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To focus on new and emerging areas of research and education, Centres of Excellence have been established within the Institute. These ‘virtual' centres draw on resources from its stakeholders, and interact with them to enhance core competencies

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IIMB Management Review

Journal of Indian Institute of Management Bangalore

IIM Bangalore offers Degree-Granting Programmes, a Diploma Programme, Certificate Programmes and Executive Education Programmes and specialised courses in areas such as entrepreneurship and public policy.

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About IIMB

The Indian Institute of Management Bangalore (IIMB) believes in building leaders through holistic, transformative and innovative education

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Prof. Pulak Ghosh to present paper titled ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’ on Dec 23 as part of IIMB Chair of Excellence & Endowed Chair Seminar Series

15 December, 2020, Bengaluru: Professor Pulak Ghosh of the Decision Sciences area, IIM Bangalore and IIMB Chair of Excellence, will present a paper titled, ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’, on December 23 (Wednesday), 2020, from 05.00 pm to 06.00 pm, as part of the IIMB Chair of Excellence and Endowed Chair Seminar Series.

Please note:
Seminar Link: https://iim-b.zoom.us/j/93773358138;
ID: 937 7335 8138;
Passcode: 761701.

Abstract of paper: The study uses unique and proprietary data from a large Fintech lender to analyze whether alternative data captured from an individual’s mobile phone (mobile/social footprint) can substitute for traditional credit bureau scores and improve financial inclusion. Variables that measure a borrowers’ digital presence, such as the number and types of apps installed, measures of social connections and borrowers’ ‘deep social footprints’ based on call logs, significantly improve default prediction and outperform the credit bureau score. Using machine learning-based prediction counterfactual analysis, the research finds that alternate credit scoring based on the mobile and social footprints can expand credit access for individuals who lack credit scores without adversely impacting the default outcomes. It is found that the marginal benefit of using alternative data for credit decisions is likely to be higher for borrowers with low levels of income and education, as well as for borrowers residing in regions with low levels of financial inclusion.

Add to Calendar 2020-12-23 05:30:00 2025-05-12 00:32:11 Prof. Pulak Ghosh to present paper titled ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’ on Dec 23 as part of IIMB Chair of Excellence & Endowed Chair Seminar Series 15 December, 2020, Bengaluru: Professor Pulak Ghosh of the Decision Sciences area, IIM Bangalore and IIMB Chair of Excellence, will present a paper titled, ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’, on December 23 (Wednesday), 2020, from 05.00 pm to 06.00 pm, as part of the IIMB Chair of Excellence and Endowed Chair Seminar Series. Please note: Seminar Link: https://iim-b.zoom.us/j/93773358138; ID: 937 7335 8138; Passcode: 761701. Abstract of paper: The study uses unique and proprietary data from a large Fintech lender to analyze whether alternative data captured from an individual’s mobile phone (mobile/social footprint) can substitute for traditional credit bureau scores and improve financial inclusion. Variables that measure a borrowers’ digital presence, such as the number and types of apps installed, measures of social connections and borrowers’ ‘deep social footprints’ based on call logs, significantly improve default prediction and outperform the credit bureau score. Using machine learning-based prediction counterfactual analysis, the research finds that alternate credit scoring based on the mobile and social footprints can expand credit access for individuals who lack credit scores without adversely impacting the default outcomes. It is found that the marginal benefit of using alternative data for credit decisions is likely to be higher for borrowers with low levels of income and education, as well as for borrowers residing in regions with low levels of financial inclusion. IIM Bangalore IIM Bangalore communications@iimb.ac.in Asia/Kolkata public
23 Dec 2020

Prof. Pulak Ghosh to present paper titled ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’ on Dec 23 as part of IIMB Chair of Excellence & Endowed Chair Seminar Series

Add to Calendar 2020-12-23 05:30:00 2025-05-12 00:32:11 Prof. Pulak Ghosh to present paper titled ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’ on Dec 23 as part of IIMB Chair of Excellence & Endowed Chair Seminar Series 15 December, 2020, Bengaluru: Professor Pulak Ghosh of the Decision Sciences area, IIM Bangalore and IIMB Chair of Excellence, will present a paper titled, ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’, on December 23 (Wednesday), 2020, from 05.00 pm to 06.00 pm, as part of the IIMB Chair of Excellence and Endowed Chair Seminar Series. Please note: Seminar Link: https://iim-b.zoom.us/j/93773358138; ID: 937 7335 8138; Passcode: 761701. Abstract of paper: The study uses unique and proprietary data from a large Fintech lender to analyze whether alternative data captured from an individual’s mobile phone (mobile/social footprint) can substitute for traditional credit bureau scores and improve financial inclusion. Variables that measure a borrowers’ digital presence, such as the number and types of apps installed, measures of social connections and borrowers’ ‘deep social footprints’ based on call logs, significantly improve default prediction and outperform the credit bureau score. Using machine learning-based prediction counterfactual analysis, the research finds that alternate credit scoring based on the mobile and social footprints can expand credit access for individuals who lack credit scores without adversely impacting the default outcomes. It is found that the marginal benefit of using alternative data for credit decisions is likely to be higher for borrowers with low levels of income and education, as well as for borrowers residing in regions with low levels of financial inclusion. IIM Bangalore IIM Bangalore communications@iimb.ac.in Asia/Kolkata public

15 December, 2020, Bengaluru: Professor Pulak Ghosh of the Decision Sciences area, IIM Bangalore and IIMB Chair of Excellence, will present a paper titled, ‘Financial Inclusion and Alternate Credit Scoring: Role of Big Data and Machine Learning in Fintech’, on December 23 (Wednesday), 2020, from 05.00 pm to 06.00 pm, as part of the IIMB Chair of Excellence and Endowed Chair Seminar Series.

Please note:
Seminar Link: https://iim-b.zoom.us/j/93773358138;
ID: 937 7335 8138;
Passcode: 761701.

Abstract of paper: The study uses unique and proprietary data from a large Fintech lender to analyze whether alternative data captured from an individual’s mobile phone (mobile/social footprint) can substitute for traditional credit bureau scores and improve financial inclusion. Variables that measure a borrowers’ digital presence, such as the number and types of apps installed, measures of social connections and borrowers’ ‘deep social footprints’ based on call logs, significantly improve default prediction and outperform the credit bureau score. Using machine learning-based prediction counterfactual analysis, the research finds that alternate credit scoring based on the mobile and social footprints can expand credit access for individuals who lack credit scores without adversely impacting the default outcomes. It is found that the marginal benefit of using alternative data for credit decisions is likely to be higher for borrowers with low levels of income and education, as well as for borrowers residing in regions with low levels of financial inclusion.