Working Group for the Standardization of Credit Card Data Report

Working Group for the Standardization of Credit Card Data

- To Realize a Cashless Society and Full Utilization of Data -

Report

December 2016

Commerce and Distribution Policy Group Ministry of Economy, Trade and Industry

Table of Contents 1. Introduction．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．1

2. Significance of the Standardization of Data．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．3

3. Basic Direction for the Standardization of Data．．．．．．．．．．．．．．．．．．．．．．．．．．．6

(1) Mechanism of credit card transactions and data to be standardized (2) Subjects discussed by the WG

4. Standardization of Information on Member Stores' Locations．．．．．．．．．．．．．．11 (1) Current status and problems (2) Approaches

5. Standardization of Information on Member Stores' Business Types．．．．．．．．．14 (1) Current status and problems (2) Approaches

6. Future Course of Facilitation of Credit Card Data Utilization．．．．．．．．．．．．．．16

7. Conclusion．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．．18

(Attachment) Guidelines for Business Type Codes in Credit Card Data

1. Introduction The Ministry of Economy, Trade and Industry (METI) has been deliberating on how to respond to social influences brought about by the advancement of various technologies. These considerations have taken place in collaboration with many stakeholders and related parties. For example, the Advisory Council on Challenges and Future Directions concerning FinTech (Advisory Council on FinTech) has been held since July 2016 to discuss influences of this new movement and clarify challenges to and measures for ensuring that such technological advancement will lead to an economic and industrial development of Japan. The roles of both the public and private sectors are considered. Regarding the utilization of big data to be obtained through the advancement of technologies, the Cross-sectional System Study Group for the Fourth Industrial Revolution set up in January 2016 has discussed produced a report on ideal approaches to establishing three cross-sectional policy systems: competition, utilization and protection of data, and intellectual property. Furthermore, the Information Economy Subcommittee of the Industrial Structure Council set up the Working Group on Distribution Strategy in March 2016. The working group envisages the future of IoT (Internet of Things) in Japan from a medium-term perspective and has been discussing strategies and systems for achieving ideal outcomes, including the means by which to ensure Japan's competitiveness.

Cashless transactions have been increasing year by year, as have their ratio among total private final consumption expenditures. Cashless transactions, which both enhance convenience for Japanese consumers as well as stimulate inbound demand, produce valuable consumption data which, if utilized effectively, can contribute to creating new industries and businesses. The Revised Japan Revitalization Strategy 2015 (Cabinet decision on June 30, 2015) contains a statement to the effect that the national government will deliberate upon concrete means to develop an environment best able to facilitate the utilization of big data, and take required measures based thereon. Under such a policy course and in consideration of the future direction of the credit card industry, meetings of the Study Group on the Credit Card Industry and Big Data were held in order to compile policy recommendation based on practical discussions and consultations, which it completed in February 2016.

The Working Group for the Standardization of Credit Card Data was established on

July 19, 2016, for the purpose of promoting the standardization of data that can be collected in connection with credit card transactions and to “Reach a conclusion on standardization within this year” (Japan Revitalization Strategy 2016; Cabinet decision on June 2, 2016), and has been carrying out practical work for that purpose.

2. Significance of the Standardization of Data Cashless transactions have been increasing in Japan both in the aggregate and in terms of share of private final consumption expenditures, but the ratio is still relatively low compared with other countries. In Japan, credit cards have disseminated non-uniformly with the utilization rate, varying by business type and by region. The utilization rate is generally higher in metropolitan areas.

Cashless transactions offer many advantages to consumers, businesses, and the national economy as a whole. Consumers can buy things without needing to carry cash, and cashless settlement is indispensable for increasingly expanding online transactions.

