DataCultr, a PaaS for consumer lending companies, helps them to provide unsecured loans, at a lower risk, by allowing borrowers to present their newly purchased or existing smartphones as collateral, said Neel Juriasingani, CEO and co-founder of the company.
The mid-to-low income group people in India and other emerging markets live on a meagre income, with zero or limited assets; they generally don’t have assets that can be pledged to get a loan, he said, adding “We understand the utility of a smartphone. It is an important asset and something that people value a lot. So it becomes a smart choice for collateral, additionally, institutional lenders can give away micro-loans without keeping this. At the same time they can control the asset if the borrower defaults.”
DataCultr converts a smartphone into a collateral that borrowers can pledge virtually, and get loans from banks, non-banking financial firms and micro-finance institutions. The platform provides a complete stack to lenders whereby they are able to reduce their risk and cost of servicing on ‘new to credit’ unbanked customers. This platform has features and modules, that not just collateralizes a smartphone but helps reduce risk, cost of collections and frauds.
Moreover, this Delhi-based IoT start-up does this without changing the customer journey or any of the processes laid down by the lender at the retail. For lenders, they need to integrate their loan management systems to DataCultr through simple application program interfaces and automate the entire process. In this way, the lending firms are able to cater to a huge market that they were hitherto not catering to. Coming to the fraud management solution for financial institutions, he said it is imperative to keep checks and balances to mitigate the risk that smartphones as collaterals bring with them. “There will always be people who will want to game the system and ‘break-in’, hence fraud management is critical to the success of the platform. DataCultr is using big data and machine learning to build models to send out alerts and triggers to lenders about potential fraud. Lenders using such models can decide to take actions necessary to mitigate their risks on the loan.”
However, those who do not have access to bank accounts and live in rural areas have to be given attention, Juriasingani said, “Financial literacy is something that we see is critical to bring this huge unbanked population to the financial mainstream. The platform allows these banks to use richer media, in the user’s local language to impart knowledge effectively; the platform also allows them to check for its impact by running quizzes and polls.”