We built Valsys to provide professionals with the tools they need to make data-driven decisions in valuation and estimation processes. Our aim is to augment our users' industry knowledge with the deep insights offered by machine learning and big data.
Private company valuation is a complex estimation process that is vital to private equity and M&A professionals. Analysts must leverage noisy and incomplete data sources to predict crucial metrics such as multiples and cash flows. Historically, there has been no statistically robust method for producing these estimates, nor has there been any way to ascertain the relative confidence a valuation practitioner can have in their model outputs.
Our platform offers our users access to state of the art machine learning techniques specifically designed for private company valuation.
Our algorithms provide substantial improvements in terms of model accuracy over traditional approaches.
Confidence regions allow users to understand and manage their model risk.
Variable weightings demonstrate the relative effect each model input has had on the output.
Our platform makes use of cutting-edge machine learning technology whilst remaining familiar to valuation practitioners.