Automated household account services have been developed as a result of accumulation of data on personal consumption histories through cashless transactions. For businesses, the introduction of cashless transactions brings about benefits by reducing the handling of cash, costs for cash management, and damage in the case of loss or theft. Also from the perspective of attracting inbound demand, which is increasing in recent years, businesses need to take proactive action to introduce cashless transaction systems.1 Some companies are already enhancing their marketing strategies through accumulating and analyzing customers' purchase data by combining them with various big data. From a public interest perspective, cashless transaction systems, which enable follow-up of settlement records and thereby enhance transparency in transactions, are also expected to have such effects as reducing tax evasion and curbing money laundering. < Examples of advantages of cashless transactions >

Amid further diffusion of cashless transactions, it is expected that effective utilization of consumption data may contribute to creating new industries and businesses while also stimulating consumption, including foreign visitors, in respective areas. As indicated in the report compiled by the Study Group on the Credit Card Industry

1 54.9% of foreign visitors use credit cards during their stay in Japan ("Consumption Trend Survey for Foreigners Visiting Japan, July-September 2016 Report" (Japan Tourism Agency)).

and Big Data in February 2016, consumption data is being utilized by various entities in various fields, such as (i) by retailing companies and manufacturers in corporation groups for formulating sales promotion strategies and store and product development strategies; (ii) by general retailers for formulating store strategies and adjusting purchase prices; (iii) by consulting companies and database companies for offering data analysis services; (iv) by credit card companies for enhancing the accuracy of credit management; (v) by consumers for using lifelog services; and (vi) by the public sector for compiling statistics. Under such circumstances, protecting personal information and standardizing data are extremely important. This working group (WG) has held discussions on the latter with the aim of developing a sound foundation from which the many abovementioned users can best utilize credit card data for diverse purposes.

3. Basic Direction for the Standardization of Data (1) Mechanism of credit card transactions and data to be standardized The credit card transaction system consists of individual members using credit cards, member stores handling credit card transactions, and credit card companies offering settlement services. In order to become a member, an individual enters his/her name, age, gender and other personal information in an application form and such information is stored and managed as the individual’s master data by the credit card issuer. A store that wants to respond to customers' needs for credit card transactions enters necessary information in an application form and concludes a contract with a company seeking member stores (acquirer), which then manages such master data information. In the case of member stores with multiple branches, a head office may represent all its stores and conclude a contract or each store may separately conclude a contract, depending on their own choice, and they are registered in the master data according to the content of such contracts. < Data held by a credit card company >

In this manner, after concluding contracts, individuals and stores make transactions. Credit card transactions are categorized into on-us transactions and off-us transactions. In an on-us transaction, an acquirer and an issuer are the same company, while in an off-us transaction, an acquirer and an issuer are different companies and an international credit card brand offers a payment network that links an acquirer and an issuer. Therefore, in an on-us transaction, data used for payment are sent from a member store to a credit card company (which serves both as an acquirer and issuer) and are used only within the company. On the other hand, in an off-us transaction, data is sent from a member store to an acquirer and then to an issuer via an international credit card brand. In both cases, two types of data, namely authorization data and sales data, are transmitted. Authorization data is used in payment procedures wherein a member store checks the credit limit by confirming with an issuer whether the credit card can be used

for the relevant payment and the issuer secures the limit. Sales data is created when a member store settles a transaction after going through the authorization process and sends a bill to a credit card company. < On-us transaction (an acquirer and an issuer are the same company) >

< Off-us transaction (an acquirer and an issuer are different companies) >

With regard to member stores with multiple branches, authorization data and sales data are sent in either of the following manners depending on their own preference, as in the case of registration in member stores' master data. (i) Send information of the representative registered in the master data (ii) Send information of each branch registered in the master data As a result, transaction data of member stores with multiple branches represented by their head office (as in Case (i) above) may be recorded integrally as sales of the registered representative.

In credit card transactions, multiple types of data are sent in various patterns as explained above, but the WG only focused on sales data for standardization, not

authorization data, as the former is the very data that determines transaction information. Additionally, individual members' master data is managed within an issuer and is not included in authorization data and sales data, while part of the information in member stores' master data is included in authorization data and sales data and is transmitted between an acquirer and an issuer. Therefore, the WG decided that standardization efforts should focus on data relating to member stores' master data. Data items to be standardized as discussed by the WG are as follows.

(2) Subjects discussed by the WG The Study Group on the Credit Card Industry and Big Data sorted out major data items to be covered, in consideration of their nature, level of attracting people's interest as consumption data, and current status of credit card data, and decided to promote standardization for the data items indicated in the central part of the following table (outlined in red).

