TWM577559U - Evaluation system for unsecured relocation loan amount - Google Patents

Abstract

In an unsecured household loan amount evaluation system, the processing unit selects a target parameter that conforms to the target customer's financial transaction behavior type from the plurality of parameter groups included in the risk tolerance parameter table according to the target customer's customer data and historical transaction data. Group and estimate the first loan amount in line with the current regulations; estimate the second loan amount related to the total amount control according to customer data, target parameter group and historical transaction data; according to customer data, target parameter group, corresponding to target customer The predetermined reference coefficient of the unsecured target credit product to be purchased and the unsecured credit transaction balance coefficient estimate the third loan amount related to the flow control; and the smallest one selected from the first to third loan amounts as the target The optimal loan amount for credit products.

Description

Unsecured household loan amount assessment system

The new model is an assessment of the amount of unsecured household loans, in particular a system for assessing the amount of unsecured household loans.

Existing banking institutions, for example, the assessment mechanism for unsecured loan quotas, can generally assess the amount of credit given to customers based on the product characteristics of the financial products they apply for and the risk-taking capabilities of the customers themselves. However, if the customer's own risk tolerance cannot be effectively assessed or mastered, this assessment mechanism is likely to cause improper credit expansion for the customer.

Therefore, there is still much room for improvement in the assessment mechanism for unsecured loan quotas used by existing banking institutions.

Accordingly, it is an object of the present invention to provide an unsecured home loan credit rating system that overcomes at least one of the disadvantages of the prior art.

Therefore, the novel unsecured home loan amount assessment system is used to evaluate an optimal loan amount of a non-guaranteed target credit product to be purchased by a target customer, and includes a storage unit, a communication module and a processing unit. . The storage unit stores a risk tolerance parameter table related to a plurality of different financial transaction behavior types, a plurality of different credit risk levels, and a plurality of different repayment capability levels. The risk tolerance parameter table includes a plurality of parameter groups, wherein each parameter group is related to one of the financial transaction behavior types, one of the credit risk levels, and one of the different repayment capability levels. Corresponding, and including at least a first parameter value related to the highest risk amount, a second parameter value representing an unutilized default risk rate of the cyclic product, and a ratio representing the total annual debt expenditure to the annual income The third parameter value. The communication module is connected to a data server provided by a data providing provider via a communication network. The processing unit is electrically connected to the storage unit and the communication module.

When the processing unit obtains customer data related to the target customer and contains at least the target customer's annual income or monthly average income, and personal identification data, the processing unit transmits a data related to the target customer via the communication module. Requesting to the data server, so that the data server transmits a no-data notification to the communication module via the communication network in response to the data request when it is determined that the target customer has not performed any historical credit transaction. When it is determined that there is a historical credit transaction between the target customer and one or more different banking institutions, in response to the data request, transmitting, via the communication network, all the information related to the target customer and the banking institution The historical transaction data of the historical credit transaction is replied to the communication module, and the historical transaction data, for each historical credit transaction, contains the corresponding transaction type, the corresponding transaction amount and the corresponding repayment record, and each historical credit transaction It is one of a mortgage transaction, a secured loan transaction, and an unsecured credit transaction.

The processing unit finds a match from the risk tolerance parameter table stored in the storage unit according to the customer data or according to the customer data and the historical transaction data included in the data from the data server. The type of financial transaction behavior, credit risk level and repayment ability level to which the target customer belongs is used as a parameter group of the target parameter group.

The processing unit estimates the first loan amount in accordance with the current regulations and related to the average monthly income based on the customer data or based on the customer data and the historical transaction data.

The processing unit estimates the total amount of control related to the target customer according to the customer data and the first parameter value of the target parameter group, or according to the customer data, the historical transaction data, and the target parameter group, and corresponds to The second loan amount of the unsecured target credit product.

The processing unit is based on the customer profile, the product profile, the target parameter set, and a predetermined reference coefficient corresponding to the product type of the unsecured target credit product, or according to the customer profile, the product profile, the target parameter set, the a predetermined reference coefficient, the historical transaction data, and one or more coefficient sets respectively corresponding to the all historical credit transactions, estimating a third loan amount related to the flow control of the target customer and corresponding to the unsecured target credit product . Each coefficient group contains one or two coefficients associated with the corresponding historical credit transaction.

The processing unit selects a minimum one of the first loan amount, the second loan amount, and the third loan amount as the optimized loan amount.

