FinTech may have become an investment and media darling over the past couple of years, but product management guru Jon Zanoff has been beating the drum for much longer than that. He founded the thriving community Empire Startups in 2011, and is currently lowering barriers to entry to accelerate FinTech innovation at Techstars. We talked to Jon about new trends in FinTech, common entrepreneur pitfalls, and novel uses for machine learning.

What drove you to found the Empire Startups community?

When I started Empire, FinTech entrepreneurs had very few resources to support innovation. I’ve found that the single most impactful, albeit low-tech, way to drive innovation is by putting smart people in a room together. Whether you’re looking to find a subject matter expert, a co-founder, share a useful blog, or to simply enjoy the fellowship of the entrepreneurial roller-coaster, community is essential to FinTech innovation.

What overall trends are you seeing in the FinTech ecosystem?

In the last year we’ve seen a huge uptick in the effort and resources financial institutions have put toward the FinTech startup community. While in many cases it’s currently more observation than actually taking major action, the realization that banks must develop a cohesive strategy for embracing nascent technology will continue to accelerate FinTech. FinTech startups are hungry for domain expertise and scale, while banks can learn from agile teams exponentially outpacing their rate of developing new products.

What advice would you give entrepreneurs?

No one can do it alone.  While you won’t be attracting Fortune 500 CEOs to your early-stage Board of Directors, it’s never too early to create a framework of mentors and advisors.

Get in the habit now of posting friends, colleagues, mentors (heck, anyone that will listen) on your progress.  Email a monthly recap of what you’ve accomplished, what’s next, and most importantly, how they can help.  Everyone around you wants to help – give them that opportunity!

Example:  Hi Lisa, I was so happy to meet in person at last week’s Empire Startups Conference.  I found your passion in building Stanley Sprockets truly inspirational.

If you wouldn’t mind, I would love to periodically update you on the progress we’ve made here at FinTech Widgets?  We know you get a ton of email, so there’s never any pressure to respond.  If you see something interesting we’d love to hear from you!

What mistakes do you hear most often from entrepreneurs?

“I’d love to tell you what I’m working on, but it’s really complicated, so I’d really like to meet in person to walk you through everything?”  Nonsense!  Sure, tech is complicated, and FinTech is as nuanced as they come. However, a 12-page executive summary is a sign that you simply can’t articulate your value proposition. It’s critical that a CEO is able to convey complex concepts succinctly and eloquently to a wide audience.

Think of your elevator pitch as a marketing funnel. Your goal is to complete the entire pitch without losing a single listener. To do this requires zero industry jargon as it must pass the “grandma test.” Would your grandma understand it?

What does your crystal ball tell you about what’s next for FinTech?

As brick and-mortar falls out of favor, there’s a dangerous assumption that consumers will accept degradation of service as an acceptable trade for modern FinTech. Millennials, and people in their 30s and 40s, do expect a fully digital user experience. That said, the expectation is that the digital experience will enable better service than ever before. Startups that build technology that results in a better customer experience overall – both product and service – will be the future of FinTech.

Which FinTech companies are using machine learning in an interesting way?

There are a few I can think of:

The Remesh platform enables a single person to conduct primary research on thousands of people in real time. Interaction with the group is mediated by artificial intelligence producing massive amounts of qualitative and quantitative information. Human-consumable insights are extracted using a stack of ML+NLP algorithms and made accessible to the moderator in real time. Compared to current methods, Remesh reduces the amount of time it takes to conduct primary people research by 10-100x; reducing costs, enabling continual feedback, and meeting the needs of the Agile movement.

Windrush, a data visualization company focused on financial services clients, is using deep learning to automate some of the most tedious parts of a junior banker’s day. They replace difficult manual charting and change tracking with powerful automation tools and recommendation engines embedded right into their customers’ spreadsheets.

Morty, an online mortgage startup building a marketplace for homebuyers to shop and close their mortgage online, is utilizing machine learning to facilitate better underwriting practices. More data and better algorithms – ones that learn from loan performance over time – can improve how lenders, the GSEs, and the public markets evaluate mortgage lending.

Interested in networking, learning, and sharing knowledge with others in FinTech? Join Jon and the Empire Startups community at their next NY FinTech Meetup, SF FinTech Meetup, or FinTech Conference. Follow them on Twitter @jonzanoff & @empirestartups.

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machine learning


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