JP5487277B2 - Housing loan refinancing business support system - Google Patents

Description

  The present invention provides a housing that can provide a refinancing business support by reliably searching or investigating a customer who may refinance a mortgage on an objective basis in the promotion of a mortgage refinancing operation in a financial institution such as a bank. Regarding the loan refinancing business support system, especially for new and old housing maps, the difference between the old (1 year to multiple years) old housing map and the current new housing map is extracted, and the new construction is based on the difference. Extracting changes in buildings and residential land to select customers who have the potential to refinance mortgages, narrowing down customers by collaborating with external databases such as existing customer information owned by financial institutions A mortgage loan that can support the financial institution's sales activities by determining credit rankings and rankings for refinancing and extracting potential business candidates (potential refinancing customer candidates) About the place of sales support system.

  When purchasing real estate such as homes and land, real estate buyers are generally from financial institutions such as banks with real estate as collateral, and from public institutions such as housing finance corporations (hereinafter simply referred to as “financial institutions”). Borrow a mortgage. For a financial institution, acquiring a large number of mortgages under better conditions is a major business objective, so it is necessary to take into account and use the differences in interest rates and conditions of mortgages that differ for each financial institution. In many cases, customers who borrow housing loans at institutions (hereinafter referred to simply as “prospects”) propose refinancing to their own banks. In order for a financial institution to make a proposal for refinancing a home loan, select a major sales office from its own beta base or a list of public institutions that have provided loans on behalf of the bank, or conduct a registry survey, etc. You will need to encourage prospective customers to refinance their home loans.

  However, because it takes a lot of labor and time to extract and select potential sales partners using the know-how of each salesman, we cannot respond to real estate fluctuations and customer changes, and we propose mortgage refinancing proposals. The loss of business opportunities such as losing the timing of For this reason, the emergence of a method and a system for efficiently utilizing existing information and extracting potential business partners quickly and reliably.

  Due to restrictions imposed by the Personal Information Protection Law, it has become difficult to collect information on customers borrowing mortgages. At present, computer processing is faster, main memory and external storage devices are larger, and network speeds are higher. Using highly developed information processing technology such as widening and widening the area, analyzing information owned by financial institutions from various angles, quickly and accurately extracting business candidates, further ranking etc., A mechanism or system for narrowing down potential sales partners is necessary, but at present there is no such mechanism or system.

JP 2005-284720 A JP 2006-85397 A

  In financial institutions, in combination with the enforcement of the Personal Information Protection Law, there are situations where it is difficult to collect information on customers who borrow housing loans from other banks. The emergence of a system that can support sales by collecting and analyzing the mortgage, which can acquire a powerful mortgage refinancing customer (a leading sales partner) is strongly desired.

  The present invention has been made under the circumstances as described above, and the object of the present invention is to collect, exchange, and process data using IT technology using GIS from a terminal such as a personal computer, Establish an analysis system, extract prospective customers by extracting the difference in secular change from old and new housing maps, rank the prospects by adding judgment on whether or not to refinance mortgages, and select potential business partners The purpose is to provide a mortgage refinancing business support system that can extract and efficiently support the business activities of financial institutions.

The present invention relates to a mortgage refinancing business support method, and the above-described object of the present invention is to calculate a position of a prospective customer and a financial institution by a computer extracting a different part of the old house map data and the new house map data over time. In cooperation with an external database owned by the company, the existing business partner of the financial institution is deleted from the difference, and a preliminary business partner is obtained. Based on the entered registry, registry data, and field survey results, This is achieved by determining whether or not to exclude the preliminary business partners, obtaining business candidate candidates, ranking the business candidate candidates that are not determined to be excluded, and displaying them in a list.

Further, the present invention relates to a mortgage refinancing business support system, and the above object of the present invention is to extract different difference data between the new house map data and the old house map data, and the address position on the registry data of the difference data. A difference part extraction / position display means for displaying the data, a cooperation means for linking with an external database that utilizes and operates the supplier data, and an existing transaction obtained from the external database based on the external data captured by the cooperation means An existing supplier elimination means for erasing the point from the difference portion data to obtain a preliminary business partner, an input means for inputting a register, registry data, and field survey details, and input by the input means Exclusion determination means for determining exclusion of the preliminary business partner based on the data and selecting business candidate candidates, and for the business candidate candidates not excluded by the exclusion determination means Perform the link with finding a leading business destination and ranking means is achieved by immediately Bei be Rukoto.

