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 proceedingConference contributionpeer-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 languageEnglish
Title of host publicationProceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages329-334
Number of pages6
ISBN (Electronic)9781728116914
DOIs
StatePublished - Oct 2019
Externally publishedYes
Event7th International Engineering, Sciences and Technology Conference, IESTEC 2019 - Panama City, Panama
Duration: 9 Oct 201911 Oct 2019

Publication series

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

Conference

Conference7th International Engineering, Sciences and Technology Conference, IESTEC 2019
CountryPanama
CityPanama City
Period9/10/1911/10/19

Keywords

  • Credit history
  • Data analysis
  • Data science
  • Evaluation model
  • Payment capacity
  • Rural saving bank

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