While ensuring consistency of the standardization of data mentioned above, it is important for entities to be able to quickly realize utilization of the data in order to maximize its benefits. Accordingly, as a key output and aiming to ascertain consumption trends of foreign visitors, the WG specifically decided to enhance the accuracy of public analysis by improving the quality of credit card data concerning foreigners' consumption transactions available on the Regional Economy Society Analyzing System (RESAS)2 provided by the national government. From this perspective, the WG agreed to target the content in sales data sent from acquirers to international credit card

2 In order to actually revitalize local economies, which have been stagnant amid structurally influenced population decline and depopulation, local governments need to accurately ascertain the current status of respective regions and objectively forecast their futures, and must inevitably have capacity to formulate and implement voluntary, efficient policies in accordance with the features and circumstances of respective local communities. The national government has established this system to collect various big data on local economies (business-to-business transactions, flow of people, demographics, etc.) and make it visible in an easy-to-understand manner, thereby aiming to assist local governments in their efforts to achieve PDCA (plan-do-check-action) cycles for their comprehensive strategies that are truly effective. (https://resas.go.jp)

brands (through off-us transactions).

When ascertaining foreigners' consumption behavior in Japan, at what types of stores they spend money and where such stores are located need to be obtained accurately. In other words, among credit card data, it is important to ensure the accuracy of information on (i) locations and (ii) business types of member stores. At present, RESAS uses these data and provides such information as the unit price, number of purchased units, and purchase date by nationality of foreign visitors, by prefecture, and by business type (for retailers, for example, the information can be broken down to major items handled at each store (home appliances, luxury goods, leisure items, etc.)). RESAS offers a function that enables cross analysis from these perspectives and data are being utilized mainly by local governments and destination management organizations (DMOs) for tourism promotional activities. However, some point out the need to further enhance the quality of location data and business type data in light of the current status as explained in 4. below. < Analysis service offered by RESAS using credit card data3 >

3 Prepared by the secretariat for the Headquarters for Overcoming Population Decline and Vitalizing Local Economy in Japan, based on the credit card data of Visa Worldwide (Japan) Co., Ltd. Amounts of payments are obtained based on payments made by foreign visitors using Visa cards and Visa cards' market shares in their home countries. Nationalities are domiciles of card owners.

The WG thus decided to consider means for the standardization of information on locations and business types of member stores out of all sales data sent from acquirers to international credit card brands (Visa and Mastercard).

4. Standardization of Information on Member Stores' Locations (1) Current status and problems At present, sales data sent from acquirers to international credit card brands contain information on the names of cities where member stores are located. However, such information is sent as literal information and expressions are not consistent. Furthermore, information on a prefectural basis and on a municipal basis may be mixed. < Example > Expressions of information on city Locations Store names Acquirers names sent from acquirers to international credit card brands Chiba-shi, Chiba Cafe A Acquirer A CHIBA

Bakery A Acquirer B TIBAKEN

Shinjuku-ku, Variety Store A Acquirer A TOKYO

Tokyo Cafe B Acquirer C TOUKIYOUTO

Sapporo-shi, French Restaurant A Acquirer B HOTUKAIDOU

Hokkaido Variety Store B Acquirer C SAPPORO

The information by region provided by RESAS (based on Visa data), for example, is processed and arranged uniformly to the prefectural level based on original data. In other words, RESAS requires this step of processing original data, which varies significantly in expressions and levels of the content (such as whether the data is input on a prefectural basis or on a municipal basis), and can consequently offer only information at a higher-order level, i.e., on a prefectural basis. On the other hand, sales data sent from acquirers to Mastercard contain postal codes (7 digits) in addition to city names of member stores. 7-digit postal codes cut out the need for the abovementioned processing and can provide more detailed information on a municipal basis. Such information is considered to be effective. The format for sending sales data to Visa has a column for entering postal codes, but acquirers in Japan do not fill in that column and information on postal codes is not sent to Visa ("0" is entered for blank columns). This is why RESAS does not utilize postal codes at present. If acquirers enter 7-digit postal codes in the prescribed column of the format, this will enhance the accuracy of member stores' location data and will eventually increase the data value. However, at present, Visa’s postal code column only has a 5-digit field.

