The Accenture FinTech Lab Experiment

Originally Published Spring 2018

Last year Accenture invited us to spend autumn in Hong Kong with the innovation teams at BNP Paribas, Bank of America Merrill Lynch, Commonwealth Bank of Australia, Credit Suisse, Goldman Sachs, HSBC, J.P. Morgan, Macquarie Group, Morgan Stanley, Nomura and Sun Life Financial. The focus was on defining the market fit of our "distributed ledger of probabilities" forecasting technology within the Financial Services & Insurance Sectors.

The result was a Robo-VC model designed to predict the success of early stage startups.

In Spring 2018 we expanded the model to include Portfolio Modeling, Enterprise Valutions, Investment Risk Profiling and Forecasting ROI.

This simple model produces a predictive forecast of budget/investment requirements, cash flow forecasts and prospective ROI for a digital start-up or R&D project.

The forecasts are based on a complex array of monte carlo simulations remapped from 25 years of tech industry data.

Why do we develop these tools? Because we believe great design is 90% intelligence and 10% styling.

Total Addressable Market Today (Estimated TAM - $Millions)
$

Total Addressable Market in the future (Forecast TAM - $Millions)
$

Total Servicable Market in the future (TSM - % of TAM)
% = $

Estimated Market Share in the future (EMS - % of TSM)
% = $

Roadmap to reach market share

Business Model

Funding Requirements

Seed Round $

A Round $

B Round $

C Round $

D Round $

E Round $

F Round $

G Round $

H Round $

Projected Seed Investor's ROI:

Want to learn more about how our predictive models can help you to grow your business? Then get in touch with us today.

Disclaimer

The use of these calculators, charts, visualisations, data or any information shall be at the user’s sole risk. Such use shall constitute a release and agreement to hold harmless, defend and indemnify Digital Partners from and against any liability (including but not limited to liability for special, indirect or consequential damages) in connection with such use. Such release from and indemnification against liability shall apply in contract, tort (including negligence of such party, whether active, passive, joint or concurrent), strict liability, or other theory of legal liability; provided, however, such release, limitation and indemnity provisions shall be effective to, and only to, the maximum extent, scope or amount allowable by law.

Questions of accuracy

Tymbals is an experiment in machine learning and statistical modelling of small data pools. Tymbals is still under development. It is still learning. Tymbals is Beta - i.e. Pre-release.

The probabilities and outputs (e.g. calculators, charts, visualisations) will evolve and change as the system ingests more data.

Tymbals is a probability model. The results generated by Tymbals are market estimates based on the cummulative value of the data within the distributed data pools.

Privacy

All data inputs are automatically added to the learning pool from which Tymbals models are generated.