TWI739239B - Specific merchant recommendation system of financial institutions and method thereof - Google Patents

Abstract

A specific merchant recommendation system of financial institutions and method thereof are provided. A destination entered by a customer is confirmed whether a external environment of the destination is suitable for travel. And then a specific merchant is based on the external environment of the destination, a customer consumption information, and merchant types to make comprehensive consideration recommendations. In addition, if the recommended merchant is not consumed by the customer, then the system will be combined the external environment, the customer consumption information, and the merchant types to adjust the recommended merchant again.

Description

Specific merchant recommendation system and method of financial institution

The present invention relates to a system and method for recommending a specific merchant of a financial institution.

At present, the Internet and smart phones are an indispensable part of people's lives, especially the applications and services on top of them. For example, using mobile payment to consume various goods or services is much more convenient and faster than general payment methods such as cash.

However, if a customer wants to plan to travel or spend at a specific location, usually the customer can only plan in advance to query the relevant external environment website and the official website of a specific business to obtain relevant information, and then query the map at this address to obtain information about the specific business nearby. Route, for example, to check the expected local temperature, rainfall, UV, wind, air quality, traffic information, etc., wait until it is suitable, and then continue to check for suitable stores. Such a lengthy step usually takes a lot of planning time for customers. Brings many inconveniences to customers.

Therefore, there is currently no comprehensive external environment data that can tell customers in advance whether they are suitable for travel or consumption. After confirming that they are suitable for traveling, customers will actually consider their internal environment such as age, interest, place of residence, consumption history, etc., external environment Such as temperature, Rainfall, ultraviolet rays, air volume, air quality, traffic information, etc., as well as business types such as food, clothing, housing, transportation, education, entertainment, etc., through the bank’s customer historical consumption database, including the external environment information of the consumption day, The types of merchants and customer consumption information, etc., and then recommend and guide customers' most suitable behavior patterns.

In addition, nowadays extreme weather has become the norm, so recommending suitable businesses must first consider whether the external environment is suitable from the customer's point of view. Therefore, a recommendation method that prioritizes the customer's main body is used to first evaluate the factors of the external integrated environmental data, and then match the action to pay the customer and the specific merchant.

In summary, although customers’ consumption behaviors are all different, it is hoped that when the external environment and background are suitable, combined with internal information and types of businesses, we can transplant the experience of our customers as much as possible to recommend specific businesses to customers. It is hoped that after grasping customer behavior, we can recommend relevant specific merchants to interested customers as much as possible, so as to meet the needs of diverse customers, create consumer demand, and obtain better profits for the bank.

In view of this, one of the objectives of the present invention is to provide a system and method for recommending a specific merchant of a financial institution. The two-stage comprehensive recommendation method is used to improve the simple recommendation method. After the customer enters the destination, first confirm whether the external comprehensive environment of the destination is suitable for travel, and then comprehensively consider the external environment of the destination, customer consumption data, and business type recommend. In addition, the recommendation can be revised immediately, that is, after the customer consumes, if the merchant does not follow the recommended consumption, the local external environment, customer consumption information, and type of merchant can be adjusted to suit the merchant again.

The system of the present invention includes a merchant category database, an external environment data conversion and classification module, an external comprehensive environment recommendation module, a customer consumption database, and an analysis comparison recommendation module.

The above-mentioned merchant category database is to store the basic data of multiple merchant categories authorized by the financial institution.

The above-mentioned external environment data conversion grading module is to receive the predetermined consumption data under the predetermined consumption environment from the client device, and is used to classify a variety of external environment data and convert them into a comprehensive index of the external environment.

The above-mentioned external comprehensive environment recommendation module is to recommend a predetermined consumption environment to the client device when the comprehensive index is greater than or equal to the predetermined threshold, and to recommend other consumption environments when the comprehensive index does not reach the predetermined threshold.

The above-mentioned customer consumption database is to store multiple consumption information. The consumption information includes multiple consumption records of a customer account, consumer information for each consumption record, and consumption composite index. The above-mentioned consumer information is the type of merchant for the consumption record. The basic data of attribution, the comprehensive consumption index is the comprehensive index corresponding to the external environment when the consumption record occurs.