  According to the mortgage refinancing business support system of the present invention, a new building or residential land is obtained by obtaining a secular change in real estate from a difference between the old and new residential maps for one year to multiple years from a residential map provided in the market. Using the ranking conditions obtained by analyzing changes in mortgages that are properly obtained and owned by financial institutions from various angles, the prospects can be ranked objectively and quickly. Therefore, it is easy to select or grasp the leading lenders, and can greatly assist the sales of financial institutions that promote mortgage refinancing. By providing this sales support, financial institutions can reduce the cost of sales, and they are also compelling because they are based on objective data in customer explanations, which can increase the number of contracts for mortgage refinancing. it can.

  For financial institutions, prospects can be extracted quickly and efficiently, and area marketing based on analysis of the results and development to new financial products will be possible.

  Until now, the latest information has always been maintained on the housing map, so if a new product was sold the following year for the housing map maker, the old product lost its product value. However, if it can be used to obtain information by comparing old and new, the value of the old product is also created, and as a result, it can contribute to the sales of the housing map maker.

  In addition, since the collection of information is greatly restricted by the Personal Information Protection Law, you must look up the published information and your own footage, such as browsing a registered copy or field survey, in order to know information on changes in the city. You have to spend people, time and money. However, if the system of the present invention is utilized, a quick and accurate business candidate can be obtained, and the reduction of people, time, and costs can be achieved. Furthermore, the present invention, in which data is extracted from an existing database owned by the company and merged with map data, has the advantage of enhancing the information value of the existing data and having a high degree of contribution to work by introduction.

It is a figure which shows the business flow of the financial institution to which this invention is applied. It is a flowchart of the selection business of the powerful sales partner in a financial institution. It is a flowchart which shows the example of selection processing of an influential business partner. It is a block diagram which shows the structural example of one Embodiment of this invention. It is a block diagram which shows the detailed structural example of a difference part extraction / position display means and the existing supplier elimination means. It is a flowchart which shows the operation example of a difference part extraction / position display means and an existing supplier elimination means. It is a block diagram which shows the structural example of an exclusion determination means. It is a flowchart which shows the operation example of an exclusion determination means. It is a block diagram which shows the structural example of a ranking means. It is a flowchart which shows the operation example of a ranking means. It is a flowchart which shows the operation example of this invention. It is a figure which shows an example of the identification character and attribute name of an old and new house map. It is a map which shows the example of extraction of a new building. It is a figure which shows an example of the list of influential business partners. It is a flowchart which shows the operation example of exclusion information utilization in this invention. It is a figure for demonstrating the operation | movement of exclusion information utilization in this invention.

  With the increase in the speed of computer processing and the increase in the size of main storage devices and external storage devices, GIS for processing map information such as house maps has been developed. In the present invention, for example, an old house map one year ago and the present Change of new building and residential land from difference with new housing map of, and extract prospective customers (customers who have received mortgages from other financial institutions) by cooperation technology with customer database owned by financial institutions In addition, we perform credit judgment and ranking of whether or not to refinance mortgages, and select or grasp the major refinancing destinations (leading sales partners) to efficiently support the financial institution's mortgage refinancing business activities. Trying to get.

  The mortgage refinancing business support system of the present invention is conceptually implemented as in the business flow of FIG. In other words, the flow of financial institutions is “expectation of potential customers” → “selection of potential sales partners” → “sales activities” → “aggregation of results”. It covers the business of creating a list of leading sales companies ranked in “Selection”. In the prospect extraction, the extraction conditions such as the municipality name and the building type are specified for the old house map and the new house map, the change of the new building and the residential land is obtained, and the prospect is extracted. When prospective customers are extracted, the bank will exclude the prospective customers who have already provided mortgage loans from the prospective customers, select a preliminary business, and then investigate the registry (address on the registry) Position), conduct field surveys, input survey results, select business candidates, and further rank them to select leading business partners.

