The purpose of this paper is to analyze the demographic andbehavioral factors that significantly affect the credit card Non-Performing Loan (NPL). This study is carried out to providemanagerial recommendations for controlling credit card NPL. Thisstudy uses secondary data from Indonesia’s most significant privatebank with 100,000 samples of cardholder data. Demographicfactors and cardholder behavior that significantly influence creditcard NPL can be used to improve the credit scoring system fornew cardholders and as indicators for a behavior scoring system forexisting cardholders. This research uses a probability stratified randomsampling technique. Logistic regression uses demographic factors andcardholder behavior significantly affected credit card NPL. Accordingto the logistic regression model, cardholder behavior was more likelyto NPL than demographic characteristics. The number of credit cardsshowed the highest credit card NPL probability.How to Cite:Achsan, Wahid, Achsani, N. A, & Bandono, Bayu. (2022). The Demographic and Behavior Determinant of Credit Card Default in Indonesia. Signifikan: Jurnal Ilmu Ekonomi, 11(1), 43-56. https://doi.org/10.15408/sjie.v11i1.20215.

Indonesia is a developing country with the fourth largest population in the world. Household consumption is still the main pillar of national economic growth in Indonesia. One sector that has an important role in national economic growth is banking. Bank carries out an intermediary function that directly or indirectly can encourage the real sector. A credit card is one of the banking products that can encourage growth in household consumption to support the growth of the real sector. However, on the other hand, the credit card is an unsecured consumer loan. This indicates the bank will have a greater percentage of losses than other types of credit if the borrower default. Therefore, the growth of credit card business must be balanced with good credit quality for the safety and soundness of the banking sector. Credit quality can be measured using a Non-Performing Loan (NPL) that reflects credit default risk. This study aimed to analyze the impact of the macroeconomic condition on credit card default which is proxied by credit card NPL ratio. NPL data obtained from Indonesia's biggest private bank with cardholders that are widespread on every island and have average card growth, transaction value, and outstanding credit card were above the national average. ARDL Cointegration model is used to determine macroeconomic variables that significantly affect credit card NPL. This study was found that exchange rate and interest rate variables partially have a significant influence on the credit card NPL in the long-term. ARDL model can be used as an early warning indicator of the condition of Bank credit card NPL if there is a shock to macroeconomic variables and the model can be used to improve the feasibility analysis tool for new cardholders (credit scoring system) and an indicator of behavior scoring system for existing cardholders.