Credit risk prediction in an imbalanced social lending environment

04/28/2018
by   Anahita Namvar, et al.
0

Credit risk prediction is an effective way of evaluating whether a potential borrower will repay a loan, particularly in peer-to-peer lending where class imbalance problems are prevalent. However, few credit risk prediction models for social lending consider imbalanced data and, further, the best resampling technique to use with imbalanced data is still controversial. In an attempt to address these problems, this paper presents an empirical comparison of various combinations of classifiers and resampling techniques within a novel risk assessment methodology that incorporates imbalanced data. The credit predictions from each combination are evaluated with a G-mean measure to avoid bias towards the majority class, which has not been considered in similar studies. The results reveal that combining random forest and random under-sampling may be an effective strategy for calculating the credit risk associated with loan applicants in social lending markets.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

04/28/2018

Handling Uncertainty in Social Lending Credit Risk Prediction with a Choquet Fuzzy Integral Model

As one of the main business models in the financial technology field, pe...
10/05/2018

Wide and Deep Learning for Peer-to-Peer Lending

This paper proposes a two-stage scoring approach to help lenders decide ...
02/28/2019

Improving fraud prediction with incremental data balancing technique for massive data streams

The performance of classification algorithms with a massive and highly i...
06/17/2021

MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data

Class-imbalanced data, in which some classes contain far more samples th...
09/03/2019

Minimizing the Societal Cost of Credit Card Fraud with Limited and Imbalanced Data

Machine learning has automated much of financial fraud detection, notify...
09/09/2020

Improving Investment Suggestions for Peer-to-Peer (P2P) Lending via Integrating Credit Scoring into Profit Scoring

In the peer-to-peer (P2P) lending market, lenders lend the money to the ...
11/22/2019

Investigating bankruptcy prediction models in the presence of extreme class imbalance and multiple stages of economy

In the area of credit risk analytics, current Bankruptcy Prediction Mode...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.