Credit Risk Modelling is a process or processes used by financial institutions to determine and manage the risk of persons defaulting on loans and failing to make the necessary payments. They carry many titles which depends on the developer, type of loan they were developed for and role.
Credit Risk Modelling has developed to a high degree of complexity in carrying out its functions in assisting financial institutions in determining the possibility or probability of applicants ability to repay loans. It has to take into consideration the probability of default, the estimated value of the loan at the time of the default, at the time of the default what the exposure is most likely to be and the cost associated with the default.
In order to accurately predict or form a relatively acceptable assessment of the possibility of a person defaulting, lending institutions balance historical banking data to estimate the behavioral patterns of applicants in the future. The historical data typically focused on patterns in payment history, levels of indebtedness to the length of credit history.
The ultimate purpose of credit risk modelling is to capture factors such as utility payments, rent and charitable contributions in combination with credit scores to provide an overall image of the transactional data, making it easier for institutions to make informed decisions regarding the application for the loan because now the assets and liabilities, along with the consumer’s information on deposits and non-income data will be in this report.
Generally there are two main categories of credit risk modelling, these categories are structural and reduced form models. Structural models are typically used to calculate the profits that a company would made from defaults based on its assets and liabilities. If the debt the company has is larger than the estimated market value of its assets then the company is said to have defaulted. Reduced Form models uses a discreet probability process, that takes into account random caused of default due to external factors.
Within the above stated categories there are even more groups of model types which would fall under either category. Such as the FICO score models, origination scoring, existing loan scoring and credit model function.
In today’s society the way in which persons spend money is changing, persons are opting to rent homes, rather than buy one, ride bikes or share vehicles rather than buy a car. This behavior has resulted in the lack of accessible credit history, however, these individuals have banking and non-credit history that can give them better access to credit.
Bearing this in mind the Credit Risk Modelling is changing to encompass all of this information leading to greater access to the credit markets and the ability for lending institutions to offer suitable products.