Individual loan analysis is hard. Debt investment professionals face a monumental task providing real-time investment decisions, for a subject whose performance is impacted by innumerable fast changing factors. They operate in a chaotic and open system, with near infinite dimensions; multi-layered factors that impact properties: submarket performance, industry classification, covenants, crime, tenants, financial leverage, environmental concerns, macro-economic disturbances, pandemics, inflation, the behavior of the Fed, global supply disruptions, war, borrower or guarantor attitudes and behavior, the special servicer, the list goeson. The complexity of this challenge was at the root of the Great Financial Crisis and many, if not all major Fixed Income market industry disruptions in the past. Furthermore, while analyzing debt instruments is intensive, costly, and requires sector specific skill sets, the work is done under crushing time constraints with market participants needing to make decisions impacted by 100’s of loans in just hours. This presents an enormous challenge but also an equally large opportunity to leverage technology for debt investing and analysis. Against this backdrop we consider how to leverage machine learning and TARA™ to meet the challenge of investment analysis.
