The current housing deficit in India stands at 19 million units which will only double to 38 million units by 2030, if nothing is done about it. To address and control this housing deficit, the Government has subsidized housing by expanding institutional credit flow that will fulfil the housing needs of the urban poor through Credit Linked Subsidy Scheme (CLSS) under the Pradhan Mantri Awas Yojana (PMAY) – Housing for All Mission. However, affordable and adequate housing come with their own set of challenges. And, technology can help bridge the gap between low-income borrowers and their affordable /adequate housing needs while carving a win-win for borrowers and lending institutions.
Affordability is viewed as a ratio of price/rent of housing to income of household. EWS households have an average annual income of 3,00,000 and can afford a housing unit of roughly 300 sq.ft. Whereas LIG households have an annual income of 3,00,001 – 6,00,000 and can afford a housing unit between 300-600 sq. ft. (MHUPA CLSS Leaflet). High land prices, cost of construction, transaction costs, volume of transactions, taxes and legal margin, profit margin of private operators combined with the above mentioned limited income as well as the challenges in credit assessment of EWS and LIG segments, means that millions of Indian households currently live in cramped, poorly constructed houses with little or no access to housing finance.
The Government is pushing for Aadhar based eKYC and cKYC for All. Again, under CLSS, for identification of beneficiary of housing finance, an Aadhar card/voter id is mandatory. According to the UIDAI Enrolment Update, Aadhar Saturation in adults as of May 2017 to be > 99% across all the states in India. However, these segments may not have filed an ITR, may not have a bank account and chances are have never gone through a structured and formal lending process before which can remain a challenge in eKYC despite a very impressive Aadhar Card saturation in the country. This implies that a traditional credit assessment that works in case of a regular salaried workforce may not translate well for a member of the EWS or LIG Segment. It is imperative for lending institutions to devise innovative means to evaluate the credit worthiness of low-income borrowers to ensure reliable credit assessment. For example, for borrowers living in rural and remote locations, non-traditional data points such as ailing parents, no. of dependents, current state of dwelling, manual background check from neighbors and local police station, need to be covered. Hand-held devices can not only assist in capturing these data points but will also facilitate real-time analysis based on the collected data. The data collected can be structured as digital checklists, which would give a clear indication of the borrower’s score for the individual items in the checklist to arrive at an overall credit rating for the borrower.
For EWS and LIG segments, under CLSS, a subsidy is only applicable to loan amount up to 6 Lakhs. Any amount above 6 Lakhs will be subject to a normal interest rates. This limit on the subsidy keeps the average loan amount for affordable houses low; therefore, the only way lenders can dispense loans profitably to these segments is by keeping the cost of transactions low. For a lender, multiple physical visits of the sales person and credit assessor, background check, document collection and management and the physical brick and mortar infrastructure required to support these above-mentioned processes, makes the cost of transaction practically unviable. This implies that technology needs to structure the workflow, bring down the back and forth between customer and branch, avoid duplicate data entry, reduce paper flow and reduce physical branch infrastructure requirement per customer. In addition, technology can be used to precipitate decision making progressively putting a multi-filter approach thereby reducing the time to approve or reject a loan request, then the overall cost of acquisition of a customer, can be brought down tremendously.
Given the nature of the customer segment, lending institutions need to go to the customer and not vice-versa – this has several ramifications on the business process, customer service, turn around times, credit decision process and data points, and all these factors lead to specific technology requirements needed to effectively and profitably cater to this business.
“Looking at the average ticket size of 4.1 lakhs, we expect to witness more and more small banks and micro-lenders getting in affordable housing lending in the coming years,” Cibil chief operating officer Harshala Chandorkar has said in an interview. Again, with The National Housing Board (NHB) giving licenses to a number of HFCs (List of HFCs registered with NHB as of 19th Feb 2016), the affordable housing sector is booming. HFCs are expected to grow at a CAGR of 40 per cent over the next four years. According to a Crisil report, a quarter of home loans today are for affordable housing, the growth rate has led to an increase in the market share of new pure-play HFCs in the housing segment from 10% in March last year to 15% in March 2017 and new HFCs have seen their assets under management (AUMs) jump 50% from March 2016 to March 2017.
With such tremendous growth in the sector – only people, who will be able to do reliable credit assessments for this customer segment, minimize transactions costs and manage high volumes in loans, will last. The Government is certainly taking steps to fill the supply and demand gap for low-income borrowers but lending institutions need to evaluate feasibility of catering to EWS and LIG segments with their current infrastructure. It is here, where Technology will play the most important role in forming the support for Banks and HFCs to not only tackle the demand-supply deficit but also keep up with the growth of affordable housing sector in the time to come.