TY - GEN
T1 - Model to optimize the Loss Ratio Index of Valued Documents in a retail company in Lima through Business Intelligence and Machine Learning
AU - Olortegui-Pinto, Elemir
AU - Cespedes-Blanco, Carlos
AU - Torres, Carlos
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The retail sector in Peru has experienced significant growth driven by economic expansion and the increased purchasing power of the middle class. Companies such as Ripley SAC, a department store chain, have expanded their presence and diversified their offerings. However, the company faces a challenge in optimizing the Loss Ratio Index (IRL) of valued documents, such as insurance policies and surety bonds, which are currently below the desired level. This research aims to develop and implement a model to optimize the IRL in retail companies using Business Intelligence (BI) and Machine Learning (ML) methodologies. The study is based on historical and real-time data on sales, claims, policies, and other relevant factors. The approach includes BI techniques for data exploration and visualization, identifying patterns and trends, and ML techniques to predict the Loss Ratio Index of valued documents. The implementation of these strategies seeks to reduce insurance losses and increase profitability.
AB - The retail sector in Peru has experienced significant growth driven by economic expansion and the increased purchasing power of the middle class. Companies such as Ripley SAC, a department store chain, have expanded their presence and diversified their offerings. However, the company faces a challenge in optimizing the Loss Ratio Index (IRL) of valued documents, such as insurance policies and surety bonds, which are currently below the desired level. This research aims to develop and implement a model to optimize the IRL in retail companies using Business Intelligence (BI) and Machine Learning (ML) methodologies. The study is based on historical and real-time data on sales, claims, policies, and other relevant factors. The approach includes BI techniques for data exploration and visualization, identifying patterns and trends, and ML techniques to predict the Loss Ratio Index of valued documents. The implementation of these strategies seeks to reduce insurance losses and increase profitability.
KW - Business Intelligence
KW - Loss Ratio Index
KW - Machine Learning
KW - Retail companies
UR - https://www.scopus.com/pages/publications/105033500803
U2 - 10.1109/ICALTER69698.2025.11355035
DO - 10.1109/ICALTER69698.2025.11355035
M3 - Contribución a la conferencia
AN - SCOPUS:105033500803
T3 - Proceedings of the 2025 IEEE 5th International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2025
BT - Proceedings of the 2025 IEEE 5th International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2025
A2 - Ramirez, Gianpierre Zapata
A2 - Arias, Heyul Chavez
A2 - Ibanez, Carlos Raymundo
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2025
Y2 - 11 December 2025 through 13 December 2025
ER -