital markets. A little preview for your here.

Today we are at a crossroad where data scientists have the computing power, the alternative mind-sets to search and the willingness to look for narrow AI solutions, not the wide AI brain that we should get to in 2030 according to experts. This enables vendors to come up with amazing solutions from Research Scaling with Natural Language Generation to Market Surveillance/Insider Trading with Machine Learning Natural Language Processing or even Virtual Traders via Deep Learning of technical analysis graphics traders look at to take decisions.

The amount of data available is another big driver for the rebirth of AI, and regulators are looking at ways of accessing that data and using it. This is borderline what my colleagues would call RegTech, and it’s coming.

Our Q2 agenda reflects our understanding that you want to know more about AI: we will share ideas on solutions for the buy side, for exchanges and for the sell side. But in the meantime I hope to bring back some cool ideas from the big apple, hopefully also from the secretive quants working in the dark Silicon Alleys.

Most of the vendors I have profiled are specialists’ boutiques, but the cost of such research is however so enormous that generalists are trying to productize their fundamental research for various sectors, from health to homeland security, including financial services in partnership with financial institutions.

This morning I woke up to great news that Microsoft is at the forefront of Deep Learning on voice, imagine what this could bring to Anti-Money Laundering or Insider Trading products.  The other news was that some top quants of Two Sigma just solved an MRI algo to predict heart disease, and I hope other great minds will, as most of them usually do, also give back to society by applying their amazing knowledge to such grand challenges.

A big bank follows the wirehouses upmarket

A big bank follows the wirehouses upmarket
Money bag icon (flat design with long shadows) JP Morgan Chase’s decision to double the minimum asset level (from $5 to $10 million) required for service by its private banking group underscores the effect that digitization is having on all levels of wealth management. It echoes the approach taken by the wirehouses, who (with the exception of Merrill Lynch, which has served less affluent clients through its Merrill Edge program) have moved steadily upmarket in an attempt to rationalize their high cost service models. As such, the decision does not come out of nowhere but rather reflects the evolving economics of the advice business and the desire to incorporate new service models. It also speaks to the challenges and opportunities facing commercial banks. The Next Shoe to Drop Little noticed in the run up to the announcement of the rejiggered segmentation were a series of layoffs across the private bank. In retrospect, it is clear these were executed to lay the groundwork for the reprised segmentation and the pending launch of what the bank calls Private Client Direct. From the name itself, it is pretty clear that the bank is set to embrace a robo advisory model, perhaps in concert with one of the vendors (such as Trizic, the founder of which, Brad Matthews, is a JP Morgan alum) that have cropped up to serve the bank space. If it moves fast enough, JP Morgan could be the first bank south of the Canadian border (BMO launched its SmartFolio robo advisor platform earlier this year) to roll out such a platform. In truth, the JP Morgan decision is as much a right sizing as a rationalization, since only a small share of current private bank clients are affected by the move. From the bank’s perspective, this tighter segmentation is worth the effort, as small deposits exact a relatively high cost in terms of compliance and offer scant opportunities for profitable lending in the current rate environment. The point has been made, meanwhile, that personal service of the high touch sort is now reserved for the bank’s wealthiest clients. Doubtless management will pull out all the stops to keep these clients happy.