Adopting a Data Driven Advisory Model for Capital Markets – Part 3


The following is the final installment of a three-part article based on an interview with Stuart Berwick, the CEO and co-founder of financial technology provider, Singletrack.  Before founding Singletrack, Stuart spent a decade in business and technology leadership roles in the capital markets business units of major global investment banks.  Click here to access Part 1 of this interview and click here to access Part 2.

Mike: So what are the areas of a capital markets firm that are the lowest hanging fruit – the groups that would be most open to see your system, adopt it, particularly given that you guys are modular in nature?

Stuart:  This probably wouldn’t surprise you, but the markets businesses are a natural audience for our platform and for the data driven advisory model. These include institutional sales, research, and trading.  Each of these groups are big producers and consumers of data already, and indeed big users of technology. So, the principles of using technology and data, at least, are well established. If you can offer them both the data and tech that drives their activity in a more profitable way, then they’re all ears. 

I believe other areas of the firm are not quite as far along in this thinking.  This includes the banking side, events or corporate access, overall management, even talent management and so on, where systems tend to be siloed.  I think the banking side historically has not really adopted technology very aggressively. However, there is a generational change taking place where the younger bankers expect to be able to leverage tech. They also are huge consumers of data.  Data products for investment banking like PitchBook and CapIQ are increasingly valuable to bankers.  Unfortunately, this doesn’t really manage banker workflows. So systems like ours that guide banker workflows and automate low-value, event triggered tasks offer an opportunity to focus on high value activities and are generating increasing excitement. Another key distinction for Bankers is where the work takes place. For example, bankers tend to be more PowerPoint and Outlook focused. So we have adapted our tools and technology to ensure we deliver insights and workflow tools where our users are.

Events teams are very busy. It’s a very intensive process. So they understandably don’t want to break anything, as they have established ways of doing things.  However, when you can demonstrate the ability to generate a revenue and interest prioritized target list and engage with those contacts with 3 clicks rather than on 50 spreadsheets, then their eyes open quickly. 

Likewise in the talent management space, there are reasonable questions about driving human performance reviews and employee performance reviews purely from data. Yet data can positively inform a review.  It’s not just how many calls did this person make or how many meetings did this person have, but what was the client engagement generated by this person’s activity over the quarter, and what value did that engagement deliver?  How did the engagement of key fund managers this quarter compare with last quarter?  These are much more meaningful metrics that can assess people’s impact in the firm.  Indeed, this is a very popular dashboard for some clients, looking at who are their best performers based on these types of impact metrics.  Tracking this data also helps others in the firm raise their level to that of the best performers.

Mike:  Yeah, it’s not just about activities. It’s about strategic results.

Stuart:  It’s impact.  I think in a sense that’s the CRM debate. It’s not about activities tracking, this is about impact measurement.

Mike:  Conversely, what areas of capital markets do you think will take the longest to adopt this and why?

Stuart:  I think the market side is probably the easiest discussion. The other areas I mentioned are maybe a little further back on the curve but gaining fast. I think that within a sell-side firm, there’s not much advisory business outside of these groups. We could talk about what happens in the back office or what happens elsewhere but that currently is outside of our purview. There are also interesting things happening in the private equity or VC world.

The buy-side is interesting. Like the sell-side, the buy-side is highly sophisticated in many areas in terms of its use of technology and data. But particularly with regards to this kind of data driven decision making, we think there is a lot more that can be done.

You may know we’ve got two products — a sell-side product and a buy-side product. The buy-side product is all about helping asset managers get the most out of their provider relationships, identifying the drivers of alpha, irrespective of the source of research or asset class. It covers research valuation, voting, fee or  spend attribution and more. So I wouldn’t say the buy-side is lagging the sell-side, though I do think there is a huge opportunity to apply the same concepts we discussed earlier. I think that’s probably the order of adoption from our perspective.

Mike:  So, which banks or brokers do you think are currently furthest along in adopting this kind of model to manage their capital markets businesses?

Stuart:  I would characterize the leaders as what I might call innovative independents. These are the mid-sized institutions who may employ hundreds if not thousands of employees.  These types of firms focus on a particular geography, asset class, sector specialization.  They are what we would call independent investment banks.  A subset of this group are the ones that embrace innovation. They’re hungry to find new ways to gain a competitive edge. They’re willing to partner with an organization like ours to achieve that.  Having said that, I think the use case for data driven advisory is equally applicable to bulge bracket firms or smaller independent research providers. The bulge bracket firms obviously are bigger, more complex, often more slow moving, and often have a significant amount of existing technology investments, although they might not have a coherent solution. But they’re on the journey.  Smaller firms are often convinced that they can make do with spreadsheets and manual processes.

Mike:  I think with larger firms, you often have to convince more people to change a direction, whereas a mid-sized firm can often make a decision to go in a particular direction much more quickly, with less people to have to convince to get on board.

Stuart: Absolutely.  From a go-to-market perspective, working with mid-sized firms is definitely a benefit for us. With the larger firms, our modular architecture is more attractive as it means we can address just one department or one specific use case. In both cases, the imperative to embrace the data driven advisory approach is what makes Singletrack an incredibly compelling proposition.


About Author

Mike Mayhew is one of the leading experts on the investment research industry. In addition to founding Integrity Research, Mike is on the board of directors of Investorside Research Association, the non-profit trade association for the independent research industry, and a frequent speaker on research industry trends and developments. Mike has over thirty years of research industry experience. Email:

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