Inactive Credit Card Accounts

by Victoria Soriano 4 min read February 9, 2021

Inactive credit card accounts are defined as credit cards that were approved, opened and never used by account holders. They also include credit card accounts that were approved, opened, utilized by account holders but don’t have a balance for the last six to 12 months. Inactive credit card accounts pose several challenges and opportunities to lenders.

A review of inactivity rates of credit card portfolios of credit unions across the United States as of March 2018 shows that inactive accounts comprise approximately 11 percent of total accounts on the books. The average credit line of inactive accounts is $8,700. (Data were extracted from Experian’s File One™ database using a sample of credit card accounts with credit unions across the United States as of March 2018. Sample size is approximately 600,000 credit card accounts.)

Why do credit card accounts become inactive? One potential reason for inactivity is the convenience of securing a credit card during demand deposit account (“DDA”) opening processes. Lenders today may prequalify or preselect a customer quickly and efficiently for a credit card while a customer’s request to open a checking account or deposit account is being processed. Lenders benefit from this choreographed process with no to very minimal additional effort and time requested from the customer. The removal or significant decrease in friction costs — such as requiring additional customer information that previously would have deterred a customer from proceeding with the credit card application — gave lenders the advantage of processing more applications. (Schruder, Kyle. Feb. 26, 2018. The Top 5 Behavioural Economics Principles for Designers — Bridgeable blog. https://uxplanet.org/the-top-5-behavioural-economics-principles-for-designers-ea22a16a4020.)  Because of this convenience, some customers say yes to obtaining a credit card even though they had no intention of securing one in the first place. In behavioral economics, this may be identified as the “yeah, whatever” heuristic. People take the option with the least effort or the path of least resistance. (Thaler, Richard H. and Cass R. Sunstein. 2009. Nudge Improving Decisions About Health, Wealth, and Happiness. New York: Penguin Books. Pages 35, 85.) With low commitment to the credit card, customers who are approved will receive the new plastic and forget about it.

An active credit card user may become inactive because the features, benefits and rewards are no longer relevant for their current financial needs. For example, a merchandise purchase or balance transfer promotion has expired and was paid off. Rewards are less attractive compared to other credit card offers in the marketplace.

Lack of lender engagement activities may also lead to inactivity. For example, there are no marketing campaigns with promotions or special rewards offers. Revolving accounts with very low credit lines aren’t given credit line increases even though credit risk is acceptable, and accounts generate good interest income.

The challenges to lenders with a large segment of inactive accounts include the direct cost of contingent liability. A percentage of unused credit lines is classified as contingent liability in the balance sheet. If contingent liability is reduced, then funds may be used to invest in more productive activities.

In the absence of analytics and deep understanding of various customer behaviors in the portfolio, it can become costly for a lender when inactive accounts are included in all kinds of marketing campaigns. Marketing budgets are limited and ought to be used wisely to target segments with high expected returns and to achieve specific and well-defined objectives.

Inactive accounts may also come with credit risk challenges. Some customers designate certain credit cards as emergency credit cards. That is, these cards will be used only in emergency situations where payment is needed immediately, and no other funds can be easily accessed at such time. Some situations are significantly more serious and may be accompanied by deep financial stress. During these times, inactive accounts are utilized and may result in collections or charge-offs.

How can lenders handle the challenges of inactive accounts? An inactive account strategy that uses data and analytics is very helpful and prudent. Determine which accounts are never active or were inactive within the last 12 months. Identify which accounts pose elevated credit risk. There are various interventions that can be designed to improve card activation, which may include marketing campaigns and account management strategies including credit line options. If inactive accounts were included in marketing campaigns or account management strategies, then track the performance. These performance reports will provide the rationale and guidelines for further action, which may include account closure.

Evaluate the multiple relationships of the customer with the lender and estimated cardmember value. Survey the inactive accounts and obtain feedback regarding the reasons for lack of card usage. Those insights will help identify areas for improvement and drive new initiatives.

We have seen that inactive accounts aren’t a trivial component of a credit card portfolio. There are real costs and risks associated with inactive accounts. They also provide opportunities for improving card features and benefits and ways to continue engaging existing cardmembers.

Related Posts

Building for Bots in the AI Age: Separating Legitimate Agents From Fraudsters

See how NeuroID helps businesses distinguish legitimate AI agents from fraud bots, while Agent Trust verifies agent-initiated transactions.