(2) Approaches (Postal codes) As mentioned above, the data of Mastercard already contains information for 7-digit postal codes and there is no need to alter current practices. On the other hand, with regard to Visa, as it is difficult to revise its data format being used internationally, the immediate approach should be to enter the top five digits of Japanese postal codes in the prescribed column with only 5-digit space of the current format, with a medium- and long-term goal of changing the format to enable the entry of 7-digit postal codes. With only the top five digits of postal codes, location data thus entered cannot be broken down to municipal levels and there are even cases where prefectures cannot be identified properly. < Example > ○ Cases where the top five digits are shared by multiple municipalities ・Postal codes starting with "135-00**" are used for most of Koto-ku, and part of Minato-ku (Daiba) and Shinagawa-ku (Higashiyashio) in Tokyo. ・ Postal codes starting with "247-00**" are used for most of Sakae-ku, Yokohama-shi, and part of Kamakura-shi in Kanagawa prefecture. ○ Cases where the top five digits are shared by multiple prefectures ・ Postal codes starting with "630-02**" are used for Kamiishikiri-cho, Higashiosaka-shi, Osaka prefecture and part of Ikoma-shi, Nara prefecture. ・Postal codes starting with "520-04**" are used for Kutakamino-cho and others in Sakyo-ku, Kyoto prefecture, and Katsuragawaumenoki-cho and others in Otsu-shi, Shiga prefecture.

The WG decided that its members should first take the initiative in carrying out the approaches decided by the WG and have Visa ask its related parties for cooperation,4 thereby increasing acquirer collaboration outside WG members in order to facilitate the development and standardization of data.

With regard to the top 100 member stores ranked in terms of the volume of transactions with foreign visitors, the WG examined whether their data is registered integrally for the respective representative alone (Case (i) in 3.(1) above) or separately

4 The international credit card brand will ensure that its related parties including acquirers properly enter data in the first place. Part of the data sent from acquirers to Visa is also sent to issuers. Therefore, Visa will notify its related issuers, which are expected to receive data partially different from conventional ones, of such possible changes in data.

for each branch store (Case (ii) in 3.(1) above) and found that around 20% are categorized into Case (i).5 Data registered separately for each branch store naturally provides more accurate information as to their location and business type. However, the choice as to whether to register data integrally or separately is up to member stores depending on their management policies to facilitate settlement procedures and they should not be forced to change their practices, but this point should be noted when one analyzes or otherwise handle relevant data. Mastercard considers it necessary to match authorization data and sales data and requests its members to provide postal code information in a consistent manner under its rules. However, in actual settlement procedures, member stores sometimes send their representative store's postal code as authorization data to ensure promptness and send each store's postal code as sales data. In such cases, acquirers rewrite each store's postal code in sales data to the representative store's postal code.

(Names of cities where member stores are located) When postal code information is properly arranged, member stores' locations will be ascertained accurately. Therefore, there is no need to make any redundant efforts to change how to handle information on city names, which varies significantly in expression, etc.

5 The ratio is around 20% based on the number of representative stores, but figures are different when based on the transaction amounts or the number of branch stores.

5. Standardization of Information on Member Stores' Business Types (1) Current status and problems Business type codes contained in sales data sent to international credit card brands are processed in the following two steps. I. A step to register a business type code entered in an application form to the member stores' master data of respective acquirers II. A step to convert codes when respective acquirers send data from their member stores' master data to international credit card brands

Step I is carried out based on respective acquirers' policies, but there are no uniform standards for business type codes used in member stores' master data and they independently adopt their own code systems that they consider most convenient for business management. On the other hand, in Step II, acquirers convert their original business type codes according to the system specified by international credit card brands before sending them. However, each acquirer uses an original conversion table based on different methods , and as a result, different codes may be assigned to the same store and be sent to international credit card brands in some cases. < Example > Business types MCCs entered in data to be sent to international credit Store names Acquirers registered in member stores' master data card brands (Visa and Mastercard) Cafe C Acquirer A Tearoom 5812 (Eating Places and Restaurants)