A list of customers that the bank has already provided for mortgage loans is managed by a customer database such as a cleaning system operated by the bank. For example, the rehabilitation system compares the repayment status and balance of mortgages that have already been lent by financial institutions with the valuation of real estate that is secured as collateral, and calculates the safety and maintenance rates for each debtor. This is a general system that is almost implemented and operated by financial institutions that have introduced a collateral evaluation system. Replacement is required four times a year, and the valuation value of the real estate at that time is calculated and compared with the balance. Figure 2 shows the flow of selecting a major business partner at a financial institution. In addition to conducting a registry survey on the preliminary sales partners that have deleted their existing lenders from prospective customers and entering the survey results (step S1), conducting a field survey and entering the survey results ( In step S2), suitability as a business partner is determined (step S3). A registry survey and a field survey will reveal the status of mortgage and the surrounding situation of a preliminary business. If it is suitable as a mortgage refinancing destination, this is set as a business candidate, and the priority is further ranked to select a potential business partner (step S4). Exclude (step S5). As a priority ranking, for example, “the borrowing amount is high and the interest rate is close to review” has a higher priority, and conversely, “the borrowing amount is low” or “the borrowing date is recent” Has a lower priority.

  The financial institution conducts sales activities after selecting a major sales partner in this manner, but a salesperson or the like inputs a record of sales activities, inputs results, and stores a sales history in a database or the like. Further, the financial institution collects the results of the contracts, analyzes the results of the analysis, and uses them for the next sales activity.

  FIG. 3 is a flowchart showing an example of the processing of the present invention for automatically selecting a leading business partner. A registry business survey is performed on the automatically extracted preliminary business partner and the survey result is input (step S10) Further, a field survey is performed and the survey result is input (step S11), and an exclusion determination process based on suitability determination is executed (step S12). For example, the registration items and the survey items in the field survey are mastered, an exclusion flag is provided, the item “land texture” is mastered, and the master is created as shown in Table 1. In other words, the place name “residential land” is not attached with the exclusion flag, but the other place names “field”, “field”, and “hybrid place” are attached with the exclusion flag.

As a result of the investigation, the presence / absence of the master exclusion flag in Table 1 above is determined from the input value of “land texture”, and the exclusion determination is performed by automatic processing. When the exclusion flag is determined, the business is excluded (step S14). ). The present invention is a refinancing of a mortgage loan, and anything other than “residential land” is not suitable for loan. In addition to the determination based on the exclusion flag, the following exclusion determination can be considered. For example, “Building age more than 25 years”, “Existing mortgage or root mortgage setting date is less than 3 years”, “Existing mortgage root mortgage is less than 10 million yen”. In addition, by using the survey results and the data of the publicly announced place, reference place, and route price, it is possible to calculate a simple evaluation value of the target property of the business partner. Therefore, a simple evaluation of the property is performed, and the building evaluation value is 0, and the maintenance rate at the time of new construction (simple evaluation value ÷ total borrowing amount) is 80% or less, the exclusion flag is attached.

  Next, rank determination is performed after the above-described exclusion determination process (step S13), and a major business partner is selected. The rank determination needs to be determined from various angles such as financial institution side merit, customer side merit, and business time. For this reason, the rank is not determined only by a specific item, but is scored by the values of a plurality of items, and is ranked by the total score. Conceptually, the system has a scoring table as shown in Table 2 below.

As a scoring result, for example, a rank “A” is given as high priority if it exceeds 100 points, and a rank “B” is given if it exceeds 80 points, and rank determination is automatically performed. That is, the system automatically performs simple evaluation based on the input information, and ranks the system based on the result. In this case as well, “the borrowing amount is high and the interest rate is close to review” is given a higher priority, and “the borrowing amount is low” or “the borrowing date is recent” is lowered. As described above, the present invention uses a customer database such as an automatic refurbishment system that obtains a changed part of a building and a residential land from old and new residential maps and manages the maintenance status of mortgage loans held by financial institutions. Eliminate existing business partners, determine the suitability and ranking of remaining customers as preliminary business partners, select leading business partners, support sales activities for mortgage refinancing at financial institutions, and aggregate results It will be used next time.

