Predicting microfinance loan default
Microfinance lending institutions can use the following predictors to avoid bad loans : Marital status (single individuals are more prone to defaults). Time period of loan (longer loans are prone to higher default rate). Interest rate (very high interest rates are likely to resul in loan default).
Main Authors: | Kumar, Senthil, Aslam, Mohammad |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/34530/1/Predicting%20microfinance%20loan%20default.CITREX2021..pdf |
Similar Items
-
Impact evaluation of microfinance: A HEPM perspective
by: Kumar, Senthil, et al.
Published: (2023) -
indoor Air Quality (IAQ) and Related Risk Factors for Sick Building Syndrome (SBS) at the Office and Home: A Systematic Review
by: Norsaffarina, Aziz, et al.
Published: (2023) -
Using artificial neural network to predict power plant turbine hall key cost drivers
by: Ng, Choo Geon
Published: (2007) -
Mechanisms for addressing the impact of covid-19 on infrastructure projects
by: S. S., King, et al.
Published: (2021) -
In-service piping inspection work-aid tool for process industries
by: Jia Chien, Lee, et al.
Published: (2021)