Acquirer B Tearoom 5814 (Fast Food Restaurants)

Clothes Acquirer A Men's clothes 5611 (Men's and Boys' Clothing and Accessories Stores)

Store A Acquirer C Women's clothes 5621 (Women's Ready-To-Wear Stores)

Drugstore B Acquirer B Drugstore 5912 (Drug Stores and Pharmacies)

Acquirer C Drugstore 5977 (Cosmetic Stores)

Additionally, in Japan, tenants in a commercial facility, such as a shopping center or

an outlet mall, are often registered integrally under the name of the facility in member stores' master data, and their business types are integrally indicated as a shopping center or an outlet mall. Such a category is not found in MCCs of international credit card brands, and consequently, their business type codes are sometimes converted to a code of department stores or miscellaneous general merchandisers, which are considered to be closest to a business type of a commercial facility that integrally manages all tenants. < Example > Stores concluding a Business types registered in MCCs entered in data to be Store names Acquirers membership member stores' master data sent to Visa and Mastercard contract Acquirer A Shopping center 5311 (Department Stores) Clothes Store A in Shopping 5399 (Miscellaneous General Shopping Center A Center A Acquirer B Shopping center Merchandisers)

5399 (Miscellaneous General Restaurant A in Acquirer B Outlet mall Outlet Mall A Merchandisers) Outlet Mall A Acquirer C Outlet mall 5311 (Department Stores)

(2) Approaches With regard to stores whose business type codes vary by acquirer as mentioned above, the WG specified, in the attached guidelines, preferable codes to be sent to international credit card brands via Steps I and II. It is expected that each acquirer, who sends data to international credit card brands, will follow these guidelines. Development of data should be facilitated not only for stores to be newly registered in member stores' master data but also for already registered stores, especially prioritizing those handling a large volume of transactions, with the view to increasing value of data as a whole. When applying the guidelines, special attention needs to be paid to the fact that some large-scale franchise chains that integrally manage multiple stores in different business modes, such as supermarkets and discount shops, are sometimes categorized into business types that are applicable more generally and are registered as such in member stores' master data, as only one business type is to be assigned even in the case of such large-scale member store. Additionally, information of each tenant or selling space in a shopping center or department store is not always ascertained individually. Whether or not to grasp such information is up to member stores (here, the relevant large-scale franchise chain or shopping center, etc.) that are making efforts to facilitate their business procedures, and they should not be forced to change their practices.

6. Future Course of Facilitation of Credit Card Data Utilization The standardization of data items by the WG is the first step to achieve the overall national goal of facilitating utilization of big data to be obtained through cashless transactions. In the case of Visa, data on off-us transactions in Japan are also transmitted via the same network as data on overseas transactions. Therefore, if acquirers handle data on domestic transactions in the same manner in accordance with the guidelines, not only consumption trends of foreign visitors but also those of Japanese consumers can be ascertained and the scope of data use is thus expected to expand in the future. At present, transactions are being made in both brick and mortar shops and via e-commerce, but e-commerce will increase and data will be further accumulated and developed accordingly.

During the discussions, it was pointed out that if the use of a credit card issued overseas is deemed to be included in consumption by foreign visitors in Japan, there is a question, for example, whether a payment made by an American serviceman in Japan with a credit card issued overseas should also be included. One solution to this problem is to distinguish card use by individuals and that by corporations, but there are foreign businessmen who use corporate cards in Japan and their payments are now included in consumption by foreign visitors. Therefore, this point needs to be further discussed. Incidentally, classification of individuals and corporations is possible with the information on types of credit cards.

Concrete concerns in actually utilizing standardized data include that as a result of enhancing the accuracy of location data and business type data, it may become possible to identify a specific store of a certain business type in a certain area in the process of analyzing RESAS data, for example, and this may pose a problem in relation to the confidentiality under a contract with the relevant member store. Therefore, some pointed out the necessity of consideration from a legal standpoint especially in the case of utilizing data externally. Under a membership contract, it is hardly possible for a credit card company to externally provide data with which a specific store can be identified, either in open cases (such as data provision to RESAS) or in closed cases, unless the relevant store gives prior consent. In open cases, however, it may be possible to prepare a mechanism to enable related parties to check in advance whether the data is identifiable or to establish criteria for data processing for each area and business type. Furthermore, postal codes include those indicating addresses and those indicating

specific business entities, and the latter, which can specify business entities, needs to be processed before being provided externally. These points must be taken into account when facilitating data utilization in RESAS, which is at present treated as an example of an open case.