  FIG. 4 shows an embodiment of the present invention. For example, an old house map database 1A two years ago and a current new house map database 1B are prepared. Is displayed. The old house map database 1A and the new house map database 1B both hold the identification number for the building and the type of building ("personal house", "office", "named building", "target"), etc. ing. A difference portion extraction / position display means 3 is provided for extracting a difference portion (for example, a new building) from a different part from the old house map and the new house map displayed on the map display means 2 and displaying the position thereof. By subtracting the customer data TD from the difference partial data, which is a secular change part such as a building, through the exchange system 10 operated by the financial institution and the linking means 11 as an interface, the borrower of the bank is differentiated. An existing supplier erasure unit 4 is provided for specifying a range (preliminary business SB) that can be erased from the portion and operated.

  In addition, since the washing | cleaning system 10 has the positional information on a real estate, it can arrange | position and display on a housing map by (circle) etc. in the applicable position. In addition to the replacement system 10, it may be connected to a customer database such as an automatic examination system or a collateral evaluation system.

  FIG. 5 shows the detailed configuration of the difference part extraction / position display means 3 and the existing supplier deletion means 4. The difference part extraction / position display means 3 detects the difference part between the old house map and the new house map. The extraction unit 31 includes a color conversion unit 32 that changes the color of the extracted difference portion, and a position display unit 33 that displays the color-converted difference portion on the new house map. In addition, the existing supplier deleting means 4 compares the position data of the difference portion with the supplier data TD input via the cooperation means 11 and the delete that deletes the portion where the position matches in the comparing section 41. The business unit display unit 43 displays a difference portion that is not erased by the erasing unit 42 as a preliminary business partner candidate SB on the map. The business partner data erased by the erasure unit 42 is accumulated in the business exclusion destination database 7C, and the preliminary business partner SB that is not erased is stored in the database 4A.

  The operation example of the difference portion extraction / position display means 3 and the existing supplier deletion means 4 is as shown in the flowchart of FIG. 6, and the difference portion extraction unit 31 is different from the new house map data 1B and old house map data 1A. A part is extracted (step S101), and difference part data is acquired (step S102). The map display means 2 displays a house map based on the new house map data 1B (step S104), and the color conversion unit 32 performs color classification according to the building type based on the acquired difference data (step S103). The building type is displayed in color on the position display unit 33 (step S104). Further, the acquired difference portion data is compared with the supplier data TD by the comparison unit 41 (step S105), and it is determined whether or not it matches the supplier data TD (step S106). Those that do not match are stored in the database 4A as a preliminary sales destination SB (step S107), and those that match are stored in the database 7C as a business exclusion destination (step S108).

  The preliminary business partner SB is input to the exclusion determination means 7. The contents of the registry and the survey results of the field survey are input to the exclusion determination means 7 via the input means 7A, the exclusion conditions are input from the exclusion condition setting means 7B, and the excluded business partners excluded are stored in the database 7C. The The business candidate FB that has not been excluded is input to the ranking means 8. The ranking unit 8 receives the ranking conditions based on the borrowing amount and the borrowing timing from the condition setting unit 8A, and outputs a list of influential business partners FBR ranked by the ranking unit 8.

  FIG. 7 shows a detailed configuration example of the exclusion determination means 7, a data adding unit 71 for adding the register and field survey data input from the input means 7 A to the preliminary sales destination SB, and an exclusion condition setting means 7 B. Whether to exclude or adopt the condition organizing unit 73 for organizing the exclusion condition inputted more, the comparison unit 72 for comparing the preliminary business customer SBA with data added to the exclusion condition, and the business partner compared by the comparing unit 72 And a distribution unit 74 that determines and distributes the business partners excluded by the distribution unit 74 are stored and accumulated in the database 7C, and the business partner candidates FB that are not excluded are input to the ranking means 8. Is done.