The effect of the new model is that the unsecured household loan quota assessment mechanism established through the concept of the household and the overall financial liabilities of the customer can optimally and completely assess the risk situation that the customer can bear, and not only in accordance with current regulations, It can effectively avoid improper credit expansion of customers.

Before the present invention is described in detail, it should be noted that in the following description, similar elements are denoted by the same reference numerals.

Referring to FIG. 1, an embodiment of the present invention for an unsecured household loan amount assessment system 100 is for evaluating an optimized loan amount for an unsecured target credit product to be purchased by a target customer, and may include a storage unit 1. A user input/output unit 2, a communication module 3, and a processing unit 4 electrically connected to the storage unit 1, the user input/output unit 2, and the communication module are not limited thereto. It should be noted that the unsecured home loan amount assessment system 100 can be implemented as an evaluation server provided by a particular banking institution or as an evaluation server provided by other service agencies independent of the banking institution. In this embodiment, the unsecured target credit product may be a periodic credit product, such as credit card credit card installment payment, personal credit loan, etc., or a recurring credit card product, such as credit card payment.

The storage unit 1 pre-stores a type of behavior related to a plurality of different financial transactions (for example, there is a capital requirement and there is a mortgage, there is a capital requirement but no mortgage, there is potential capital demand, no potential capital demand, etc., but not limited to this example ), a number of different credit risk levels and a number of different repayment ability levels of risk tolerance parameters Table 11. In this embodiment, the risk tolerance parameter table 11 may include a plurality of parameter groups, wherein each parameter group is related to one of the financial transaction behavior types, one of the credit risk levels, and the corresponding one. And one of the different repayment ability levels, and at least one first parameter value related to the highest risk amount, one second parameter value representing the unutilized default risk rate of the cyclic product, and one representing the total year The third parameter value of the ratio of debt expenditure to annual income, but not limited to this. It is worth noting that the risk tolerance parameter table 11 is developed under the consideration of three dimensions, one of which can be applied to the customer's products in the overall banking institution (such as all banking institutions in Taiwan). The category adds the total amount of the total risk of the credits of all the credit products of the same customer to all the banking institutions; dimension 2 can be applied to the basic information according to the customer and the transactions of the customers in all banking institutions (for example, the closeness of the transaction, the payment situation, etc.), comprehensive judgment Customer credit status and score (ie, credit score) to distinguish or identify the customer's credit risk level; and dimension 3 can be applied to the income documents (such as payroll, withholding voucher, etc.) and/or attached to the customer Or financial documents (such as current assets documents, deposit certificates, live balances, etc.) to distinguish or identify their repayment ability level, but not limited to this.

The communication module 3 is connected to a data server 300 via a communication network 200. In the present embodiment, the material server 300 may be provided by, for example, a data providing institution of a government association, but not limited thereto, and used to provide relevant information of all historical financial transactions of individuals.

In this embodiment, in use, the user can use a user terminal 400 (eg, a computer device, but not limited to) connected to the communication network 200 to include a customer profile related to the target customer, and related An evaluation request for product information of the unsecured target credit product is transmitted to the communication module 3. However, in other embodiments, the user can manually operate the user input/output unit 2 to cause the user input and output unit 2 to generate the customer information and the product information, and the customer information and the product. The data is output to the processing unit 4 together. It is worth noting that the customer information may include, for example, the residential address, annual income or monthly average income of the target customer, and personal identification data, and the like, and the product information indicates, for example, at least the unsecured target credit product. The product type and other related materials.

The following is a description of how the processing unit 4 performs an unsecured homing when the processing unit 4 receives the evaluation request from the user terminal 400 via the communication module 3 in the present embodiment with reference to FIG. 1 and FIG. Loan credit assessment process. The unsecured household loan amount evaluation includes the following steps S21 to S27.

First, in step S21, the processing unit 4 transmits a data request related to the target client and containing the personal identification data to the data server 300 via the communication module 3.

Therefore, after receiving the data request from the unsecured home loan amount evaluation system 100 and determining that the target customer has not executed any historical credit transaction, the data server 300 responds to the data request via the data request. The communication network 200 transmits a no-data notification to the communication module 3, and when it is determined that there is a historical credit transaction between the target customer and one or more different banking institutions, the communication network 200 is responded to by the data request. Transmitting a message containing historical transaction data relating to all historical credit transactions between the target customer and the banking institution to the communication module 3. It is worth noting that the historical transaction data, for each historical credit transaction, contains the corresponding transaction type, the corresponding transaction amount and the corresponding repayment record, and each historical credit transaction may be, for example, a mortgage transaction, One of the secured loan transactions and one unsecured credit transaction, but not limited to this.

