Automating market adoption and growth scenario projections based on real-time market transaction data

Investor in prominent fintech company with new commercial and wholesale banking software needed a data-driven understanding of different technology adoption scenarios, along with a real-time analysis of public use of the software network and the transactions taking place globally.

Rehinged data scientists applied statistical modeling and monte carlo analysis, linked to a real-time view of network transactions and adoption, to automate the market adoption and potential valuation scenarios based on current data.

The investment partner was able to understand how the fintech investment could be valued as the technology displaced varies sections of incumbents over time, and thus size their investments based on the most likely future outcomes.