  An example of the operation of the exclusion determination means 7 is as shown in the flowchart of FIG. That is, the preliminary business SB is input (step S141), and then the registry and field survey data are input via the input means 7A (step S142). The data adding unit 71 adds the data to the comparing unit 72. Is compared with the exclusion condition set by the exclusion condition setting means 7B (step S143). If there is an item to be excluded, it is distributed by the distribution unit 74, changed from the preliminary sales destination SB to the business exclusion destination (step S144), and stored in the business exclusion destination database 7C. If there is no item to be excluded, it is sorted by the sorting unit 74 and transmitted to the ranking means 7 as a business candidate FB.

  FIG. 9 shows an example of the detailed configuration of the ranking means 8. The condition organizing section 81 that organizes the ranking conditions set by the condition setting means 8 A and the various conditions organized by the condition organizing section 81. A scoring table setting unit 82 for setting a scoring table, a scoring unit 83 for scoring an input business candidate FB according to the set scoring table, a determining unit 84 for determining a scoring result, and the determined business partner It is comprised with the arrangement | sequence part 85 which ranks and arranges in order of scoring.

  FIG. 10 shows an example of the operation of the ranking means 8. The business candidate FB is input to the scoring unit 83 (step S151), and scoring is performed according to the scoring table as shown in Table 2 (step S152). The total value of the scoring is calculated (step S153), and the determination unit 84 determines “A rank”, “B rank”, etc., and performs ranking (step S154). The array unit 85 creates a list according to the ranking (step S155), outputs it as a leading business partner FBR, and registers it in the database 8B (step S156).

  In such a configuration, an operation example of the entire system will be described with reference to the flowchart of FIG.

  A difference part of change for one year or a plurality of years is obtained from the old house map database 1A and the new house map database 1B of the house map database provided in the general market (step S100). That is, map data is fetched and displayed from the old house map database 1A and the new house map database 1B via the map display means 2, and the difference portion extraction unit 31 acquires the difference portion between the new house map and the old house map. The difference portion is acquired using building attribute information in housing map data, for example, digital map data “Zmap Town II (registered trademark)” of a housing map published by Zenrin. In the digital map data “Zmap Town II (registered trademark)”, the building attribute information is expressed by a combination of 16 alphanumeric characters. Since the building attribute information has a unique identification character (for example, “abcdEFFGhij123456”) for one building, a building having an identification character “not in the old house map but in the new house map” Or it can be regarded as an extended building. That is, the identification character group of the differential building can be acquired by “identification character group included in new house map−identification character group included in old house map”. FIG. 12A shows an example of the identification characters and attribute names of the new house map, and FIG. 12B shows an example of the identification characters and attribute names of the old map, which are shaded in this example. Since “xxxx” does not exist in the old house map, this is the extraction target. That is, “Corporation xxxx” is extracted as a new building. Thus, the map of the difference building can be expressed by attaching the mark of the building having the identification character group of the difference building to the old house map and the new house map. In the present invention, the difference portion is color-converted by the color conversion section 32, and the difference display portion 33 is color-converted and displayed at the corresponding position.

FIG. 13 is a specific house map showing an example of extracting a new building. Zmap Town II (registered trademark) of the residential map on the market has an identification number for the building and the type of building “personal house, office, named building, target”. The building acquired as the difference is colored by changing the color for each type of building. In addition, since the information of the replacement system 10 possessed by the financial institution has real estate location information, it is in a state of being placed on the housing map with a circle symbol at the corresponding location as shown in FIG. Then, after acquiring the difference between the old and new residential maps, the existing business partner erasure unit 4 performs a process of erasing the business partner of the bank in cooperation with the customer database such as the cleaning system 10 (step S110). And the deletion part 42 deletes the bank's own business partner and displays it on the business partner display part 43, and sends the obtained preliminary business partner SB to the exclusion determination means 7 and stores and accumulates it in the database 4A. Since the data of the repayment system 10 is mortgage lending data of the financial institution itself, it is used to exclude the lender of the bank from prospective customers of mortgage refinancing. Input of data from the rejuvenation system 10 via the link means 11 is performed by import processing using a direct database link or an intermediate file in CSV (Comma Separated Value) format. Replacement system information reference function includes automatic batch import replacement data import via intermediate file, "Yen symbol + customer name" prospect customer map display, overview display by symbol click, prospect information display, 10 items It is composed of a search condition specification of a certain degree and a prospect search that is a list display of search results. Elimination of our lending destination can automatically determine whether or not it is a lending destination based on the coordinate information held by the rehabilitation system 10. For properties whose determination result is gray Check visually. In the case of own lenders, it is not necessary to conduct refinancing business, so it will be deleted.

