Credit Scoring Models

Updated on April 12, 2024
Article byPriya Choubey
Edited byPriya Choubey
Reviewed byDheeraj Vaidya, CFA, FRM

What Are Credit Scoring Models?

A credit scoring model refers to a mathematical framework designed to gauge the creditworthiness of a borrower by determining the chances of default. Such a model provides a customized credit score for every individual or firm based on factors like borrowing history, financial position, and customer characteristics.

Credit Scoring Models

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Lenders widely use these models to estimate credit risk levels when offering various financial products, such as personal loans, credit cards, mortgages, auto loans, and unsecured loans. The credit bureaus maintain and provide the information generated by these models. Thus, it serves as a critical input for determining the credit terms and interest rates.

Key Takeaways

  • Credit scoring models refer to statistical and algorithm-based frameworks that assess the potential default risk involved in extending a loan or debt to a particular individual or firm.
  • The various factors contributing to credit risk estimation for a customer include their characteristics, credit history, previous defaults, credit utilization, etc.
  • There are multiple credit scoring models; 90% of users prefer the ones provided by FICO Score. Credit bureaus and merchants also use VantageScore and can develop customized frameworks or use hybrid models.
  • When compared to the traditional methods, these frameworks provide instant, accurate, consistent, and reliable credit information.

Credit Scoring Models Explained

The credit scoring model is a 3-digit number that determines the borrower’s creditworthiness and its capacity for repayment. Lenders design these frameworks using various techniques. Such as algorithms, including machine learning, logistic regression, binning algorithms, linear regression, predictive analytics, and cumulative accuracy profiles. They utilize these frameworks to make informed decisions regarding extending credit and examining loan terms.

These frameworks utilize the data entered by the lending institutions. These are pertaining to an individual’s previous or current borrowings, including their loan amount, payment timeliness, missed or late payments, remaining dues, etc. The other considerable factors used for risk assessment are individual characteristics, types of credit accounts, credit history length, credit utilization, and defaults.

Credit rating agencies and credit bureaus often gather individual credit information. And process it through these models. Hence, to generate credit reports stating the default risk and credit history of the respective person or firm. They then sell this information to the lenders or creditors by charging a certain fee from them. Therefore, a high credit score generally refers to higher chances of getting any financial product and lower chances of default.

However, the biggest challenge arises with the quality of data that serves as an input for processing credit information through these models. More often, such information is manually entered by the people working in lending institutions. Thus, it may only draw an accurate picture if the data is appropriate, biased, complete, and updated. Merchants need to adhere to consumer protection regulations to protect the customer’s privacy while using these frameworks. Also, the selection of a suitable credit scoring model analysis based on individual requirements and purpose is a critical task. Moreover, the merchants preferring a customized model may encounter complexities. Since the designing and quality assurance of such frameworks requires high-level skills and knowledge.

Types

The choice of a credit scoring model depends on the specific needs and purpose of the merchants or lenders. Given below are the various kinds of frameworks available for analyzing the customer’s creditworthiness:

  1. FICO Score: A FICO score is a model developed by the Fair Isaac Corporation. It provides a credit score on a scale from 300 to 850 for every individual or firm. The higher the score (more than 700), the lower the probability of default. It has different versions, like FICO Score 2, 4, 5, 8, 9, 10 and 10T.
  2. VantageScore: The second most popular credit scoring model is VantageScore, which was developed by Experian, Equifax, and TransUnion in 2006. It takes into account various factors such as credit history, duration, and credit utilization to draw a credit score from 300 to 850. It has multiple versions, while VantageScore 3.0 is the best one.
  3. Customized Models: Some merchants and lenders make their models using their database. And they externally gather information about their existing customers or applicants. Such frameworks have a unique algorithm developed to serve the individual purpose.
  4. Hybrid Models: Such frameworks are developed by customizing the standard models to cater to the individual requirements and purposes of the users.
  5. Other Models: Some of the alternative credit scoring models include CE credit score (widely used in China), Credit Xpert credit score, Experian’s National Equivalency Score, TransRisk, and Insurance Score.