Then, in step S22, the processing unit 4 receives the no-data notification or the data reply from the data server 300 via the communication module 3.

Then, in step S23, the processing unit 4, according to the customer data, or according to the customer data and the historical transaction data included in the data reply, finds from the risk tolerance parameter table that one belongs to the target customer. The financial transaction behavior type, credit risk level and repayment ability level are used as parameter groups of the target parameter group. More specifically, when the processing unit receives the no-data notification in step S22, since the target customer does not have any historical credit record, the processing unit 4 can only find the target parameter group according to the customer profile, and When the processing unit receives the data reply in step S22, the processing unit 4 searches for the target parameter group according to the customer data and the historical transaction data.

Next, in step S24, the processing unit 4 estimates, according to the customer profile, or based on the customer profile and the historical transaction profile, a first loan amount that is consistent with the current regulations and related to the average monthly income of the target customer. More specifically, when the processing unit 4 (in receiving the notification of non-trading case) only when the first loan amount estimated in accordance with the customer data, the first amount of the loan obtained by the following formula 1: The first a loan amount = the average monthly income 'one of the current regulations specification predefined integer multiple ... (type 1) and when the processing unit 4 (in the case of receiving the information reply) based on the customer data and the historical trading when the first data to estimate the amount of the loan, the loan amount first obtained by the following formula 2: the first loan amount = (the average monthly income of 'the predetermined integer multiple) - All transactions in which the credit history of all unsecured credit transactions Total balance ................................................ (Formula 2) For example, the predetermined integer multiple specified in the current regulations is, for example, 22 times, but Not limited to this example.

Then, in step S25, the processing unit 4 estimates the relevant target customer according to the customer data and the first parameter value of the target parameter group, or according to the customer data, the historical transaction data, and the target parameter group. The total amount of control and corresponds to the second loan amount of the unsecured target credit product. More specifically, if the product information indicates that the unsecured target credit product is a periodic credit product, when the processing unit 4 (when receiving the no-transaction notification), according to the customer information, the product information and when the first parameter value of the target parameter set to the second estimate of the amount of the loan, the loan amount to the second obtained by the following formula 3: the first parameter of the second amount of the loan = the average monthly income 'of the target parameter set Value ..... (Formula 3) and when the processing unit 4 (in the case of receiving the data reply), the second loan amount is estimated based on the customer data, the product data, the historical transaction data, and the target parameter group when the second loan amount obtained by the following formula 4: the second loan amount = (the first parameter value of the average monthly income 'of the target parameter set) - the total balance of all unsecured credit transactions - (All the unsecured credit transactions of cyclic unutilized overall balance 'the second parameter value of the target parameter set) ............................................. .. (formula 4) On the other hand, if the The product information indicates the unsecured item The credit product is a revolving credit card product of a cyclic type of product, when the processing unit 4 (when receiving the no transaction notification), according to the customer profile, the product profile, and the first of the target parameter set when the estimated value of the second parameter loan amount, the second amount of the loan is obtained by the following formula 5: the second loan amount = (the first parameter value of the average monthly income 'of the target parameter set) ¸ the target parameter set The second parameter value is .......................................... (Formula 5) and when the processing unit 4 is based on the customer data, the product information, the historical transaction data, and the when the target parameter set to the second estimate of the amount of the loan, the loan amount to the second 6 by the following formula is obtained: the second loan amount = [(the first parameter value of the average monthly income 'of the target parameter set) - all this total unsecured credit balance transactions - (all the unsecured credit transactions of recycling the second parameter value is the total balance 'of the target parameter set unspent)] ¸ the second parameter value of the target parameter set ......... ..... (Formula 6)

