There is no doubt that digital lending space has done wonderful job. I being in banking for last 18 years & shifted to loans sourcing in my own venture of helping customers( Rejected by banks) to get credit. To my surprise within these limited period of last nine months i am very much surprised to see how use of CIBIL data is helping & at the same time denying credit to many financially needy ( but imprudent customers - not there fault) . They have clear case of loan to be disbursed but due to poor CIBIL they are straight away no. There is urgent need to develop another credit eligibility matrix consisting of various other parameters which are getting ignored like Reason of default( not just days of default) - specially in case of business's having track record & promoters experience, Nature of job, Family data & there are "n" parameters which are getting ignored & credit being denied & then they have to go to private money lenders to get loan at 3 - 9% monthly pay. This also brings to point that there are enough opportunities for different set of lenders to create huge business in lending space which looks risky due to not updated risk measurement tools/ local know how or customer level knowledge & taking all customers as same due to CIBIL set standard. This is allowing duplication of credit to those who are already have "n" offers & denying to those who needs credit. Still there is lot of work to be done, profit to be earned & capital to be deployed or risk capital to serve the need of vast set of customers. Required is more & newer set of risk management tools/ practice's & people. Use of psychometric tools which can predict better outcome by capturing multiple data sets not just CIBIL score. With so much advancement in DATA mining this should not be issue.
There is no doubt that digital lending space has done wonderful job. I being in banking for last 18 years & shifted to loans sourcing in my own venture of helping customers( Rejected by banks) to get credit. To my surprise within these limited period of last nine months i am very much surprised to see how use of CIBIL data is helping & at the same time denying credit to many financially needy ( but imprudent customers - not there fault) . They have clear case of loan to be disbursed but due to poor CIBIL they are straight away no. There is urgent need to develop another credit eligibility matrix consisting of various other parameters which are getting ignored like Reason of default( not just days of default) - specially in case of business's having track record & promoters experience, Nature of job, Family data & there are "n" parameters which are getting ignored & credit being denied & then they have to go to private money lenders to get loan at 3 - 9% monthly pay. This also brings to point that there are enough opportunities for different set of lenders to create huge business in lending space which looks risky due to not updated risk measurement tools/ local know how or customer level knowledge & taking all customers as same due to CIBIL set standard. This is allowing duplication of credit to those who are already have "n" offers & denying to those who needs credit. Still there is lot of work to be done, profit to be earned & capital to be deployed or risk capital to serve the need of vast set of customers. Required is more & newer set of risk management tools/ practice's & people. Use of psychometric tools which can predict better outcome by capturing multiple data sets not just CIBIL score. With so much advancement in DATA mining this should not be issue.