  Next, a survey in the register and a field survey are performed (step S130). Appropriateness confirmation is performed in the exclusion determination means 7 by a survey of the register book or a field survey (step S140), and an exclusion condition or reason is input for an inappropriate property (step S141), and data is stored in the business exclusion destination database 7C. Exclusion conditions are used when the next business candidate is acquired. Examples of exclusion conditions include “unconditionally exclude”, “exclude until year x month”, and “review next time”. In addition, accumulation of business partner exclusions accumulates that are inappropriate for the refinancing business partner at the stage of transition from the business partner candidate to the leading business partner and those that are determined to be unanticipated during the business activity. The accumulated information is used at the time of extracting the next business candidate.

  That is, the contents of the survey in the registry and the survey results of the field survey are input by the input means 7A and added to the preliminary business partner SB, and the preliminary business partner SBA to which the survey result is added is input to the comparison unit 72. The The exclusion condition set by the exclusion condition setting unit 7B is arranged for comparison by the condition organizing unit 73 and input to the comparison unit 72, and based on the result of comparison by the comparison unit 72, the distribution unit 74 determines the exclusion condition. With the reason attached, the excluded business partners are accumulated in the database 7C or sent to the ranking means 8 as business candidate candidates FB.

  When the suitability of the business candidate is confirmed as described above, ranking is performed by the ranking means 8 (step S150), and the ranked leading business FBR is output as a list and registered in the database 8B. To do. Ranking is performed by evaluating the borrowing amount, borrowing timing, evaluation amount, etc. based on the unique know-how of financial institutions. Therefore, the conditions for ranking (borrowing amount, borrowing time, evaluation amount, etc.) are set in the condition setting means 8A, the various conditions are arranged by the condition arranging unit 81, and the scores of the various conditions are obtained by the scoring table setting unit 82. Set as shown in Table 2 above. Then, the scoring unit 83 performs scoring of the business candidate FB according to the scoring table, the score is determined by the determination unit 84, and the array unit 85 has the leading sales as shown in FIGS. 14A to 14C according to the score. In addition to outputting as a previous list, leading business data is accumulated in the database 8B.

  In addition, financial institutions operate an automatic examination system, collateral evaluation system, and the like, and by linking them with these customer databases, maintainability can also be involved. The automatic screening system can rank using the creditworthiness of leading business partners, and the collateral evaluation system can be related to maintainability, such as obtaining a ranking element using a more accurate collateral evaluation amount. The database 8B of potential business partners stores information that is determined to be appropriate for the mortgage refinancing business by the registration book or field survey from the business candidates.

  The salesperson of the financial institution conducts sales activities with reference to the database 8B of the leading business partner (step S160), determines whether or not there is a prospect of refinancing (step S170), and if there is no prospect, The reason is input (step S141), and this is stored in the business exclusion destination database 7C. If there is a prospect, the business is continued and the contract is concluded (step S180). If the contract is concluded, it is registered in the contract destination database 9.

During operation of the present invention, information registered as an exclusion destination in the previous extraction may be referred to at the time of the next extraction, and may be acquired as a business candidate from the exclusion destination according to an exclusion condition. That is, the following processing (1) to (3) is executed with reference to the exclusion destination at the time of difference portion extraction.
(1) Exclude unconditionally At the time of subsequent extraction of the difference portion, no extraction is made as a business partner candidate.
(2) Exclude until specified date Checks the specified period, automatically acquires as a business candidate if the difference date has been extracted, and as a business candidate if the extracted date has not passed Do not extract.
(3) Review next time Unconditionally automatically acquired as a business candidate.

