Blending a Finance Background with the Latest Tech Stack: A Conversation with Magnifi CPO Tom Van Horn

At Magnifi, we like to say that we’re creating the “fin in fintech.” That means combining real-world experience in financial services with deep technological know-how to create platforms that address today’s most pressing market need: simple investment discoverability. Below, Magnifi’s Chief Product Officer, Tom Van Horn, discusses how technology is solving this lingering challenge while simultaneously personalizing and improving the investment experience for advisors and clients alike.


You have a unique background for a CPO, what can you tell us about your career?

Tom Van Horn: I’ve spent my career both on the business side of financial services — working for RIAs, banks, holding companies, etc – and have also held various positions on the technical side as well. I’ve been on the product creation teams of startups as well as supporting more mature technologies on both the implementation and business sides. So, it’s a blended background, with a history of building, launching, and optimizing many financial systems that are out there in the marketplace.

As I look at my career path, what’s made me the happiest has been being on the technical implementation side of things, overseeing product creation. But my background as a user on the business-side gives me a unique perspective as well. I’m able to work with a broad lens of understanding the needs of many of our clients ranging from independent advisors, broker-dealers, asset managers, and other financial enterprises.  This allows me to implement user-centric solutions to meet the latest demands in the industry. 

I like being able to see all of that landscape in the marketplace and how it relates to our solution.


Magnifi recently announced the integration with custodian Charles Schwab.  Tell us more about this integration and how it will benefit advisors?

TVH: In seconds a Schwab Advisor can use Magnifi’s natural language search capabilities to ‘Google their book’ and  Discover signals such as; ‘Where do I have exposure to China…TESLA…ESG…Battery Tech…Space Exploration etc?’  This integration for Schwab Advisors will unleash the power of Magnifi and allow Advisors to quickly Discover and act on value add and event driven opportunities in their clients’ portfolios.


What brought you to Magnifi specifically? What about this project was interesting?

TVH: I was initially intrigued by the way Magnifi is approaching some major problems in the industry. For one thing, Magnifi is bridging the gap between product and investor.  It is addressing the discoverability challenge brought upon by increased opaqueness via the introduction of tens of thousands of new investment products that are out there today. And doing it using plain English to make the process fast, easy, and intuitive for both investors and advisors. That was a growing problem that remained unsolved prior to Magnifi.

In addition to the “What”, I was also attracted to the approach that Magnifi takes. Previously, I was with Broadridge Financial for nine years.  While I enjoyed my time there, I was excited to get back into a nimble and entrepreneurial environment that’s very fast paced and willing to make moves quickly in order to be on the cutting edge. That’s Magnifi. 

That’s not to say that Magnifi is just another startup operating out of a garage. There is a constellation of talent here including a number of well-respected industry veterans like Dr. Vinay Nair, David Pottruck, Trish Rothschild, and a few others who I know and grew up with in this industry. These are the individuals that have seen the evolution of this industry and can identify where there are opportunities to apply new thinking to modern challenges. Seeing the types of people who were brought in to not only work here, but also the advisors and investors who believe in our shared vision is quite unique and exciting to be a part of it.


How can technology solve for the problem of sorting and filtering all of today’s investment products and options?

TVH: Google is a good example. Luckily, I was around on the internet before Google and of course I’ve also been able to see it afterwards, and it’s almost impossible to remember how we navigated around the web before that type of search technology existed. Amazon has done the same thing for shopping marketplaces, turning basic cost, review, and feature comparisons into a search and discovery process.

That hasn’t happened yet in the investment industry. I’m extremely fortunate in that I have a finance background so I understand the calculations and comparative aspects that go into choosing different investment options.  However, if you walked up to a normal person on the street and asked “is this ETF a good investment?” reveals how complex this all is. There’s a true disconnect between the people who want to get involved in the market and the systems and information that are out there.

Now, technology is able to bridge that gap by combining natural language recognition with investment intelligence.  We can understand this is what you care about, this is what you’re looking to include/exclude, or this is the theme that you’re going after. That way the investor doesn’t have to know anything about volatility calculations, fee structures, or anything else – all they need to do is ask for the products they are looking for and the platform does the work. 

You shouldn’t need a PhD in complex and expensive software tools to find the right investment for you.  You just need an idea and a keyboard. 


Where does data science plug in to make that possible?

TVH: It goes back to the core of what machine learning can do. For example, if we think about what recently happened with COVID-19, maybe a user would go into the Magnifi application today and search for “ventilators.” That’s a topic that’s being talked about a lot today in news cycles.  An investor would want to know how to discover investment options for something that is having an impact on the market.

As investors search for that term, our machine learning navigates through 10-Ks, prospectuses, earnings reports, etc looking for keywords that relate back to ventilators. From ventilators we can go into “healthcare” and that ends up pulling in “medical” and “medical devices.” So, from a single search term like that, Magnifi can easily determine where the strongest holdings are that correlate to ventilators across a marketplace of investment products.

That was learned in the software based on actual user search terms, and it is one of the key differentiators of what we’re building at Magnfi. The software itself has to be self-learning in order to keep pace with what’s going on in the world today and how real people talk. Every year, speech patterns and word usage change. That’s just how natural language and communication works. We need the ability to not only keep pace but continue to be ahead of that curve so that our search results bring a level of relevance that does not exist today across investment products.


What else is the software learning?

TVH: We use the word “fund” a lot, particularly around ETFs and mutual funds, but one of the areas that have been extremely opaque in the investment industry are Separately Managed Accounts. Let’s say an Advisor is looking to fill some exposure in a category such as Large Cap Opportunity and within it there are thousands of variations, asset manager products, and holdings. Very few individuals in the finance industry, let alone especially your average weekend investor, is going to painstakingly read through all that documentation and every quarterly write-up to determine who the best managers may be.  Or, if how those managers are classifying themselves actually hold true to the underlying holdings and what the exposure and risk truly looks like.

But an analytical tool that can key in on very specific naturally spoken search terms helps to solve this problem while simultaneously delivering a more personalized experience. Using natural language to distill all of these different products without having to spend hours on research is pretty powerful and points to the importance of simplicity when it comes to user experience. Just because an investor doesn’t have weeks to spend on research doesn’t mean they don’t need that information. They just need a better way to access it.