The WG has focused on the development of original data sent from acquirers as the means to enhance the accuracy of analysis of data from multiple senders. For that purpose, proper systems need to be put in place and this may require time in some cases. With regard to the standardization of business type information, some mentioned the possibility of improving accuracy of data analysis by way of having entities where various data is gathered (international credit card brands) and entities that manage, sort, and clean data.

It is also important to consider benefits of utilizing credit card data from the viewpoint of consumers, who are users. If the information on shops is more detailed in credit card statements sent to individual members, they will be able to know more clearly where they used cards.

This time, the WG only targeted data accumulated by Visa and Mastercard, but there are further more diversified transaction patterns such as on-us transactions and transactions via other international credit card brands. From the perspective of better utilizing credit card data, collaboration with other consumption data, such as electronic receipts,6 may also be possible. Further deliberations from such perspectives will be necessary as a next step.

At present, the banking industry is considering whether to introduce an open Application Programming Interface (API) to disclose specifications to link to the banking system as a tool to enhance financial services through the collaboration between financial institutions and FinTech companies, etc. In the credit card industry as well, some companies have already started API-related collaborations and the initiatives in the banking industry need to be closely watched.

6 A service to issue receipts electronically via e-mail or by the use of smartphone applications; METI is also deliberating means to fully utilize data accumulated through this service.

7. Conclusion In the future when cashless transactions disseminate more broadly, consumers may be able to check purchase records, which are automatically accumulated based on enhanced data, with their smartphones at any time without needing to keep household accounts every day. They may manage such purchase records by themselves and provide them to companies as data and in return may receive such benefits as royalty points or personally customized recommendations on goods and services.7 ETCs on expressways and automatic ticket gates at railway stations have already been broadly adopted as infrastructure to enable consumers to receive services smoothly without the trouble of waiting in line or paying cash. There is the possibility that self-checkout systems that are being introduced in some stores may be further developed, and it may become normal that consumers simply pick up goods at stores and leave without making payments at self-checkout machines, and stores will able to ascertain and analyze their customers' purchase records by the use of IT and AI. The standardization of data discussed by the WG is the first step to realize such a future. Data standardized as recommended by the WG is expected to be broadly utilized by diverse users for various purposes, not limited to RESAS, which serves as the foundation of the WG discussions. If further pioneering initiatives like RESAS are made and additional data that should be developed cooperatively among related parties is found, the standardization of data will be facilitated more broadly. Efforts to be made among companies having close business relationships are also expected. In such cases, data development will be first discussed in a closed environment and data thus developed will later be disclosed and utilized. In any case, when all efforts for better utilizing data come to steadily bear useful outcomes, this will encourage people to participate in and accelerate similar efforts, leading to further advancing the standardization of data.

Technological innovation and entry of new players have been drastically changing the environment surrounding the credit card industry. In particular, taking advantage of technological innovation in the IT field, FinTech companies have been creating new advanced financial services of granting loans, offering insurance, managing assets, or scoring credits, through managing and utilizing various big data, not limited to only

7 The interim report by the Dispersal Strategy Working Group under the Information Economy Subcommittee, Commerce and Distribution Information Committee of the Industrial Structure Council points out the importance of the approach to ensure that personal data is held independently by individuals, instead of being collected by companies as in the conventional manner, and are managed and provided at one's own initiative, from the perspective of protecting one's privacy.

offering settlement services. They have been entering business fields where financial institutions have had an overwhelming dominance. These companies meticulously respond to consumer needs and consider the financial business as a mean by which to resolve social problems through offering medical services in an increasingly aging society and enhancing current industrial supply chains. They may speedily and flexibly commence new services and further expand their business even beyond the financial business. Such movements are especially notable overseas. Efforts to strengthen and expand existing business are important for credit card companies, but considering the existence of such newly emerging competitors that have been achieving business expansion with such speed, it is becoming increasingly difficult to strengthen and expand business only based on conventional revenue sources and revenue structures. During the discussions of the Study Group on the Credit Card Industry and Big Data, some mentioned that credit card data has an advantage in the quality, accuracy and volume of information on members. However, such advantage may sooner or later be complemented and replaced by other means or players under a dramatically changing environment. Now is the time for credit card companies to take action quickly in order to continue contributing to promoting the shift to a cashless society, maintaining dominance in the big data business and also fulfilling a role in resolving societal challenges.