Examples

Let us understand the concept better with the help of examples:

Example #1

Let’s look at an instance where a lender evaluates a loan applicant using a scoring model. The application’s payment history is considered by the model. The model looks at whether the applicant has regularly made on-time payments on their current credit accounts. The credit utilization ratio, which evaluates the amount of available credit the applicant is utilizing, is another factor taken into account by the model. An applicant’s credit history is also taken into consideration; a more extended credit history is typically viewed favorably.

The model may evaluate the combination of credit types that the person possesses. These include installment loans, mortgages, and credit cards, in order to determine how well they can handle various financial obligations. Finally, the model takes into account any recent credit applications. Since several applications in a short amount of time could be a sign of financial strain. After being weighted and run through a scoring system, these variables are combined to create a credit score. The lender can use this to make more informed decisions on the terms of the loan and the applicant’s creditworthiness.

Example #2

During the annual convention of the Mortgage Bankers Association in Philadelphia on October 17, 2023, VantageScore presented a white paper that stated that lenders who use the new credit scoring models by 2025, as mandated by regulators, would have access to a massive pool of 2.7 million prospective home buyers.

In its article, the authors implored lenders to adopt the most recent 4.0 iteration of the VantageScore algorithm as soon as possible, claiming that this unexplored pool of potential borrowers might generate up to $1 trillion in new revenue.

In its most recent evaluation, 4.0’s predictive performance, according to the white paper, rated about halfway between vital accuracy and perfect predictive value.

According to the research, the majority of borrowers who would be eligible for a mortgage with a credit score below 4.0 are either “dormant” or “newly scorable.” Conventional grading schemes overlook both categories.

Advantages

Credit scoring models are the lifeline of banks and other lending institutions. Since they serve as robust frameworks for evaluating credit risk beforehand. They offer numerous benefits to the users, as discussed below:

  • Instant Evaluation: Credit scoring models streamline the process of default risk analysis by providing the credit score and history of the customer in minutes, which can never be possible with traditional methods.
  • Accuracy: The credit report generated by these frameworks ensures reliability and accuracy since they are processed using statistical tools and algorithms. Moreover, the chances of human errors and biases are negligible in this approach.
  • Reduces Credit Risk: Such models estimate the creditworthiness of a credit-seeking individual or firm, thus facilitating the lenders’ identification of potential defaulters.
  • Efficiency: Since these frameworks provide quick and reliable information, they are cost-efficient in credit decision-making for the merchants or lenders. Hence, using these methods can bring down the cost of extending loans and advances significantly.
  • Consistency: Credit scoring models provide standard and consistent information related to the credit scores, history, and accounts of the customers based on various algorithms. It, therefore, ensures transparency and fairness without any human biases.
  • Shapes Credit Terms and Decisions: Credit score analysis through these models helps determine the customer’s credit limit, terms, interest rates, and other charges based on the underlying risk.
  • Better Customer Relationships: Since these frameworks provide a fair platform for analyzing a customer’s credibility, without the need for manual reviews, it prompts immediate responses to their demands, improving customer relationships.
  • Reward System: The credit scoring models allow the borrowers to improve their creditworthiness as they positively reflect the timely and consistent payments of debt in the credit reports.

Frequently Asked Questions (FAQs)

What credit scoring model is used for mortgages?

Given below are the three most popular credit scoring models for mortgages:

1. Equifax – FICO® Score 5 (Equifax Beacon 5)
2. Experian – FICO® Score 2 (Fair Isaac Risk Model v2)
3. TransUnion – FICO® Score 4 (TransUnion FICO® Risk Score 04)

How many credit scoring models are there?

While there are 16 versions of FICO® credit scoring models facilitated by Experian and Equifax altogether, TransUnion alone provides 21 frameworks to generate FICO® credit scores.

What is the most commonly used credit scoring model?

The most preferred FICO® version among lenders for credit score estimation is FICO® Score 8 despite the availability of the latest versions like FICO® Score 10 Suite and FICO® Score 9.

How to measure the quality of credit scoring models?

The quality of credit scoring models can be gauged through the various quantitative indices, including Kolmogorov-Smirnov (K-S) statistics, Informative statistics, Gini index, Mahalanobis distance, and Lift.

This article has been a guide to what are Credit Scoring Models. Here, we explain the topic in detail, including its examples, types, and advantages. You may also find some useful articles here –

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