Optimizing Recurring Billing with BIN-files

As the importance of recurring billing increases, new needs emerge at merchant services market. More and more recurring billing companies turn to BIN-files in order to get vital information for optimizing their recurring billing process. In this article, we are going to explain, how usage of BIN-files can enhance recurring billing process. Some information on card intelligence can be found in our respective article.

One of the key problems faced by companies in recurring billing context is that customers can use pre-paid and gift cards while subscribing for some memberships or services. The “trick” is often used by those who want to get a free trial period, and know that (due to the low membership cost) they are not going to deal with collections agencies when the company finds out that the membership is no longer paid for (see article on collections).

Example

A person subscribes for a pay-as-you-go membership costing $15 a month, using a pre-paid card. When the card is depleted, the member can just through it away and have the membership get cancelled, therefore relieving himself from the responsibility for canceling the service properly.

Often such cases create problems for merchants. One of the ways to avoid these problems is to use BIN-files to identify these cards and block them at the time when the accounts are initially setup.

Another advantage of BIN-files is that they can be used to identify transactions, whose processing cost is too high (too low). In subscription-based services industry the issue is even more important than in retail space. The reason is that while in retail business the card, causing money losses on transaction processing, is used just once, in recurring billing it is used regularly, and the potential losses from high processing fees are, consequently, larger. For example, if you don’t want to pay high processing costs, associated with rewards cards, you can identify them through BIN and decline them, thus, avoiding expensive processing fees.

Consequently, BIN-files, can help you in several ways:

  • You can identify expensive rewards cards and avoid processing them
  • If BIN-file indicates, that many of the cards used by a merchant, could be processed at lower rate through some specific debit network, it might be reasonable for the merchant to sign a separate agreement with the network and process the cards through this particular network (and not through Visa and MasterCard), saving on processing.
  • In our previous articles we also mentioned, that, using BIN-files, you can identify the bank that issued a given card. Therefore, you can use BIN files while conducting decline analysis to detect problems, that might be associated with a specific issuing bank. Working through this issue with one of your customers will automatically provide a solution for everybody else, carrying cards, issued by this bank.

Conclusion

Card intelligence through BIN-files can help you to save on processing costs, as well as detect abusive practices during recurring billing and common credit card transaction decline reasons. If you are not using BIN-files today, it may be the right time to start.

Credit Card BIN Files

Most modern-time credit card fraud protection tools are based on geo-location principles, IP-address filtering, and cardholder data verification. In addition to these methods a merchant can enhance the security of its business, and improve card processing strategy by adding another filtering mechanism. The filtering can be based on various attributes of a card, identifiable through credit card BIN.

The first 6 digits of a bank card number allow a merchant (and any business which processes bank card transactions) to learn additional information about the card by using pre-defined Bin ranges, that can be obtained from the acquirers. Based on the range the card number falls into, a merchant can understand additional information about the card.

Information which can be obtained from BIN file includes the following elements:

  • The maximal length of PAN (primary account number)
  • Name of the issuing bank and the country of origin of the issuing bank (country of issue)
  • Card type (credit, debit, prepaid, charge etc.) and PIN capability (such as credit with no PIN, debit with PIN only, hybrid card etc.)
  • The list of debit networks (for debit cards) that can be used to process the card outside Visa and MasterCard networks.
  • Information on whether the issuer is Durbin-regulated or not. In case of a PIN-less debit the BIN range allows you to determine if the issuing bank is regulated by Durbin amendment or not. It might be cheaper to partner with regulated debit networks (especially if you are processing million-dollar worth of transactions).
  • Information on card’s usage for healthcare transactions (FSA/HSA)
  • Ways to identify pre-paid and gift cards
  • Card class (purchase card, business card, consumer card, personal card, corporate card)

If you are a merchant, dealing with payment cards, the information, learned from card BIN is a useful component of your fraud protection strategy. Beside fraud protection, you can also use this information for interchange optimization, and to lower your processing costs.

Examples

The most typical example would be a US-based online retailer that only wants to accept US-issued cards.
Another example could be a pharmacy that wants to force HAS cards on certain types of purchases.

Conclusion

If you are a merchant, you should ensure that your payment system includes the logic for verification and, if necessary, filtering of payment cards, based on their BIN ranges. This will protect you from consumer fraud and unreasonably high processing fees.

What is a credit card BIN?

