Abstract

Paying for goods and services with a credit card is quick and easy. However, the likelihood of late payments increases as debt grows over time, especially in light of the pandemic and rising unemployment. The global financial crisis of 2007-2008 illustrates the need for commercial institutions to anticipate their customers' credit risk. As the quantity of Mastercard clients has expanded, banks have been confronting a heightening charge card default rate. This paper proposes a clever viable procedure to section clients by their anticipated likelihood of defaulting on instalments to assist monetary establishments with surveying risk before giving charge cards. We used the Taiwan credit card default dataset to present our method and findings. However, the proposed method can be applied to credit card default datasets from other nations because it has been generalized.

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