Customer Success Spotlight: Benzschawel Scientific
At Intrinio, we are known for being a top provider of financial data. Our powerful technology is paving the way for developers and large enterprises across the globe and is positively changing the way our dispersed financial sector operates. Intrinio’s advanced, reliable platform delivers premium data packages that allow innovators to build with a peace of mind.
We are proud to collaborate with some of the most innovative and impactful entrepreneurs and businesses, and we’re delighted to showcase their leading-edge work in our blog. Intrinio’s Customer Success Spotlight series will focus on a client that has used our powerful technology to build something revolutionary.
Meet our newest Customer Success Spotlight, Benzschawel Scientific! Benzschawel Scientific is an AI-based firm specializing in financial education, systematic trading, and asset management. The company has over 25 years of Wall Street experience and is dedicated to helping clients figure out which bonds to buy and sell through proprietary mathematical models and deep learning networks. We recently had the pleasure of speaking with Terry Benzschawel, Founder and Principal of Benzschawel Scientific, and discussed what sets them apart from competitors, talked about their biggest challenges and successes so far, and Terry explained how the firm was created.
Give us the elevator pitch for your company.
Benzschawel Scientific is a firm that specializes in machine learning models to predict returns on corporate bonds for sale to institutional clients. In addition, the firm participates in teaching machine learning techniques, particularly applied to problems in finance.
What is your professional background?
I have a Ph.D. in experimental psychology and have done post-doctoral fellowships in optometry, ophthalmology and engineering. More relevant is my 25 years of experience on Wall Street, focusing on proprietary trading, risk management, advanced model development, and traveling the world on sales calls to corporate bond clients.
What inspired you to start your company?
After 17 years of out-of-sample testing of my algorithms for predicting corporate bond returns for clients, the regulators determined that I was acting in a fiduciary capacity for a corporate bond trading desk. This was no longer legal. Rather than abandon my successful strategy, I decided to start my own firm to sell those predictions away from corporate bond trading.
What have been your biggest challenges, and what did you learn from them?
My biggest challenges have been convincing management to deploy my innovative and/or advanced techniques for proprietary trading and risk management.
What have been your biggest successes?
Several things stand out. I developed the first neural network model in banking in 1992 as well as several successful model trading algorithms after that. I was hired by Salomon Brother’s Fixed Income Arbitrage Group (think Liar’s Poker by Michael Lewis). I received two patents on my work in finance. Of course, my promotion to Managing Director at Citigroup was an important feature of my corporate life.
How do you set yourself apart from your competitors?
I think that my analytics on the corporate bond market has provided me with an advantage over competitors. Part of this is due to my decades of experience, but also my extensive visit with clients, and, in particular, my huge database of corporate bond indicative data and historical returns.
Why did you choose to work with Intrinio?
We chose Intrinio owing to their wide range of equity prices and other corporate financial data. These are particularly well-suited for input to our corporate bond models. We are very happy with this arrangement.