Card Payments: Void, Reversal, Refund Transactions

Payments in the banking business mostly through credit cards. In this post, I have shared void, reversal, refund, installment, and recurring transactions. And these are tricky to understand.


Credit cards domain Tricky Transactions.

Transaction #1: Recurring

The best example is the post-office recurring transactions. Every month you will pay a certain fixed amount as a recurring deposit.

In the recurring payments, the amount is fixed.

So, the other best examples are recurring payments to the merchant, for the purchases you made like Cloth, Gold, House rent, etc.

Recurring vs Instalment

Transaction #2: Installment

In the installment, the amount is not fixed. The best examples are Hospitals and Lodges.

In the Hotel, while check-in you pay some amount as a deposit for 3 days.

Later due to some work you extended to 5 days. So the remaining amount you need to pay to the merchant.

That payment is called installment transactions. Here you paid two times.


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Transaction #3: Void

The Void transactions you can call them as canceling or ignoring the transaction.

Only the current transaction you can make it as Void.

Transaction #4: Reversal

Reversal transactions are something initiated when the transactions do not pass through some of the business rules.

  1. The reversals are system generated reversals and Issuer generated reversals.
  2. There are many technical reasons due to timeout also your card transactions will be reversed automatically.
  3. Sometimes the merchant can reverse the transaction immediately or after some time.
  4. Sometimes issuer generates reversal transactions due to some technical glitch.

Transaction #5: Refund

Refund transactions also called return transactions.

When you return a product you already purchased, then that amount will be refunded at a certain time.

These kinds of transactions you can find in the monthly card statement.

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Author: Srini

Experienced software developer. Skills in Development, Coding, Testing and Debugging. Good Data analytic skills (Data Warehousing and BI). Also skills in Mainframe.