TY - JOUR
T1 - Evaluating Financial Inclusion in Peru
T2 - A Cluster Analysis Using Self-Organizing Maps
AU - Talavera, Alvaro
AU - Maehara, Rocío
AU - Benites, Luis
AU - Arriaga, Benjamin
AU - Aybar-Flores, Alejandro
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/12
Y1 - 2024/12
N2 - This study evaluates financial inclusion in Peru through self-organizing maps. Financial inclusion is a multidimensional issue of great importance on the global agenda and continues to concern various actors internationally. In this context, the objective is to assess the financial inclusion situation in the country and determine how self-organizing maps can complement standard models for this purpose. The empirical aim is to demonstrate how this technique can help identify priority areas and vulnerable groups, thus facilitating decision-making and policy design to improve the access to and use of financial services among Peruvian consumers by finding clearly defined profiles that allow the identification of potential problems within each category. This makes it possible to create customized strategies for each group, such as addressing the financial inclusion barriers faced by rural residents, compounded by low income and educational levels.
AB - This study evaluates financial inclusion in Peru through self-organizing maps. Financial inclusion is a multidimensional issue of great importance on the global agenda and continues to concern various actors internationally. In this context, the objective is to assess the financial inclusion situation in the country and determine how self-organizing maps can complement standard models for this purpose. The empirical aim is to demonstrate how this technique can help identify priority areas and vulnerable groups, thus facilitating decision-making and policy design to improve the access to and use of financial services among Peruvian consumers by finding clearly defined profiles that allow the identification of potential problems within each category. This makes it possible to create customized strategies for each group, such as addressing the financial inclusion barriers faced by rural residents, compounded by low income and educational levels.
KW - clustering
KW - financial inclusion
KW - machine learning
KW - self-organizing maps
UR - http://www.scopus.com/inward/record.url?scp=85213471354&partnerID=8YFLogxK
U2 - 10.3390/jrfm17120549
DO - 10.3390/jrfm17120549
M3 - Article
AN - SCOPUS:85213471354
SN - 1911-8074
VL - 17
JO - Journal of Risk and Financial Management
JF - Journal of Risk and Financial Management
IS - 12
M1 - 549
ER -