Abstract
The Data Science Model for the evaluation of clients of rural savings banks seeks to increase the credits granted to potential clients with or without a credit history and who possess or lack income and expense support. The evaluation consists of entering your identity document at the risk centers, measuring your income, expenses with or without supporting documents. Pilot tests were conducted in one of the agencies of the rural saving bank Edpyme Raiz for 3 weeks, obtaining favorable results and increasing from 10 to 30% the number of credits obtained per official when using the evaluation model and, if not, when the The result of the evaluation of the client is not favorable, it is suggested some recommendations to be able to approve again.
Original language | English |
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Title of host publication | Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 329-334 |
Number of pages | 6 |
ISBN (Electronic) | 9781728116914 |
DOIs | |
State | Published - Oct 2019 |
Event | 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 - Panama City, Panama Duration: 9 Oct 2019 → 11 Oct 2019 |
Publication series
Name | Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 |
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Conference
Conference | 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 |
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Country/Territory | Panama |
City | Panama City |
Period | 9/10/19 → 11/10/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Credit history
- Data analysis
- Data science
- Evaluation model
- Payment capacity
- Rural saving bank