There is no platform where the expense analysis, financial advice and access to micro-credit is simple and easy for underbanked India which also preserves the privacy of their financial data.
We intend to serve the credit needs of 400 million Indians and our goal is to become a key component in the financial data value chain.
Our solution builds on the consent based data access framework of Account Aggregators (AA).
Our solution runs on novel privacy-preserving technologies based ML models to protect user data from malicious attacks. No P2P lending firm has been able to scale because of a lack of financial profile building data which is available for the first time thanks to AA framework also enabling better micro-credit lending.
A major component of our platform is the P2P lending service which will enable people with no traditional credit history to build a solid credit record to gain access to institutional credit to fulfill their aspirations.
We have developed ML models which use privacy-preserving techniques to predict future cash flows of our consumers and scores them.
We had a lot of problems with mostly AA sandbox apis being undercooked and tedious to implement. We felt they were not even near to production grade. Another challenge we faced was in running ml models in almost real time for the user to have a seamless experience.
We believe slow response from servers will be a big bottle neck when in production. Data requests for thousands of days will slow everything down.