The above analysis and comparison recommendation module is based on the external environment data combined with the basic data of the merchant category. Some merchants are screened for the first time, and then the merchants are screened for the second time based on the information in the customer consumption database to obtain personalized information. Recommendation ranking of a specific merchant or a specific combination of merchants, recommending a specific merchant or a specific combination of merchants to the client device.

According to another embodiment of the present invention, the system of the present invention further includes a merchant consumption system authorized by a financial institution to record the consumption information and return the consumption record to the customer Household consumption database, in which the consumption records are the merchant, consumption amount, consumption date and time, or any combination of the above.

According to another embodiment of the present invention, the aforementioned comprehensive index is a temperature comfort index, a rainfall classification, an ultraviolet index, an air volume classification, an air quality index, a traffic index, activities in related counties and cities, or any combination of the foregoing.

According to still another embodiment of the present invention, the above-mentioned external comprehensive environment recommendation module further includes displaying the reason why the comprehensive index has not reached the predetermined threshold value, and displaying the reason why the other consumer environment is recommended.

According to still another embodiment of the present invention, the aforementioned predetermined consumption data is the current location of the client device, tourist area information, travel date, start and end locations, or any combination of the foregoing.

Based on the above, the present invention uses a two-stage comprehensive recommendation method to first determine whether the comprehensive environment of the predetermined consumption data is suitable for travel, and then screen out suitable merchants based on customer consumption data and merchant category data. In addition, after the customer makes a purchase, the recommended merchant will be automatically corrected based on the recommendation result judged by the recommended merchant based on the consumption information. Therefore, it can save many customers' time in planning their trips, and effectively increase the efficiency of finding recommended businesses.

In summary, the present invention is to provide a specific merchant recommendation system and method for financial institutions. It is expected to find out the strength and relevance of customer consumption through the analysis and combination of the external environment and customer consumption information. Therefore, it no longer recommends based on the "maximum number", but considers the "internal and external environmental factors" to conduct a "relatively majority" recommendation method to improve the efficiency of customers' search for recommended businesses and the probability of accepting recommendations.

110: Internal systems of financial institutions

111: Business Type Database

112: External environment data conversion classification module

113: Recommended Module for External Comprehensive Environment

114: Customer consumption database

115: Analysis and comparison recommended module

120: client device

130: Merchant consumption system

200-255: steps

In order to make the above and other objectives, features, advantages and embodiments of the present invention more comprehensible, the description of the attached drawings is as follows: Figure 1 shows a specific merchant recommendation of a financial institution according to an embodiment of the present invention The relationship architecture diagram of each module in the system.

FIG. 2 is a schematic flowchart of a method for recommending a specific merchant of a financial institution according to an embodiment of the present invention.

Please refer to FIG. 1. FIG. 1 is a diagram showing the relationship structure of each module in a specific merchant recommendation system of a financial institution according to an embodiment of the present invention. The specific merchant recommendation system of the financial institution in FIG. 1 includes an internal system 110 of the financial institution, a client device 120, and a merchant consumption system 130.

The aforementioned financial institution internal system 110 includes a merchant category database 111, an external environment data conversion and classification module 112, an external comprehensive environment recommendation module 113, a customer consumption database 114, and an analysis comparison recommendation module 115.

The above-mentioned merchant category database 111 stores the basic data attributable to multiple merchant categories. The categories of the above-mentioned businesses can be, for example, basic information such as food, clothing, housing, transportation, education, entertainment, extremes, etc. The businesses are classified into indoor and outdoor categories, and the "food" area is further divided into hot food, cold food, cold and hot All categories are distinguished. The above-mentioned basic information can be, for example, a business name, telephone number, address, business hours, website address, customer reviews, or any combination of the above. Jirui refers to recommendations under special circumstances, for example, recommending skiing and hot spring businesses when it is extremely cold. When it's extremely hot, water sports businesses are recommended. The aforementioned merchant type database 111 can be any available database.

