The purpose of this article is to familiarize payment card industry players with the concept of credit card batch processing optimization. Particularly, the article addresses several techniques intended for increase of approval rates in recurring billing and bill payment scenarios, where batch transaction processing is widely implemented. The two approaches to credit card batch processing optimization to be addressed are account number aggregation and account number optimization.
Account number aggregation concept
One of the techniques to increase approval rates of credit cards processed in batch is transaction aggregation (or account number aggregation).
The concept is as follows. When a batch of transactions comes in, and it has multiple transactions with the same account number in it, these transactions are aggregated into a single transaction (by account number).
Such aggregation is performed for the following reasons:
- Reduction of transaction fees paid by the merchant through reduction of the total transaction count (since there are per-transaction fees to be paid)
- Consolidation of charges for the cardholder, since only one transaction is shown on cardholder’s statement. (Sometimes cardholder is using the same card for multiple accounts, and he or she might get falsely alerted seeing multiple transactions from the same merchant on a bank statement)
The disadvantage of the technique is that, in a sense, account number aggregation can minimize the chance of collecting on certain accounts. For this reason the first technique is mostly used on files containing original attempts to collect the money and not reattempted declines.
Account number optimization concept
Because of the disadvantages of the previous approach, another credit card batch processing optimization technique (sometimes called transaction optimization or account number optimization) is used in order to ensure higher likelihood of collecting.
The concept is as follows. When a batch of previously declined transactions comes in, and it has multiple transactions with the same account number in it, the transaction with the smallest amount is reattempted first. If the reattempt is successful, all remaining transactions with the same account number can be submitted; while if the smallest-amount transaction doesn’t come through, there is no point in resubmitting other ones.
The advantages of this approach are as follows
- There is a higher probability of collecting
- The merchant doesn’t have to pay per-transaction processing fees for pointless reattempts
For these reasons this technique is more often used on files, containing reattempts (transactions that have previously been declined), i.e. in decline recycling.
Let us consider an example, illustrating the transaction optimization principle.
One of the challenges for companies that rely on recurring billing is that the first billing transaction often happens at least 30 days after the customer’s initial subscription to the service. By that time, many customers tend to forget what the service was. Consequently, it is critical for the descriptor of a recurring payment transaction that appears on the bank statement, to be clear for the customer. Our next article will provide detailed explanation of credit card and ACH transaction descriptors known as dynamic descriptors or soft descriptors.