Data science model for the evaluation of customers of rural savings banks without credit history

Aldo David Caceres Gonzales; Fabio Leonel Paucar Villantoy; David Santos Mauricio Sanchez

doi:10.1109/IESTEC46403.2019.00067

Data science model for the evaluation of customers of rural savings banks without credit history

Aldo David Caceres Gonzales, Fabio Leonel Paucar Villantoy, David Santos Mauricio Sanchez

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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
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	https://doi.org/10.1109/IESTEC46403.2019.00067
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

Conference

Conference	7th International Engineering, Sciences and Technology Conference, IESTEC 2019
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

Access to Document

10.1109/IESTEC46403.2019.00067

Cite this

Gonzales, A. D. C., Villantoy, F. L. P., & Sanchez, D. S. M. (2019). Data science model for the evaluation of customers of rural savings banks without credit history. In Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 (pp. 329-334). Article 8943666 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IESTEC46403.2019.00067

Gonzales, Aldo David Caceres ; Villantoy, Fabio Leonel Paucar ; Sanchez, David Santos Mauricio. / Data science model for the evaluation of customers of rural savings banks without credit history. Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 329-334 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019).

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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.",

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Gonzales, ADC, Villantoy, FLP & Sanchez, DSM 2019, Data science model for the evaluation of customers of rural savings banks without credit history. in Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019., 8943666, Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 329-334, 7th International Engineering, Sciences and Technology Conference, IESTEC 2019, Panama City, Panama, 9/10/19. https://doi.org/10.1109/IESTEC46403.2019.00067

Data science model for the evaluation of customers of rural savings banks without credit history. / Gonzales, Aldo David Caceres; Villantoy, Fabio Leonel Paucar; Sanchez, David Santos Mauricio.
Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 329-334 8943666 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Gonzales ADC, Villantoy FLP, Sanchez DSM. Data science model for the evaluation of customers of rural savings banks without credit history. In Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 329-334. 8943666. (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019). doi: 10.1109/IESTEC46403.2019.00067

Data science model for the evaluation of customers of rural savings banks without credit history

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