The above-mentioned external environment data conversion and classification module 112 captures the external environment from various open platforms such as the Central Meteorological Administration Open Data Platform, the Environmental Protection Agency Environmental Resources Open Data Platform, the Highway Administration Development Data Platform, and the Taipei City Tourism Net Open Platform, etc. material. The external environment data can be, for example, temperature, rainfall, ultraviolet, wind, air quality, traffic information, and activity data of related counties and cities, for example, programs, events, and so on. With date and time as the key value, if there is non-breakpoint classification data, it will be converted into breakpoint classification data and then classified, and the breakpoint classification data will be stored. For example, the temperature in Table 1 below is non-breakpoint classification data, and the temperature will change with different times, so it is converted into breakpoint data with date and time as the key value, and then the temperature is classified by the classification conversion table. The above-mentioned external environment data conversion and classification module 112 is a software program, which can be any available computer device, such as a personal computer, a laptop or a handheld electronic device.

The following table 1 to table 6 are the external environmental data conversion grading tables.

The external comprehensive environment recommendation module 113 is the predetermined consumption data input by the customer, such as destination and date, and obtains a comprehensive index through the external environment data conversion grading table. If the single index is 0, or the composite index does not reach a predetermined threshold, it will not be recommended and the reason will be notified. Instead, alternative locations and businesses with a composite index greater than a predetermined threshold will be recommended and the reason will be notified. The external integrated environment recommendation module 113 is a software program, which can be any available computer device, such as a personal computer, a laptop, or a handheld electronic device.

According to an embodiment of the present invention, if a customer expects to arrive at Neiwan Old Street on 1/1 day, the recommended predetermined threshold must be greater than 50 points. The comprehensive index of the external environment on that day reached 70 points, so you can directly recommend businesses near Neiwan Old Street, and inform the analysis of the reasons for the recommendation, such as comfortable temperature, moderate UV index, good air quality, etc.

According to another embodiment of the present invention, if a customer expects to arrive at Neiwan Old Street in 2/2 days, the recommended predetermined threshold must be greater than 50 points. The composite index of the external environment on that day only reached 40 points, and the analysis was informed of the reasons for not recommending, such as very cold temperature, heavy rainfall, strong wind and so on. Therefore, we recommend another similar place, Tamsui Old Street with a comprehensive index of 90 points for the external environment that day, and inform the analysis of the reasons for the recommendation, such as comfortable temperature, good air quality, and normal ultraviolet rays.

According to another embodiment of the present invention, if a customer expects to arrive at Neiwan Old Street in 3/3 days, the recommended predetermined threshold must be greater than 50 points. Although the composite index of the external environment reached 60 points on that day, a certain index is 0. For example, the air quality is at a "hazardous" level. Therefore, Neiwan Old Street is not recommended, and another similar location is recommended instead.

The above-mentioned customer consumption database 114 is for storing multiple consumption information, including consumption records of customer accounts, consumption merchant information of each consumption record, and consumption comprehensive index. The consumption record is the data that the merchant consumption system 130 requests authorization from the financial institution, and the financial institution authorizes the reply, such as the date and time of consumption and the amount of consumption. The consumer business information is the basic data attributable to the business category in the consumer record. The consumption composite index is the composite index corresponding to the external environment when the consumption record occurs. The aforementioned customer consumption database 114 can be any available database.

The above analysis and comparison recommendation module 115 is based on the input data of the current location, designated date, destination, etc., and obtains the external environment data combined with the basic data of the merchant category, and screens out the merchants that meet the threshold for the first time. Then, through the information in the customer consumption database, the merchants are selected from the merchants that meet the threshold for a second time, and the personalized recommendation ranking of the specific merchant or the specific merchant combination is obtained, and the specific merchant or the specific merchant combination is recommended to the client device 120. The above analysis and comparison recommendation module 115 can be, for example, a software program, loaded on any available computer device, such as a personal computer, a laptop or a handheld electronic device.

According to another embodiment of the present invention, a customer expects to travel to Tainan on 4/4, and has obtained the current external environment data of Tainan as "sultry, no rain, moderate ultraviolet rays, good air quality, clear wind, and smooth traffic." It has passed the recommendation of the external environment integrated module. According to the above-mentioned external environment data, suitable businesses are selected, for example, hot and cold food stores, clothing stores, and lodging stores that are suitable for indoor and outdoor are all on the candidate list. Then through the information in the customer consumption database, for example, the customer often goes to eat cold food, go shopping, etc., combined with the candidate list merchants, analyze and compare the merchants with the most comparisons among all the customer's consumption information to make a recommendation list.