Then, in step S26, the processing unit 4 is based on the customer data, the product data, the target parameter set, and a predetermined reference coefficient corresponding to the product type of the unsecured target credit product, or according to the customer data, the product Data, the target parameter set, the predetermined reference coefficient, the historical transaction data, and one or more coefficient sets respectively corresponding to the all historical credit transactions, estimating flow control related to the target customer and corresponding to the unsecured The third loan amount of the target credit product. It is worth noting that each coefficient group contains one or two coefficients associated with the corresponding historical credit transaction. More specifically, when all historical credit transactions exist as periodic credit products, the corresponding coefficient group contains two coefficients and the coefficients are a balance coefficient and a contract amount coefficient, respectively, and when all historical credits When one of the transactions belongs to a revolving credit product, the corresponding coefficient group contains only one coefficient and the coefficient is a balance coefficient. Therefore, if the product information indicates that the unsecured target credit product is a periodic credit product, the predetermined reference coefficient is a contract amount coefficient, and when the processing unit 4 is based on the customer data, the product data, the target when the predetermined reference parameter set and the third coefficient estimated loan amount, the loan amount third is obtained by the following formula 7: the third loan amount = (the value of the third parameter income 'of the target parameter set) ¸ The predetermined reference coefficient ............................................................ (Formula 7) and when the processing unit 4 is based on the customer profile, the product profile, the target parameter set, when the predetermined reference coefficient, the history and the transaction data (such as) sets of coefficients, the third loan amount can be obtained by the following formula 8: the third of the loan amount = [(annual income of the 'group of the target parameter the third parameter value) - (S history of all credit transactions wherein the coefficients a balance of each amount of contracting or 'coefficients contained in the corresponding group)] ¸ the predetermined reference coefficients .............................. ................................. . . . (Formula 8) On the other hand, if the product information indicates that the unsecured target credit product is a revolving credit card product, the predetermined reference coefficient is a balance coefficient, and when the processing unit 4 is based on the customer profile, when the product information, the target group and the predetermined reference parameter coefficient estimate of the third loan amount, the third loan amount can be obtained by the following formula 9: the third of the loan amount = (the annual income 'of the target parameter set a third parameter value ) ̧ the predetermined reference coefficient 该 the second parameter value of the target parameter group .................................... (Formula 9) and when the processing unit 4 is based on the customer profile And the product data, the target parameter group, the predetermined reference coefficient, the historical transaction data, and the (equal) balance coefficient, when the third loan amount is estimated, the third loan amount may be obtained by the following formula 10: the third loan amount = [( 'the third parameter value of the target parameter set - (S transactions where the credit balance of all the history of each of the amount of annual revenue or contracting)' corresponding to a coefficient of the coefficient group contained)] ¸ the predetermined reference coefficients ¸ The second parameter value of the target parameter set .............................. .. (Formula 10)

Finally, in step S27, the processing unit 4 selects a minimum one of the first loan amount, the second loan amount, and the third loan amount as the optimized loan amount.

At this point, the unsecured household loan amount assessment procedure was completed. However, in this embodiment, the processing unit 4 may further transmit, in response to the evaluation request, an evaluation result indicating the optimized loan amount to the use terminal 400 via the communication module 3 for the use. End 400 displays the optimized loan amount indicated by the evaluation result. In other embodiments, however, the processing unit 4 may also cause the user input and output unit 2 to display the optimized loan amount.

Hereinafter, the optimized loan amount obtained by the processing unit 4 executing the steps S23-S27 in the above-mentioned unsecured home loan amount evaluation program will be further exemplified in four different example cases.

Example 1: The annual income/average monthly income of the customer data is, for example, about 600,000 yuan / 50,000 yuan. The target customer has not executed any historical credit transaction, and the product information indicates that the unsecured target credit product is A regular credit product. In this case, the first to third parameter values included in the target parameter group selected by the processing unit 4 in step S23 are, for example, 20, 40%, and 70%, respectively; the predetermined integer multiple is, for example, 22 times. The first loan amount obtained by the processing unit using the above formula 1 in step S24 is about 1.1 million yuan (=50,000 yuan ́22); the processing unit 4 uses the second loan amount obtained by the above formula 3 in step S25. Approximately 1 million yuan (= 50,000 yuan ́20); the predetermined reference coefficient is a contract amount coefficient and is, for example, 18%, and the processing unit 4 uses the third loan amount obtained by using the above formula 7 in step S26. It is 2.333 million yuan (≈600,000 ́70% ̧18%); and the optimization loan amount obtained by the processing unit 4 in step S27 is about 1 million yuan (that is, the second loan amount).