What is a credit card BIN?

CC BIN abbreviation stands for credit card bank identification number. Card BIN includes the first 6 to 9 digits of credit card number. Values of particular digits in BIN of a credit card define various information about the type of the card and its issuing bank. For instance, particular numbers in credit card BINs indicate card association, issuing bank, country of issue, and card type. More detailed information on credit card BIN numbers can be found here.

How can my business take advantage of credit card BINs?

In general, the key advantage of card BINs is that, based on credit card BIN numbers, a business can gain better insights into its customer portfolio. Particularly, a merchant business can find out, which types of cards are used by its customers (credit cards, debit cards, gift or reward cards) and which countries these customers come from. Consequently, for example, most frequently used foreign cards, and issuing banks, whose card transactions result in numerous declines and chargebacks, can be identified. Based on information, “extracted” from credit card BINs, businesses can prevent credit card fraud, plan their credit card processing strategies, and, thus, optimize the process, in order to achieve higher profitability.

How can a business obtain the listing of BIN numbers for credit and debit cards?

There are two ways to get card BIN numbers. Card BIN databases can be purchased online, from various web-sites. However, new card BIN ranges become utilized fairly often, so there is a common practice of getting those from the acquirers that a business uses for its merchant services. For example, First Data has a file that it can deliver to its respective merchants to get updated card BINs on weekly basis.

Payment Gateways II: Credit Card BINs and Card Intelligence

The purpose of this article is to familiarize the key merchant services industry players with the concepts of credit card BINs (bank identification numbers) and card intelligence as advanced features to be considered during payment gateway selection. If this is the first time you are reading “Payment Gateways II” series, please, start with the Introduction as it will improve your understanding of the current post.

Card intelligence concept is based on detecting certain patterns (what card types are used, where they come from) based on analysis of processed card numbers. First 6 to 9 digits of a credit/debit card number contain considerable amount of information about card type and its origin (detailed information on issuer identification numbers can be found here ). For example, the first digit usually identifies the association (Visa, Amex, etc), next digits define the card type (debit/credit/gift), country of issue, issuing bank etc.

The concept is fairly new, but it is rapidly gaining popularity among merchants and processors. Payment gateways utilizing credit card BINs are capable of providing additional analytical data to their customers (merchants). Examples of such data are given below.

Why credit card BINs are important

An important card intelligence aspect is differentiation of various card types (credit/debit/pre-paid/gift cards), because in some cases debit cards can be processed in a special way (PIN-debit or PIN-less debit), while pre-paid and gift cards are not a preferred option in the context of recurring billing agreements.

BIN also allows merchants to predict the cost of transaction. For example, if desired, a merchant can exclude (stop processing) reward cards that carry cash back and have high processing cost, or foreign-issued cards.

Credit card BINs can also be used to determine whether the card can be used in specific types of transactions (for example, HSA (healthcare) cards, fleet cards, purchase cards and level-III cards).

BIN also identifies the issuing bank, its location and contact data, enabling merchants to research problems around specific transactions.

Based on credit card BIN data, declines can be analyzed with respect to card types or issuing banks; respective patterns can be detected and measures taken.

In general, credit card BIN data analysis and patterns derived through it might help merchants make informed decisions in the area of credit card transaction processing. Illustrative examples of such patterns and decisions are provided below.

Examples

A merchant gets a certain number of declines during recurring billing, but, due to lack of card intelligence, it is unable to detect a potential pattern in declines. A lot of declines might come from a specific issuing bank. In this case the merchant might try to resolve the problem with the issuing bank.
As mentioned above, an important card intelligence aspect is the ability to identify a gift or pre-paid card during recurring billing. For instance, a health club customer is using a pre-paid card to buy a recurring contract for a year. If the amount on the card is relatively small, then there is a high likelihood of decline after it is consumed.
If some card type (credit/debit/gift or pre-paid) prevails in transactions, it might be appropriate to switch to a processor offering “cost plus” pricing model.
If many clients are using foreign-issued cards, the merchant/reseller might be able to conclude that the business has many customers from abroad (Canada/Europe), and may consider opening a foreign merchant account to reduce the costs.

Conclusion

A payment gateway/processor must be able to deliver the information about a specific card based on the first 9 digits of its number. Using this information, the business management will be able to make intelligent decisions.

The next post will cover aggregation models used by large-size merchants, wholesale resellers and PSPs.