In addition, after the customer consumes, the merchant consumption system 130 returns the consumption record to the customer consumption database 114, and sends the consumption information to the analysis comparison based on the consumption record that has occurred. For the recommendation module 115, the recommended merchants are adjusted again in combination with the external environment data of the consumption place, the types of merchants in the consumption place, and the customer's consumption data.

According to yet another embodiment of the present invention, a customer originally expected to play in Jiufen, and because the external environment is not suitable, the customer has been recommended to play in Neiwan, but the customer is still playing in Jiufen, so the consumption information is still recommended The system analyzes and compares the recommended modules to re-recommend.

According to another embodiment of the present invention, a certain customer is playing in Jiufen, and the recommendation system has recommended related stores, but the store the customer consumes is not in the list of recommended stores, and the consumption information is still sent to the analysis comparison recommendation module to do it again recommend.

FIG. 2 is a schematic flowchart of a method for recommending a specific merchant of a financial institution according to an embodiment of the present invention. Please refer to Figs. 1-2 at the same time. Step 200 in Fig. 2 is the beginning. In step 205, the customer inputs the scheduled consumption data in the scheduled consumption environment to the client device 120, and the internal system 110 of the financial institution will receive the scheduled consumption data.

In step 210, the external environment data conversion grading module 112 classifies a variety of external environment data and converts them into a comprehensive index of the external environment. Then in step 215, the external comprehensive environment recommendation module 113 displays the environment analysis result. In step 220, if the composite index is greater than or equal to a predetermined threshold value, the predetermined consumption environment is recommended to the client device, if a predetermined threshold value is not reached, then it returns to step 215 to recommend other consumption environments whose composite index meets the standard to the client device. The client device.

In step 225, obtain the basic information of multiple merchant categories authorized by the financial institution in the merchant category database 111, and based on the external environment data combined with the basic information of merchant category attribution, screen out for the first time those that meet the predetermined threshold Business.

In step 230, a plurality of consumption information in the customer consumption database 115 is obtained, and the consumption information includes a plurality of consumption records of a customer account, the consumption merchant data of each consumption record, and the current consumption comprehensive index. The consumption record is the data that the merchant consumption system 130 requests authorization from the financial institution, and the financial institution authorizes the reply. The consumer business information is the basic data attributable to the business category in the consumer record. The consumption composite index is a composite index corresponding to the external environment when the consumption record occurs. According to the information in the customer consumption database 115, the merchants are screened for the second time, and then go to step 235 to sort out personalized recommendations of specific businesses or combinations of specific businesses, go to step 240, and display the results on the client device 120.

In step 245, if the customer accepts the recommendation, it proceeds to step 255, where the customer goes to the recommended particular merchant or combination of particular merchants. If the client does not accept the recommendation, go back to step 235. After the customer consumes, the merchant consumption system 130 returns the consumption record to the customer consumption database 114. According to the consumption records that have occurred, the consumption information is sent to the analysis, comparison and recommendation module 115, and the recommended merchants are adjusted by combining the external environment data of the consumption place, the type of merchants in the consumption place, and the customer's consumption data. Steps 240-250 are then performed in sequence, and finally step 255 is entered to complete the merchant recommendation.

According to the above disclosed system and method, it can improve the process of customers searching for recommended businesses on the Internet and then screening according to their own interests in combination with external weather, festivals and other factors, and converting it into a system analysis. First, analyze whether the environment is suitable for travel. Based on the external environment of the destination, the types of businesses, and customer consumption data, comprehensive consideration and recommendation are made to shorten the time for customers to plan their trips. Moreover, the recommended merchants will be automatically revised as the consumption records are updated.

Although the embodiments of the present invention have been disclosed as above, they are not intended to limit the present invention. Those who are familiar with the art will follow the spirit of the present invention without departing from the present invention. Various changes and modifications can be made within the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be subject to those defined by the subsequent patent applications.

