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Wharton FinTech Podcast: Beacon Co-Founder Mark Higgins on FinTech Advantages, AI and Hedging, and the Appeal of Finance for PhDs

I recently joined host Andrew Janssens on a Wharton FinTech Podcast to discuss a variety of topics, including my evolution from a quant at a small power utility fintech to founding Beacon with my former colleague, Kirat Singh. Over the span of my career, I’ve solved problems as a quant, seen trading go from a voice trading business to electronic trading, and helped build Beacon as a platform for innovation in today’s markets and future ones. 

I was hired by Wall Street as the derivatives markets exploded in size and complexity and companies realized that they needed physicists and financial engineers to handle the math. My first job in 1996 was at a small power utility fintech, Contango Energy. I was tasked with building a power and natural gas trading system as the power markets deregulated and utilities built their first trading desks. I was thrown into the deep end in this brand new market, along with everyone else there. It was a great learning opportunity, having to figure things out on the spot and watching a new market coalesce, develop, and evolve. 

I then moved to Goldman Sachs in 1998, working as a quant on the foreign exchange desk. It was here that I met Kirat, who was working on SecDB. SecDB was a highly customizable trading and risk system for the foreign exchange and commodities businesses in the mid-90’s, but it soon spread across all of Goldman Sachs’ trading businesses. It allowed users to see risk and P&L across businesses. As a development platform it made us very productive; we could write our own code as quants, do testing at scale, and use the tools in SecDB to solve our problems. This enabled Goldman to get models to the front line and calculate their risk exposure faster than most of its competitors. And helped them reduce their reliance on the horrible trap of spreadsheets.  

Kirat and I went to JPMorgan in 2006 and built Athena, a similar platform to SecDB. We had the advantage of hindsight from our SecDB experiences, and a modern technology base to build on. After four years Kirat moved to Bank of America to build Quartz, another SecDB-style system, while I remained at JPMorgan, where I co-headed the Quantitative Research group and ran the electronic market-making business for currency options. Kirat left Bank of America in late 2013, and catching up over a beer, we decided to start Beacon as a way of delivering what we’d learned about technology at banks to a broader set of customers across capital markets.

As Beacon has evolved, we’ve worked with many financial institutions who want to move to the cloud, but have a hard time figuring out how to do it efficiently and effectively. In-house tech departments are used to data centers and can struggle making the shift to the cloud. At Beacon, we’ve built a cloud-native foundation that they can quickly leverage, whether they are integrating their underlying enterprise technology solutions, building a yield curve, or structuring a foreign exchange knock-out option. Financial institutions can buy Beacon and focus on their own secret sauce. They don’t have to spend years building the foundation; we’ve already done it and learned from years of experience, so they don’t have to.

Listen to the podcast to hear more of our discussion including the edge provided by Goldman Sachs’ SecDB, how SecDB affected outcomes during the financial crisis, applications of AI and neural networks in financial hedging, and how quantitative finance can appeal to PhD grads. And my favorite hobby, backgammon.

Key takeaways

  • Beacon enables financial institutions to innovate faster, whether it’s adding a new product, implementing an end-to-end rollout, or fixing models on the fly. We consider Beacon to be a more modern and customizable version of SecDB.
  • Our vision is that capital markets developers want Beacon the same way traders want a Bloomberg terminal: it’s just a much better set of tools for them in their business than the alternatives.
  • In today’s marketplace, there’s a place for those with quantitative finance backgrounds, statistics, or PhDs. Working as a quant on a trading desk is a fun, fast-paced environment that provides for immediate feedback, and intellectual problem solving.