Example 2: The annual income/average monthly income of the customer data is, for example, about 600,000 yuan / 50,000 yuan. The historical transaction data indicates that the target customer and the bank have executed a regular type of credit that is a regular product. The contracted amount and (loan) balance of the transaction are, for example, $500,000 and $200,000 respectively, and the credit card amount and (arrears) of the revolving credit card transaction of the revolving credit card product executed by the target customer and Bank B. The balances are, for example, $150,000 and $50,000 respectively, and the product information indicates that the unsecured target credit product is a regular credit product. In this case, the first to third parameter values included in the target parameter group selected by the processing unit 4 in step S23 are, for example, 20, 40%, and 70%, respectively; the predetermined integer multiple is, for example, 22 times. The first loan amount obtained by the processing unit 4 using the above formula 2 in step S24 is about 850,000 yuan (=50,000 yuan ́22-20 million yuan -50,000 yuan); the processing unit 4 uses the above formula in step S25. The second loan amount obtained by 4 is about 710,000 yuan (=[(50,000 yuan ́20)-200,000 yuan -50,000 yuan]-(150,000 yuan -50,000 yuan) ́40%); The reference coefficient is a contracted amount coefficient and is, for example, 18%. The coefficient coefficient and the contracted amount coefficient of the coefficient group corresponding to the term credit transaction of Bank A are, for example, 40% and 18%, respectively, and correspond to Bank B. The coefficient coefficient included in the coefficient group of the recurring credit card transaction is, for example, 69%. Specifically, in step S26, the processing unit 4 first calculates two amounts related to the term credit transaction of the bank A, that is, , the first amount (= balance ́ balance coefficient = 200,000 yuan ́40% = 80,000 yuan), and the second amount (= contracted amount ́ contracted amount coefficient = 500,000 yuan ́18 %=90,000 yuan), and select one of the first and second amounts (ie, the first amount), and calculate a third amount (= balance) related to the revolving credit card transaction of Bank B ́ balance coefficient = 50,000 yuan ́69%), and then the third and third amount of the third loan amount obtained after the above formula 8 is about 1.697 million yuan (≈{(600,000 ́70%) -[(200,000 ́40%)+(50,000 ́69%)]} ̧18%); and the optimization loan amount obtained by the processing unit 4 in step S27 is about 710,000 yuan (ie, The second loan amount).

Example 3: The annual income/average monthly income included in the customer data is, for example, about 600,000 yuan / 50,000 yuan. The target customer has not executed any historical credit transaction, and the product information indicates the unsecured target credit product. In the case of a revolving credit card product, the first to third parameter values included in the target parameter set selected by the processing unit 4 in step S23 are, for example, 20, 40%, and 70%, respectively; 22 times, the first loan amount obtained by the processing unit 4 using the above formula 1 in step S24 is about 1.1 million yuan (=50,000 yuan ́22); the second obtained by using the above formula 5 in step S25 The loan amount is about 2.5 million yuan (= (50,000 yuan ́20) ̧ 40%); the predetermined reference coefficient is a balance coefficient and is, for example, 69%, and the processing unit 4 obtains the method obtained by the above formula 9 in step S26. The third loan amount is about 1.522 million yuan (≈ (600,000 ́70%) ̧ 69% ̧ 40%); and the optimal loan amount obtained by the processing unit 4 in step S27 is about 1.1 million yuan (ie , the first loan amount).

Example 4: Similar to the above example 2, the annual income/average monthly income of the customer data is, for example, about 600,000 yuan / 50,000 yuan. The historical transaction data indicates that the target customer and the bank have executed one periodically. The contracted amount and (loan) balance of the regular type credit transaction of the type products are, for example, 500,000 yuan and 200,000 yuan respectively, and the credit card transaction of the revolving credit card transaction executed by the target customer and the bank B, which belongs to the revolving credit card product. The balance of the quota and (arrears) are, for example, $150,000 and $50,000 respectively, but the product information indicates that the unsecured target credit product is a revolving credit card product. In this case, the first to third parameter values included in the target parameter group selected by the processing unit 4 in step S23 are, for example, 20, 40%, and 70%, respectively; the predetermined integer multiple is, for example, 22 times. The first loan amount obtained by the processing unit 4 using the above formula 2 in step S24 is about 850,000 yuan (=50,000 yuan ́22-20 million yuan -50,000 yuan); the processing unit 4 uses the above formula in step S25. The second loan amount obtained by 6 is about 1.775 million yuan (={[(50,000 yuan ́20)-20 million yuan -50,000 yuan]-(150,000 yuan -50,000 yuan) ́40%)} ̧ 40%); the predetermined reference coefficient is a balance coefficient and is, for example, 69%, and similar to the above example 2, the processing unit 4 substitutes the first calculated first and the third amount into the formula 10 in step S26. The amount of the third loan obtained was about 1.107 million yuan (≈{(600,000 ́70%)-[(200,000 ́40%)+(50,000 yuan ́69%)] ̧69% ̧40% And the optimization loan amount obtained by the processing unit 4 in step S27 is about 850,000 yuan (that is, the first loan amount).

