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Creditworthiness Assessment Using Natural Language Processing
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Author(s): Somya Goyal (Delhi Technological University, India)and Arti Saxena (Manav Rachna International Institute of Research and Studies, India)
Copyright: 2021
Pages: 22
Source title:
Deep Natural Language Processing and AI Applications for Industry 5.0
Source Author(s)/Editor(s): Poonam Tanwar (Manav Rachna International Institute of Research and Studies, India), Arti Saxena (Manav Rachna International Institute of Research and Studies, India)and C. Priya (Vels Institute of Science, Technology, and Advanced Studies, India)
DOI: 10.4018/978-1-7998-7728-8.ch007
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Abstract
NLP is a wide and quickly developing segment of today's new digital technology, which falls under the domain of artificial intelligence. Alternative approaches for qualifying and quantifying an individual's creditworthiness have emerged in recent years as a result of recent advancements in AI. Banks and creditors may use AI to rate potential borrowers' creditworthiness based on alternative data, such as social media messages and internet usage, such as which websites people visit and what they buy from e-commerce stores. These digital footprints may show whether or not an individual is able to repay their debts. In this chapter, how the approaches of NLP could offer financial solutions to unbanked communities is explored. This chapter includes the use of various machine learning algorithms and deep learning to find the most accurate credit score of a user. Since NLP is less intrusive than providing direct access to a person's entire contact list or a social media site, it is a more accessible way to measure risk while still having the potential to target a larger audience.
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