Fintech and Credit Scoring for the Millennials: Evidence using Mobile and Social Footprints

Agarwal, Sumit; Alok, Shashwat; Ghosh, Pulak; Gupta, Sudip

doi:10.2139/ssrn.3507827

Cited by 21 publications

(25 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such data include “mobile footprints,” which refer to the households’ online behaviour that are captured from their mobile phones. Using data from one of the largest FinTech lenders in India, Agarwal et al (2020) found that the mobile footprint of an individual outperforms traditional credit bureau scores in predicting loans approvals and defaults. With deep digital information of the applicant’s social connections or type of applications that they used, FinTech firms can proxy for otherwise hard to quantify and unobservable aspects of individual behaviour.…”

Section: Lendingmentioning

confidence: 99%

FinTech and household finance: a review of the empirical literature

Agarwal

Chua

2020

CFRI

Self Cite

View full text Add to dashboard Cite

PurposeThis paper reviews recent advances in the empirical literature of FinTech and household finance.Design/methodology/approachWe survey the effects of FinTech on three different aspects of household finance: payments, lending and portfolio decisions. Specifically, we examine the impact of digital payments, mobile money, FinTech lending, marketplace lending, robo-advising and crowd-funding.FindingsStudies suggest that FinTech has positively benefited households by increasing consumption and borrowing. This allows them to smoothen their consumption across time. Furthermore, there is an improvement in their portfolio diversification. Nonetheless, there is also evidence that certain households overconsume and borrow beyond their means.Originality/valueDespite the importance of this topic, there has been a lack of empirical evidence until recently. In this paper, we take stock of the empirical evidence in the literature through the lens of household finance

show abstract

Section: Lendingmentioning

confidence: 99%

FinTech and household finance: a review of the empirical literature

Agarwal

Chua

2020

CFRI

Self Cite

View full text Add to dashboard Cite

show abstract

“…Our results also emphasize an unintended role of robo-advising tools (D'Acunto and Rossi (2020)), which are diffusing around the world to facilitate consumers' spending ), saving (Gargano and Rossi (2020)), borrowing (Agarwal et al (2019)), and lending decisions. We show that such tools can help discriminating agents avoid the financial losses they face when making culturally biased choices.…”

Section: Introductionmentioning

confidence: 51%

“…9 This setting is reminiscent of the recent literature on FinTech adoption in developing countries (e.g., see Agarwal et al (2019); Crouzet, Gupta, and Mezzanotti (2019); Higgins (2019); D'Andrea and Limodio ( 2019)).…”

Section: Borrowers' Screening By the Platformmentioning

confidence: 99%

How Costly are Cultural Biases?

D’Acunto

Ghosh

Jain³

et al. 2020

SSRN Journal

Self Cite

View full text Add to dashboard Cite

“…The potential to assess the creditworthiness of people without a conventional credit history can improve accessibility to credit markets. Another study conducted by Agarwal et al (2019) also investigates the effectiveness of mobile footprints and finds predictive power that outperforms traditional credit scores in assessing loan approvals and possible defaults.…”

Section: Literature Reviewmentioning

confidence: 99%

Asia Small and Medium-Sized Enterprise Monitor 2020:

2020

View full text Add to dashboard Cite

The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent.ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned.By making any designation of or reference to a particular territory or geographic area, or by using the term "country" in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.

show abstract

Fintech and Credit Scoring for the Millennials: Evidence using Mobile and Social Footprints

Cited by 21 publications

References 30 publications

FinTech and household finance: a review of the empirical literature

FinTech and household finance: a review of the empirical literature

How Costly are Cultural Biases?

Asia Small and Medium-Sized Enterprise Monitor 2020:

Contact Info

Product

Resources

About