Welcome to the InfoSci Platform
Reference Hub8
Artificial Intelligence and SHGs: Enabling Financial Inclusion in India

Artificial Intelligence and SHGs: Enabling Financial Inclusion in India

Vinay Kandpal, Osamah Ibrahim Khalaf
Copyright: © 2020 |Pages: 13
ISBN13: 9781799850687|ISBN10: 1799850684|ISBN13 Softcover: 9781799852759|EISBN13: 9781799850694
DOI: 10.4018/978-1-7998-5068-7.ch015
Cite Chapter Cite Chapter

MLA

Kandpal, Vinay, and Osamah Ibrahim Khalaf. "Artificial Intelligence and SHGs: Enabling Financial Inclusion in India." Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks, edited by K. Martin Sagayam, et al., IGI Global, 2020, pp. 291-303. https://doi.org/10.4018/978-1-7998-5068-7.ch015

APA

Kandpal, V. & Khalaf, O. I. (2020). Artificial Intelligence and SHGs: Enabling Financial Inclusion in India. In K. Sagayam, B. Bhushan, A. Andrushia, & V. Albuquerque (Eds.), Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks (pp. 291-303). IGI Global. https://doi.org/10.4018/978-1-7998-5068-7.ch015

Chicago

Kandpal, Vinay, and Osamah Ibrahim Khalaf. "Artificial Intelligence and SHGs: Enabling Financial Inclusion in India." In Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks, edited by K. Martin Sagayam, et al., 291-303. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-5068-7.ch015

Export Reference

Mendeley
Favorite

Abstract

For inclusive growth and sustainable development of SHG and women empowerment, there is a need to provide an environment to access quality services from financial and non-financial agencies. While banks cannot reach all people through a ‘brick and mortar' model, new and advanced banking technology has enabled financial inclusion through branchless banking. By using artificial intelligence in banking, banks have a cost-effective and efficient solution to provide access to services to the financially excluded. Digital technology improves the accessibility and affordability of financial services for the previously unbanked or underbanked individuals and MSMEs. A big data-driven model can also be helpful for psychometric evaluations. Several psychometric tools help evaluate the applicant's answers which aid to capture information that can help to predict loan repayment behavior, comprising applicants' beliefs, performance, attitudes, and integrity.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.