In summary, the unsecured household loan credit assessment system implemented by the new unsecured household loan credit assessment system 100 is established through the concept of the household and the overall financial of the client (all banks that have traded with it). The unsecured household loan assessment mechanism can optimally and fully assess the risk conditions that customers can afford, and not only can comply with current regulations, but also effectively avoid improper credit expansion of customers. Therefore, the purpose of this novel can be achieved.

However, the above is only the embodiment of the present invention, and when it is not possible to limit the scope of the present invention, all the simple equivalent changes and modifications according to the scope of the patent application and the contents of the patent specification are still This new patent covers the scope.

100‧‧‧Unsecured household loan amount assessment system

1‧‧‧ storage module

11‧‧‧ Risk Tolerance Parameter Table

2‧‧‧User input and output unit

3‧‧‧Communication module

4‧‧‧Processing unit

200‧‧‧Communication network

300‧‧‧Data Server

400‧‧‧Use side

S21~S27‧‧‧Steps

Other features and effects of the present invention will be apparent from the following description of the drawings, wherein: FIG. 1 is a block diagram exemplarily illustrating an embodiment of the novel unsecured home loan credit rating system. And a usage end and a data server; and FIG. 2 is a flow chart exemplarily illustrating how a processing unit of the embodiment performs an unsecured home loan amount evaluation procedure when obtaining a target customer's customer profile.

Claims (8)

