The Prediction Models Forecasting Global Market Shifts

Liquidity’s proprietary decision science technology is able to anticipate market shifts and integrate them into its risk models, underwriting assumptions and capital strategies.

A recent case study compiled by Liquidity’s data science teams forecasts the overall default rate for VC-backed companies that have raised over $5 million by analysing past events.

Liquidity’s machine learning (ML) model took into consideration a range of macro and industry level features, from monetary and fiscal policy to current economic conditions and overall VC funding patterns.

“What makes our approach distinctive isn’t just the use of AI in predicting a company's revenue generation or business fundamentals,” says Oron Maymon, Liquidity’s co-founder and CSO.

“It’s how we tailor our models to the funding realities of venture-backed firms. That’s what helps us remain resilient, even in unpredictable markets.”

Backtesting showed that Liquidity’s model predictions successfully captured distinct periods between 2005 and 2024, including the high default years post-global financial crisis (GFC) when unemployment was high and interest rates were zero, the lower default rates in the years immediately preceding COVID and then the turbulent post-COVID years.

The study reveals Liquidity’s AI forecasting model’s ability to accurately predict shifting market trends ahead of time to keep its portfolio companies proactive in the face of market shifts.

“No matter what’s happening in the market, our approach remains grounded, data-informed and deliberately cautious. It is designed to propel our portfolio companies through changing cycles.”