The use of big data and analytics in credit scoring

Loans are common among people who want to achieve their financial goals of buying a home or investing in a business. In the financial world, there are several ways an individual can get hassle-free loans through a repaying mechanism. Among such processes is the credit score system that is utilized to give a score or rating to a credit-taker by the lending or financial institution.

Credit score and loan mechanism

Whenever someone applies for a financial loan for buying a home, or vehicle or starting a business, their credibility is judged on the basis of the institution’s credit scoring system. Any sort of default, or failure to pay the loan taken impacts the credit score of a person. Successful loan repayment gives a high credit score while a low score is due to failed repayment. Herein, banks hold the authority to deny loans in the future basis the default and score.

What is big data?

Big data and analytics are industry key terminologies for handling various types for solving business problems. It contains large volumes of structures and unstructured that are converted into insights for taking business decisions. Big data is classified on basis of four factors – Volume, Velocity, Variety, and Value.

Credit score system using big data

Financial institutions issue different types of loans to credit-takers. Mainly there are two types of loans – secured and unsecured loans. Secured loans allow banks to take collateral as security against the given credit while unsecured loans are issued without any collateral for repayment.

A financial institution may have more parameters to internally judge the loan criteria and mechanism to allot a credit score. The primary values for calculating the score are age, income, and points, while other factors also matter in allotting it.

Big data greatly helps in defining loan issuing and denial on the basis of credit score. Credit score systems make use of a large volume of structured and unstructured datasets. These datasets are referred to as big data, owing to their enormous volumes. The credit score system, as per pred-defined AI algorithms or mathematical data modeling, uses data and analytics to give a score. This core, in turn, is used for loan consideration.

Conclusion

Big data has solved many business challenges by combining various models and providing actionable insights into data. From giving credit scores to allowing the lending institution to analyze the loan history of a person, data has influenced decision-making in valuable ways. Not merely for lending, credit score goes on to provide a detailed peak into a financial behavior of a person, helping the banking system become advanced for streamlining lending products.

The article has been published by the editorial board of the Fintek Diary. Happy Reading. For more information please visit www.fintekdiary.com

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