An unsecured household loan amount assessment system for evaluating an optimal loan amount for an unsecured target credit product to be purchased by a target customer, the unsecured household loan amount evaluation system comprising: a storage unit, storing a correlation a risk tolerance parameter table for a plurality of different financial transaction behavior types, a plurality of different credit risk levels, and a plurality of different repayment capability levels, the risk tolerance parameter table including a plurality of parameter groups, wherein each parameter group is related to One of the financial transaction behavior types, one of the credit risk levels, and one of the different repayment capability levels, and at least one first parameter value related to the highest risk amount, a second parameter value representing an unutilized default risk rate of the cyclic product, and a third parameter value representing a ratio of the total annual debt expenditure to the annual income; a communication module connecting a data via a communication network Providing a data server provided by the organization; and a processing unit electrically connecting the storage unit and the communication module; wherein, when The processing unit obtains the customer information related to the target customer and contains at least the target customer's annual income or monthly average income, and personal identification data, and the product information related to the unsecured target credit product, the processing unit via the communication Transmitting, by the module, a data request related to the target client to the data server, so that the data server transmits the data request via the communication network in response to the data request when determining that the target client has not performed any historical credit transaction Notifying the communication module when there is no information, and transmitting a content related to the target via the communication network in response to the data request when it is determined that there is a historical credit transaction between the target customer and one or more different banking institutions The historical transaction data of all historical credit transactions between the customer and the (and other) banking institutions is returned to the communication module, and the historical transaction data, for each historical credit transaction, contains the corresponding transaction type, the corresponding transaction amount and Corresponding repayment history, each historical credit transaction is a mortgage transaction, a guarantee And one of the unsecured credit transactions; wherein the processing unit responds to the historical transaction contained in the data according to the customer data or the customer information and the data from the data server Data, the risk tolerance parameter table stored in the storage unit is used to find a parameter group that meets the financial transaction behavior type, the credit risk level, and the repayment capability level of the target customer and is a target parameter group; The processing unit estimates, according to the customer data, or based on the customer data and the historical transaction data, a first loan amount that is in compliance with current regulations and related to the average monthly income; wherein the processing unit is based on the customer data, the product information, And the first parameter value of the target parameter group, or based on the customer data, the product data, the historical transaction data, and the target parameter group, estimating the total amount of control related to the target customer and corresponding to the unsecured a second loan amount of the target credit product; wherein the processing unit is based on the customer information, the product capital a target parameter set and a predetermined reference coefficient corresponding to the product type of the unsecured target credit product, or based on the customer data, the product data, the target parameter set, the predetermined reference coefficient, the historical transaction data, and one or a plurality of coefficient groups respectively corresponding to the all historical credit transactions, estimating a third loan amount corresponding to the flow control of the target customer and corresponding to the unsecured target credit product, wherein each coefficient group contains one or two a coefficient related to the corresponding historical credit transaction; and wherein the processing unit selects a minimum from the first loan amount, the second loan amount, and the third loan amount as the optimized loan amount. The unsecured home loan amount evaluation system according to claim 1, wherein when the processing unit estimates the first loan amount based only on the customer data, the first loan amount is one of the average monthly income. a predetermined integral multiple of the current regulation, and when the processing unit estimates the first loan amount based on the customer data and the historical transaction data, the first loan amount = (the average monthly income ́ the predetermined integer multiple) - The total balance of all unsecured credit transactions in all historical credit transactions. The unsecured household loan amount assessment system of claim 2, wherein: the product information indicates that the unsecured target credit product is a periodic credit product; and when the processing unit is based on the customer information, the product information, and When the first parameter value of the target parameter group estimates the second loan amount, the second loan amount=the average monthly income ́ the first parameter value of the target parameter group; and when the processing unit is based on the customer data The product data, the historical transaction data, and the target parameter group estimate the second loan amount, the second loan amount = (the average monthly income ́ the first parameter value of the target parameter group) - the all none The total balance of the secured credit transaction - (the total unbalanced total balance in all unsecured credit transactions ́ the second parameter value of the target parameter group). The unsecured home loan amount evaluation system according to claim 3, wherein: the predetermined reference coefficient is a contract amount coefficient; when the processing unit is based on the customer data, the product data, the target parameter group, and the predetermined reference When the coefficient estimates the third loan amount, the third loan amount = (the third year value of the target income parameter of the annual income ́) ̧ the contract amount coefficient; and when the processing unit is based on the customer data, the product The third loan amount = [(the annual income ́ the third parameter value of the target parameter group) when the data, the target parameter set, the predetermined reference coefficient, the historical transaction data, and the (equal) balance coefficient - ( S. A balance of each of the historical credit transactions or a coefficient included in the coefficient group corresponding to the contract amount ́) ̧ the predetermined reference coefficient. The unsecured household loan amount evaluation system according to claim 2, wherein: the product information indicates that the unsecured target credit product is a revolving credit card product of a cyclic type product type; When the customer data, the product data, and the first parameter value of the target parameter group estimate the second loan amount, the second loan amount = (the average monthly income ́ the first parameter value of the target parameter group) ̧ The second parameter value of the target parameter group; and when the processing unit estimates the second loan amount according to the customer data, the product data, the historical transaction data, and the target parameter group, the second loan amount=[ (the average income of the month ́ the first parameter value of the target parameter group) - the total balance of all unsecured credit transactions - (the total unbalanced total balance in all unsecured credit transactions ́ the target parameter group The second parameter value)] 该 the second parameter value of the target parameter group. The unsecured home loan amount evaluation system according to claim 5, wherein: the predetermined reference coefficient is a balance coefficient; and when the processing unit estimates the customer data, the product data, the target parameter group, and the predetermined reference coefficient When the third loan amount is obtained, the third loan amount = (the third year value of the target income group of the annual income ́) 余额 the balance coefficient 该 the second parameter value of the target parameter group; and when the processing The unit estimates the third loan amount according to the customer data, the product data, the target parameter group, the predetermined reference coefficient, the historical transaction data, and the (equivalent) balance coefficient, and the third loan amount=[( Income ́ the third parameter value of the target parameter group) - (S a balance of each of the historical credit transactions or a coefficient group corresponding to the contract amount ́)] ̧ the predetermined reference coefficient ̧ The second parameter value of the target parameter group. The unsecured home loan amount evaluation system according to claim 1, wherein: the processing unit receives, via the communication module, a user terminal connected to the communication module via the communication network and includes the customer profile and the The evaluation request of the product information; and the processing unit, in response to the evaluation request, transmits an evaluation result indicating the optimized loan amount to the use terminal via the communication module. The unsecured home loan amount evaluation system of claim 1, further comprising a user input and output unit electrically connected to the processing unit, wherein the user input and output unit generates the customer data and the product data through a human operation, and The customer data and the product data are output to the processing unit, wherein the processing unit further causes the user input and output unit to output the optimized loan amount.