This undoubtedly impacted the rural economy, as the growth rate in terms of gross value added (GVA) in agriculture declined sharply from 11.6 per cent in 2016-17 to almost one third at 4.6 per cent in 2017-18, according to data from the Central Statistics Office (CSO).
Around two years ago, L&T Rural Finance decided to rejig its business model with an emphasis on data intelligence. While many companies
use data to inform their business strategy teams, the company chose to do the opposite.
A data intelligence system today conducts all rural lending tasks and monitors more than 4 million micro-loan customers and the overall 5 million rural customer base. The idea is to improve credit standards to improve portfolio quality and control operating expenses.
“The credit algorithms that we design and keep refining is the only way we write credit. These algorithms helps give 40 per cent better portfolio and credit decisions than human under-writers,” says Sunil Prabhune Chief Executive of LTFHs Rural business.
While lending is done entirely by an data intelligence system, manual intervention and individual staff discretion is reduced to a minimal.
“The emphasis by staff at the front-line should be on building relationships and acquiring new business and not on taking subjective or bias credit calls,” he said.
The idea is to track the credit quality of their customers and better understand risk, while improving the overall portfolio quality.
Front-line staff, working across the 1,200 points of presence in the country, have been asked to concentrate more on building relationships and develop local knowledge that can be leveraged to improve the company’s data intelligence capabilities.
The micro-loan lending book has grown by 133 per cent on a year-on-year basis to Rs 91 billion for the quarter ended June 2018, from Rs 39 billion at the end of the same period in the previous year.
With across the country, the company’s management says 40 per cent of its customers are new to credit, while half of them only have a credit exposure to LTFH.
"Demonetisation and the subsequent cash crunch had a impact mainly on the micro-loans business, but the continuous macroeconomic shocks in 2017 have been a “blessing in disguise” for the industry," said Prabhune.
Across the financial services industry, financial year 2017 saw collections decreasing and non-performing assets rising, as the cash crunch led to delayed loan repayments. But thanks to technology, LTFH's rural lending business has grown on the back of superior collection mechanisms and early warning signals.
Gross non-performing assets in the rural lending book have shrunk from Rs 12 billion in June 2017 to Rs 9.1 billion in June 2018.
Loans in the micro-loans segment can be disbursed within two minutes.
On farm loan waivers for example, Prabhune said, “We have a contrarian view, wherever the waiver has been clearly communicated it has had in general two positive impacts. It increases primary demand for assets in the rural areas, as it puts more money in the pockets of farmers, and second it results in enhanced collection efficiencies.”
Net profit for the rural business off LTFH has grown by 86 per cent to Rs 1.93 billion at the end of June 2018, as against Rs 1.04 billion during the same period the previous year.