What we are
ficc.ai is a financial technology firm based in Seattle and New York that provides accurate real-time pricing for over one million municipal bonds, enabled by the latest advances in machine learning. Our artificial intelligence models provide continuous understanding of the market for munis, enabling all market participants to operate with greater speed, greater visibility, greater confidence, and greater efficiency.
How we do it
Our technology creates profit opportunities by enabling users to evaluate buying and selling opportunities systematically and quickly. This allows clients to take advantage of market inefficiencies and achieve alpha in a repeatable way. Increasingly, the determination of market actions, both on the sell side and buy side, is done by algorithms. Our technology is a crucial enabler of this trend for municipal bonds.
Whom we help
Accurate real-time price estimates are valuable not just for traders, but also for issuers, municipal advisers, underwriters, dealers, brokers, alternative trading platforms, portfolio managers, other asset managers, compliance and risk managers, financial advisers, end investors, and more. We serve all these constituencies within the municipal bond ecosystem.
AI-powered real-time pricing streams for municipal bonds give investors and traders an unparalleled advantage in the market. Our product includes the first-ever fully data-driven, fully objective, fully real-time yield curve for the muni market, and advanced algorithms that continuously improve our pricing capabilities. Our product can incorporate decision theory for optimized automated trading and additional machine learning for optimized hedging, ensuring that we remain at the forefront of the industry.
By using deep neural networks, which outperform decision tree methods and other older methods, we deliver accurate results throughout the trading day, far more useful than the end-of-day prices provided by existing services. Estimated prices and predicted yield-to-worst (YTW) can be consumed via API, via in-house applications, and/or via spreadsheets. All software is cloud-based and highly scalable, so integration with existing order management systems and trade processing systems is straightforward.
Charles was most recently a managing director at Goldman Sachs in New York, where he was the global head of machine learning. Previously he led the central machine learning organization for Amazon in Seattle, and spent many years as a professor of computer science and artificial intelligence at the University of California, San Diego. He has a Ph.D. from Cornell University in computer science and an undergraduate degree in mathematics from Cambridge University.
Prior to starting ficc.ai, Gil spent six years at Microsoft AI and in the Amazon core machine learning team, where he drove initiatives to apply state-of-the-art artificial intelligence techniques to real-world applications with several hundred million users. Earlier, Gil founded Amobee, the world’s first mobile advertising company, sold to Sing-Tel for $324mm. He started his career as a software engineer and has an MBA from the Wharton School, University of Pennsylvania.
ML Software Engineer
Ahmad Shayaan joined ficc.ai from Columbia University, where he earned his M.S. in financial engineering. He has previous research experience in artificial intelligence and at hedge funds. He also holds M.S. and B.S. degrees in computer science from IIIT Bangalore (India).
Data & Research
Jesse came to ficc.ai from Oberlin College (Ohio) where he was a professor teaching courses on technology in East Asia. He holds a Ph.D. from the University of California, Berkeley and an M.A. from Peking University.
Prior to joining ficc.ai, Myles was a professor at Lee University. Previously Myles had been a researcher at the Université de Lorraine (Metz, France) as well as at Oxford University (Oriel College). Myles will defend his Ph.D. dissertation at the University of Groningen (Netherlands) in 2023, and holds an M.A. from Yale University.
ML Software Engineer
Prior to joining ficc.ai, Mitas was a researcher at the University of Washington in Seattle, working on machine learning methods for sequential decision making and decision-dependent optimization. Mitas holds a M.S. from the University of Washington. Immediately after earning his B.S. in computer science from the University of California, Berkeley, Mitas was appointed as a lecturer there.
ML Software Engineer
Isaac has extensive experience in both machine learning and finance. He earned his M.S. in management science and engineering from Columbia University in 2021. Previously, he earned a B.S. in economics with first class honors at University College, London. Isaac has worked on applied machine learning projects for the Ministry of Finance in Singapore and the luxury group LVMH.
Joe is a founder of Intricate Bay Capital. From 2018 until recently he was co-head of the Global Spread Products division at Citi. Earlier, also at Citi, he managed sales, trading, structuring, and lending businesses for municipal securities also. Joe graduated magna cum laude as an undergraduate at Harvard, and he has served on the Municipal Securities Rule-making Board (MSRB), where he was Vice Chair.
Ross co-founded Old Orchard Capital Management, an investment advisor that specializes in trading municipal bonds, in 2014. Earlier he was a partner at First New York Capital Management, a managing director at Union Bank of Switzerland (UBS), and a vice president at J.P. Morgan and Prudential Financial.
click here to request a demonstration of our technology or email our product manager Myles at firstname.lastname@example.org
We are always looking for world-class software engineering, financial, and machine learning talent to join our growing team. If you are interested, email us at email@example.com