There was not one but several ideas, mostly coming from multinational corporate clients, that combined, have led to the creation of Fennech. In no particular order, there was a recurring message coming from CFO’s, treasurers and financial controllers from corporates of all sizes:
Despite normalisation and good capabilities from TMS (Treasury Management Systems), the corporates felt their technical relationship with their banks was not optimal. Too many bank accounts, too much paperwork, not enough reactivity, not enough self-service, and flexibility.
They reported difficulties to embrace innovation. As most corporates are having relationships with many banks, they often have difficulties to implement the innovation those can propose. Implementing a new product or service from one of them means creating another process. The corporates’ capacity to manage several different processes for several different banks is limited, and that is the reason why they are so much looking after bank agnostic normalisation.
Finally, legacy IT and lack of integration of treasury and controlling functions in the usual accounting base ERP deployments. Those functions very often can not find in real-time the accurate and relevant data they need, and therefore are building additional or parallel tools and processes, mostly on excel, to compensate. Even for critical activities like cash forecasting and liquidity management, that drive funding, hedging, and investments. The result is manual, not accurate, not real-time, not resilient, and costly.
So, our idea has been “let’s empower the corporates and commoditise the banks.”
We have built with F3 (Fennech Financial Framework), a secure, robust bank agnostic digital and open platform, that fixes all of the above-mentioned issues. To do so, we have amongst others developed “digital contracts” at the core of F3. Those are complex objects -populated directly and automatically from real contractual documents- are self-executable objects, similar to smart contracts but outside of blockchain and without any need for tokenisation. The best of all worlds.
The clients can ultimately deploy, manage, and control their In-house bank, with all their processes operating end-to-end and automated. The use of machine learning makes the implementation fairly intuitive, and AI helps the clients and users to focus quickly on the real issues and key strategic decisions.