110: Internal systems of financial institutions

111: Business Type Database

112: External environment data conversion classification module

113: Recommended Module for External Comprehensive Environment

114: Customer consumption database

115: Analysis and comparison recommended module

120: client device

130: Merchant consumption system

Claims (10)

A specific merchant recommendation system for financial institutions, including: a merchant category database, which stores the basic data attributable to multiple merchant categories authorized by the financial institution; an external environment data conversion grading module, which receives a reservation from a client device One of the predetermined consumption data under the consumption environment, and used to classify multiple types of external environment data and convert them into a comprehensive index of the external environment; an external comprehensive environment recommendation module, which recommends the predetermined consumption environment to the client device as the comprehensive index If the index is greater than or equal to a predetermined threshold, recommend a different consumer environment to the client device when the composite index does not reach the predetermined threshold; a consumer consumer database, storing a plurality of consumer information, the consumer information includes a plurality of customer accounts Consumption records, data of one consumer business for each of the consumption records, and a comprehensive consumption index, where the consumer business information is the basic data attributable to the types of businesses in the consumption records, and the consumption comprehensive index corresponds to the consumption The comprehensive index of the external environment at the time the record occurred; and an analysis and comparison recommendation module, based on the external environment data combined with the basic data of the business categories, to screen out multiple businesses for the first time, and then based on the The consumption information of the customer consumption database is screened for the second time to obtain the personalized recommendation ranking of a specific merchant or a specific combination of merchants, and the specific merchant or the specific combination of merchants is recommended to the client device. The specific merchant recommendation system of the financial institution according to claim 1, further includes a merchant consumption system authorized by the financial institution to return the consumption records to the customer consumption database, wherein the consumption records are consumption records Merchant, consumption amount, consumption date and time or any combination of the above. According to the specific merchant recommendation system of the financial institution mentioned in claim 1 The comprehensive index is temperature comfort index, rainfall classification, ultraviolet index, air volume classification, air quality index, traffic index, activities of related counties and cities, or any combination of the above. According to the specific merchant recommendation system of a financial institution according to claim 1, wherein the external comprehensive environment recommendation module further includes displaying the reason why the comprehensive index has not reached the predetermined threshold, and displaying the reason why the other consumer environment is recommended. According to the specific merchant recommendation system of a financial institution according to claim 1, wherein the predetermined consumption data is the current location of the client device, tourist area information, travel date, start and end locations, or any combination of the foregoing. A method for recommending a specific merchant for a financial institution, including: a customer inputs a predetermined consumption data in a predetermined consumption environment to a client device; a financial institution internal system receives the predetermined consumption data; classifies and transfers plural kinds of external environment data As a comprehensive index of the external environment, if the comprehensive index is greater than or equal to a predetermined threshold, recommend the predetermined consumption environment to the client device, if it does not reach the predetermined threshold, recommend another consumption environment to the client device; obtain finance The basic data attributable to a plurality of merchant categories authorized by the organization; to obtain a plurality of consumption information of the customer, the consumption information includes a plurality of consumption records of a customer account, one of the consumption records of each of the consumption records, and a comprehensive consumption Index, where the consumer business information is the basic data attributable to the business categories of the consumer records, and the consumer composite index is the composite index corresponding to the external environment when the consumer records occur; based on the external environment data Combining with the basic information of the categories of these businesses, a plurality of businesses are screened for the first time; according to the consumption information, these businesses are screened a second time, and a personalized feature is sorted. A recommendation of a specific merchant or a combination of a specific merchant; and the recommendation of the specific merchant or a combination of the specific merchant is displayed on the client device. According to the specific merchant recommendation method of the financial institution described in claim 6, it further includes a merchant consumption system authorized by the financial institution to return the consumption records to a customer consumption database, where the consumption records are the merchants and the consumption Amount, date and time of consumption or any combination of the above. According to the specific business recommendation method of the financial institution described in claim 6, wherein the comprehensive index is temperature comfort index, rainfall classification, ultraviolet index, air volume classification, air quality index, traffic index, activities of related counties or cities, or any of the above combination. According to the specific merchant recommendation method of the financial institution described in claim 6, if the composite index does not reach the predetermined threshold, the recommendation will not be recommended and the reason will be notified, and the other consumer environment that is greater than the predetermined threshold will be recommended instead. reason. According to the specific merchant recommendation method of a financial institution according to claim 6, wherein the predetermined consumption data is the current location of the client device, tourist area information, travel date, start and end locations, or any combination of the foregoing.

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