Monte Carlo Simulation Study Of Regression
Models Used To Estimate The Credit Banking Risk
In Home Equity Loans
Author(s)
D. Morales, A. P´erez-Mart´ın & M. Vaca
Abstract
The banking structure of today is quite damaged. This happened because the
industry was not able to foresee the different risks that surrounded it. Of the
group of risks associated with the business of banking activity, the risk of credit in
many occasions accounts for 60%. The risk of credit arises when there exists the
possibility of suffering a loss due to the breach of the other party to assume the
payment or payments. The default originates a loss for the entity that climbs not
only to the none recovered amount, but also to the expenses incurred in the process.
The uncertain nature of the risk does mean that this risk is measured through the
unexpected loss, which coincides statistically with the standard deviation. This
is why statistical methods are needed to enable the prediction of bank credit
risk (default and non-payment) in home equity loans through estimates based
on statistical models (also called techniques of ‘credit scoring’), to improve the
currently available methods.
Keywords: credit scoring, credit risk, home equity loans, linear mixed models,
Monte Carlo.
Keywords
Keywords: credit scoring, credit risk, home equity loans, linear mixed models,
Monte Carlo.
Related Book
Other papers in this volume
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