Loan Applicant Anomaly Detection

Anomaly detection, also known as outlier detection, involves identifying data points or patterns that deviate significantly from the expected or "normal" behavior within a dataset. Anomaly detection in loan applicants is an important topic in the financial industry to reduce the risk of de...

Full description

Bibliographic Details

Published in:	2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE) pp. 469 - 474
Main Authors:	Maming, Nurhuda, Chaimontree, Santhana, Lim, Apiradee
Format:	Conference Proceeding
Language:	English
Published:	IEEE 19-06-2024
Subjects:	Anomaly detection Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Forestry Isolation Forest (iForest) k-Nearest Neighbor (k-NN) Labeling Loan applicant Local Outlier Factor (LOF) Noise Predictive models Profitability Reviews Risk management
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!