List of WG Members

(1) International credit card brands Visa Worldwide (Japan) Co., Ltd. Mastercard

(2) Credit card companies (acquirers) Sumitomo Mitsui Card Co., Ltd. Mitsubishi UFJ NICOS Co., Ltd. UC Card Co., Ltd. Rakuten Card Co., Ltd. (In the order of the Japanese syllabary)

(Attachment) Guidelines for Business Type Codes in Credit Card Data [Basic Policy] ・Business type codes sent from acquirers to international credit card brands should preferably be assigned under a uniform concept shared among relevant companies in line with the guidelines of international credit card brands. ・In particular, if international credit card brands have not established any clear guidelines for the following types of member stores, business type codes should preferably be assigned based on each company's judgment by referring to these guidelines, in accordance with such information as the line of products and sales ratio.

Types of member stores Guidelines In the case of stores in the mode of wholesalers, for those relating to PCs, for example, the business type code should be 5045 (Computers and Computer Peripheral Electric appliance stores Equipment and Software). In the case of stores in the mode of retailers targeting ordinary consumers, either 5722 (Household Appliance Stores) or 5732 (Electronics Stores) should be selected. When a store can be recognized as a duty-free store, 5309 (Duty Free Stores) should be selected. Duty-free stores When the business mode cannot be clearly defined as a duty-free store, the business type code should be assigned depending on the line of products. ○ When a store is separately registered as an individual store ・When a store can be recognized as a duty free store, 5309 (Duty Free Stores) should be selected. ・When the business mode cannot be clearly defined as a duty free store, the business type code should be assigned depending on the line of products. St o r es in air p o r t s ○ When multiple stores are integrally registered, for example, as a unit of a certain area ・When an area can be recognized as a duty free area, 5309 (Duty Free Stores) should be selected. ・When the business mode of a duty free store is not definitely applicable for an area, 5311 (Department Stores) should be selected. Shopping malls, fashion buildings and 5311(Department Stores) outlet malls (commercial complexes) Discount stores 5310(Discount Stores) Secondhand brand shops 5931(Used Merchandise and Secondhand Stores) Ticket shops 7922(Theatrical Producers (Except Motion Pictures) and Ticket Agencies) T here is no business type code for brand-name shops, so the business type code should be assigned depending on t he line of products. Brand-name shops （Ex.）5948(Luggage and Leather Goods St ores) 5621(Women’s Ready-To-Wear Stores) Souvenir shops 5947(Gift, Card, Novelty and Souvenir Shops) Character goods stores and toy stores 5945(Hobby, Toy, and Game Shops) Stores dealing with miscellaneous goods, household articles, bags and other 5331(Variety Stores) various goods Convenience stores 5499(Miscellaneous Food Stores – Convenience Stores and Specialty Markets) 5814(Fast Food Restaurants) Fast food restaurants When the business mode cannot be clearly defined as a fast food restaurant, 5812 (Eating Places and Restaurants) is one option. Basically, 5912 (Drug Stores and Pharmacies) should be selected, but 5977 (Cosmetic Drugstores Stores) may also be applicable. Basically, 5411 (Grocery Stores and Supermarkets) should be selected. Large supermarkets However, when food is not sold or the ratio of food is small, the business type code should be assigned depending on the line of products. Amusement facilities 7996（Amusement Parks, Circuses, Carnivals, and Fortune Tellers） < Remarks > In the case of shopping malls or other commercial complexes, if any individual store therein concludes a tenant contract independently and has installed original POS terminals, etc., such store is not prohibited from selecting a business type code independently depending on the line of products.