Super-app behavioral patterns in credit risk models: Financial, statistical and regulatory implications

Author:

Roa Luisa,Correa-Bahnsen Alejandro,Suarez Gabriel,Cortés-Tejada Fernando,Luque Maria A.,Bravo CristiánORCID

Funder

Canada Excellence Research Chairs, Government of Canada

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference38 articles.

1. ‘all data is credit data’: Constituting the unbanked;Aitken;Competition & Change,2017

2. Arráiz, I., Bruhn, M., Ortega, C. R. & Stucchi, R. (2017). Are Psychometric Tools a Viable Screening Method for Small and Medium-Size Enterprise Lending? Evidence from Peru. Tech. Rep. 8276, The World Bank.

3. Asian Insights Office (2019). Super apps in financial services: Business models and opportunities. Tech. Rep. sector briefing 81, DBS Group Research.

4. Baesens, B., Roesch, D. & Scheule, H. (2016). Credit risk analytics: Measurement techniques, applications, and examples in SAS. Wiley & SAS Business Series. Wiley, Hoboken, New Jersey.

5. Basel Committee on Banking Supervision (2018). Sound Practices: Implications of fintech developments for banks and bank supervisors. Tech. rep., Bank for International Settlements.

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