Credit default prediction for micro-enterprise financing in India using ensemble models
by Pankaj Kumar Gupta; K.K. Jain
Global Business and Economics Review (GBER), Vol. 26, No. 1, 2022

Abstract: Assessment of default risk for micro-enterprise financing is altogether distinct from the financing of large corporations. Credit assessment officers bear dual pressure from a policy perspective to grant more credit to micro-enterprises and also an internal pressure of minimising default to them. The conventional approach of evaluating borrower-centric default risk to micro-enterprises, which uses the ability to pay criterion, has proven to be irrelevant in the absence of a first-generation potential borrower's financial data implying the need to model a set of variables capable of predicting credit default. We ensemble the findings of the multinomial logistic regression, neural network, and CHAID algorithms using the most significant variables developed from lender's package of credit granting framework for credit default prediction to improve prediction ability. We use a database of 3,013 micro-enterprises obtained from a cluster of micro-enterprises who are first-time borrowers of a financial institution based in Delhi, covering a period from 2007-2010. We find that our model is robust as predictive accuracy results confirm its validity and it can be used by policy-makers and the central bank (RBI), which can change the entire philosophy of financing for micro-enterprises in India.

Online publication date: Tue, 04-Jan-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the Global Business and Economics Review (GBER):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com