The above process is shown in a flowchart in FIG. 15, and the exclusion conditions (1) to (3) are confirmed (Step S201) when the difference portion is acquired for the second time and thereafter (Step S200). For example, when FIG. 16 (A) is a new house map and FIG. 16 (B) is an old house map, the shaded part is an extraction target that is not in the old house map, and is this extraction target an exclusion condition? Confirm. For example, the exclusion destination information is shown in Table 3 below.

When the exclusion condition is “unconditionally excluded” of the condition (1) (step S202), the difference part acquisition is ended as it is as an exclusion destination (step S208). If the exclusion condition is “exclude until the specified date” in the condition (2) (step S203), the specified period is confirmed (step S205). The partial acquisition ends (step S206). When the specified period has passed (step S207), the partial acquisition is acquired (step S209), and then the difference partial acquisition ends (step S209).

  When the exclusion conditions in Table 3 above exist, it is determined whether or not to be a business partner candidate by executing the following processing. Since the identification character “AAAA0002” “corporation xxxx” is excluded unconditionally, it is not treated as a business candidate and is retained as exclusion information. Also, since the “Maison XX” of the identification character “DDDD0009” is excluded until the designated date, the designated date is confirmed. For example, if the extraction date is September 1, 2008, the due date is October 1, 2008, and the extraction date has not passed the specified period, so it is not treated as a business partner candidate and is retained as exclusion information. If the extraction date is November 1, 2008, the due date is October 1, 2008, and the extraction date has passed the specified period. Therefore, the extraction date is deleted and extracted as a business candidate. On the other hand, “limited company □□” of the identification character “EEEE0001” is deleted from the exclusion destination and extracted as a business candidate for review next time.

DESCRIPTION OF SYMBOLS 1A Old house map database 1B New house map database 2 Map display means 3 Difference part extraction / position display means 31 Difference part extraction part 32 Color conversion part 33 Position display part 4 Existing supplier elimination means 41, 72 Comparison part 42 Erase part 43 Sales destination display unit 4A Preliminary business destination database 7 Exclusion determination means 71 Data addition unit 74 Distribution unit 7A Input means 7B Exclusion condition setting means 7C Sales exclusion destination database 73, 81 Condition organizing unit 8 Ranking means 8A Condition setting means 8B Influential business partner database 82 Scoring table setting unit 83 Scoring unit 84 Judgment unit 85 Arrangement unit 9 Contracting destination database 10 Replacement system (external database)
11 Cooperation means

Claims (4)

Computer
Extracting the difference part of the old house map data and the new house map data over time, calculating the position of the prospective customer and linking with the external database owned by the financial institution, and the existing business partner of the financial institution from the difference part Eliminate and find a preliminary business partner, determine the exclusion of the preliminary business partner based on the entered registry, registry data, and field survey results to obtain a candidate for the business partner. A mortgage refinancing business support method, characterized by ranking prior candidates and displaying a list. The computer is
The mortgage refinancing business support method according to claim 1, wherein the business exclusion destination information determined not to be closed by the exclusion determination is reused. A difference part extraction / position display means for extracting different difference data of the new house map data and the old house map data, and displaying the address position on the registry data of the difference part data;
Cooperation means that cooperates with external databases that utilize and operate supplier data,
Existing supplier erasure means for erasing an existing supplier obtained from the external database based on the external data captured by the cooperation means from the difference data and obtaining a preliminary business partner;
An input means for inputting the register, the register data and the survey content of the field survey;
Exclusion judgment means for judging exclusion of the preliminary business partner based on the data input by the input means and selecting a business partner candidate;
Ranking means for ranking leading business candidates that are not excluded by the exclusion determination means to obtain leading business partners;
Housing loan refinancing business support system characterized by comprising The mortgage refinancing business support system according to claim 3, further comprising continuous exclusion information reuse means for reusing business exclusion destination information determined not to be closed by the exclusion determination.