October 29, 2026 by Laura Burrows
2026 Retail Banking Identity and Fraud Report 

Learn how banks can convert rising fraud investment into protection customers recognize, value and feel in our recent report. Read more!

October 28, 2026 by Laura Burrows
One Platform, Fewer Handoffs, Faster Decisions

The average credit union manages between 100-300 vendor relationships, and nearly a third have no dedicated staff managing them. What was supposed to drive efficiency is stunting growth and compromising the member experience. Application volume is continuing to rise, and consumers expect a loan decision at digital speed. But for credit unions, meeting that expectation isn't the only goal. They must also continue to make the right lending decisions while also prioritizing risk management. The institutions pulling ahead aren't the ones with the most tools. They're the ones that have turned credit, fraud and decisioning into a single, coordinated system. A single loan decision touches: Credit data Identity verification Fraud signals Decisioning logic Reporting Rarely does all of that live in one place. More often, it’s stitched together across separate platforms, each with its own contract and its own support line. When a credit view and a fraud view are generated separately, they must be reconciled instead of read together in the same instant. Every handoff is a place where a decision slows down and a signal gets missed. It's why a fraud pattern that would be obvious next to the credit file often surfaces only after the funds are already gone. Fragmentation also makes it harder to optimize lending strategies over time. When data, analytics and decisioning are disconnected, credit unions have less visibility into what's working, what's changing and where strategies need to be adjusted. An integrated decisioning ecosystem closes those seams by design, with credit, fraud and lending strategy running on one platform and accessed through a single Application Programming Interface (API). Identity and compliance capabilities can be an integrated decisioning flow. The data doesn't need to be reconciled after the fact because it was never separated in the first place. Stop overengineering, start removing friction When decisioning underperforms, the instinct is to build something more custom: a proprietary model, tighter segmentation, more configuration.  Custom modeling has its place for institutions with the scale and data to justify it. But often, for small or mid-sized credit unions, the bigger opportunity is a flexible decisioning strategy that uses a strong, continuously refreshed model. This shouldn't be either/or. The right approach gives credit unions a strong decisioning strategy today, with the ability to introduce more customized analytics and modeling as their needs evolve.  The same principle applies to strategy management: credit unions can gain greater control through self-service capabilities as they build a more sophisticated data science team.   That kind of flexibility is important as credit unions modernize their decisioning infrastructure. Research surveying more than 2,000 senior credit risk and fraud decision-makers across 11 countries found that organizations investing in unified platforms and modern infrastructure are moving faster and realizing the greatest Return on Investment (ROI).   As their needs evolve, credit unions can adjust decisioning strategies without introducing another layer of technology or relying on third parties to make every change. Until self-service is the right fit, choose a partner that understands what makes your credit union’s membership and risk appetite different from others.  Same member, same afternoon, faster answer Consider a credit union growing its auto and personal loan originations.  A member applies for an auto loan on Saturday afternoon. Credit data, identity and fraud signals are read together in a single real-time pass instead of separate reviews:  Most applications resolve immediately, approved or declined based on a more comprehensive view of the applicant. A smaller number are flagged for quick step-up verification and cleared within minutes. Only genuinely ambiguous cases reach an underwriter, who is working from one complete picture instead of reconciling multiple signals. The member has an answer before the weekend is over. The credit union books the loan before competitors even open on Monday. Built to scale This kind of process holds up today. However, the better test is whether it holds up eighteen months from now when application volume has grown, new products are live and the data flowing through the system looks nothing like it does right now. Future-proofing isn't only about handling more volume. It's about having room to be nimbler and make adjustments as quickly as the market changes. A credit union that relies on standard models within a decisioning strategy may want more customized analytics and greater control over its strategies tomorrow. Connect with us With more than three decades of credit expertise and one of the industry's largest data footprints, Experian helps credit unions do more than solve this year's friction. We're helping to build a decisioning foundation that scales, so growth becomes something the system absorbs, rather than something it must be rebuilt around. Explore More

October 21, 2026 by Zohreen Ismail

Subscribe to our Newsletter

Enter your name and email for the latest updates.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Subscribe to our Newsletter

Don't miss out on the latest industry trends and insights!
Subscribe