System for providing simulated loan interest rate recommendations for assisting credit evaluation and method thereof

Abstract

A system and method for providing a suggested loan application interest rate to assist in credit approval are disclosed. The credit interest rate assessment server performs statistical analysis based on the creditor's transaction history to obtain creditor loyalty indicators, risk assessment indicators, creditor revenue contribution indicators, and profitability indicators. It also analyzes the revenue ratio of credit application identification information to the creditor's industry category, uses an industry trend prediction model corresponding to the creditor's industry category to predict the future loan application period, generating an industry prospect indicator. Furthermore, it determines the correlation between the loan purpose and the predicted industry trend to generate a correlation indicator. The system then adds the risk-weighted interest rate to the sum of the above indicators to calculate a suggested loan application interest rate, which is then displayed on the credit approval device. This achieves the technical effect of providing a suggested loan application interest rate to assist in credit approval.

Claims

1. A system for providing a loan application interest rate suggestion to assist in credit approval, the system comprising: a credit approval terminal device, which, when one of multiple credit application identification information in a credit application approval page is selected for approval, provides the selected credit application identification information, receives credit application information and a loan application interest rate suggestion corresponding to the selected credit application identification information, and displays them on the credit application approval page; and a credit interest rate assessment server, the credit interest rate assessment server further comprising: a credit application information database, storing the credit application identification information and the credit application information, the credit application information including a credit account identification information, a credit account industry, a credit limit, an account type, a loan application purpose, and a loan application term; and a transmission module, which receives the credit application identification information from the credit approval terminal device and provides the credit application information and the loan application interest rate suggestion corresponding to the selected credit application identification information to the credit approval terminal device; A query module retrieves the credit application information corresponding to the credit application identification information from the credit application information database, and then retrieves the corresponding credit account transaction history from a bank data server based on the credit account identification information in the credit application information; an external data module obtains a key economic and financial indicator from a key economic and financial indicator server when it receives the credit application identification information from the credit review terminal device; a credit account transaction analysis module performs statistical analysis based on the retrieved credit account transaction history to obtain a credit account loyalty indicator, a risk assessment indicator, a credit account revenue contribution indicator, and a profitability indicator, and analyzes the revenue ratio indicator of the credit application identification information to the credit account's industry category. A credit applicant industry analysis module uses an industry trend prediction model corresponding to the credit applicant's industry to predict the industry trend for the future loan application period, generating an industry prospect index, and determines the correlation between the loan application purpose and the predicted industry trend to generate a correlation index; and a loan application interest rate calculation module calculates a risk-weighted interest rate by summing the credit applicant's industry, loan application period, account type, credit applicant loyalty index, risk assessment index, credit applicant revenue contribution index, profitability index, revenue ratio index, major economic and financial indicators, industry prospect index, and correlation index, and adds the indicator interest rate to calculate the loan application interest rate recommendation information.

2. The system that provides a suggested loan application interest rate to assist in credit approval as described in Request 1, wherein the industry analysis module for credit applicants uses an industry trend prediction model to determine the correlation between the purpose of the loan application and the predicted industry trend to generate the correlation index, and the industry trend prediction model further includes the use of natural language processing to determine the correlation between the purpose of the loan application and the predicted industry trend.

3. The system that provides a trial loan interest rate suggestion to assist in credit approval as described in Request 1, wherein the industry analysis module for the credit applicant further includes importing external industry trend data and using the industry trend prediction model corresponding to the industry of the credit applicant to predict the industry trend of the future loan application period of the industry and generate the industry prospect index.

4. The system that provides a suggested loan application interest rate to assist in credit approval as described in Request 1, wherein the credit account transaction analysis module further includes importing external business data to analyze the revenue ratio of the credit application identification information to the industry category of the credit account in conjunction with the queried credit account transaction history.

5. The system for providing a trial loan interest rate suggestion to assist in credit approval as described in Request 1, wherein the credit interest rate assessment server further includes an approval suggestion module, which calculates a net benefit of the credit application information based on the credit limit, the loan interest rate suggestion information, an industry risk weight, a capital adequacy ratio, a capital cost ratio, and a funding cost ratio, generates an approval suggestion information based on the net benefit, and then provides the approval suggestion information to the credit approval terminal device through the transmission module for display on the credit application approval page.

6. A method for providing a suggested loan application interest rate to assist in credit approval, comprising the following steps: A credit interest rate assessment server stores the credit application identification information and the credit application information, wherein the credit application information includes a credit account identification information, a credit account industry, a credit limit, an account type, a loan application purpose, and a loan term; When one of multiple credit application identification information on a credit application approval page is selected for approval, a credit approval terminal device provides the selected credit application identification information to the credit interest rate assessment server; The credit interest rate assessment server queries the credit application information database to retrieve the credit application information corresponding to the credit application identification information, and then queries a corresponding credit account transaction history from a bank data server based on the credit account identification information in the credit application information; When the credit interest rate assessment server receives the credit application identification information from the credit approval terminal device, the credit interest rate assessment server obtains a major economic and financial indicator from a major economic and financial indicator server. The credit interest rate assessment server performs statistical analysis based on the queried transaction history of the credit account to obtain a credit account loyalty index, a risk assessment index, a credit account revenue contribution index, and a profitability index. It also analyzes the revenue ratio of the credit application identification information to the credit account's industry category. The credit interest rate assessment server uses an industry trend prediction model corresponding to the credit account's industry category to predict the future loan application period for the credit account's industry, generating an industry prospect index. Furthermore, it determines the correlation between the loan application purpose and the predicted industry trend, generating a correlation index. The credit interest rate assessment server calculates a risk-weighted interest rate by summing the following factors: the industry of the credit applicant, the loan term, the account type, the credit applicant loyalty index, the risk assessment index, the credit applicant's revenue contribution index, the profitability index, the revenue ratio index, the main economic and financial indicators, the industry prospect index, and the relevance index. The risk-weighted interest rate is then added to an indicator interest rate to calculate the loan application interest rate recommendation. The credit interest rate assessment server provides the credit application information corresponding to the selected credit application identification information, along with the loan application interest rate recommendation, to the credit approval terminal device and displays it on the credit application approval page.

7. The method for providing a suggested loan application interest rate to assist in credit approval as described in Request 6, wherein the credit interest rate assessment server uses an industry trend prediction model to determine the correlation between the purpose of the loan application and the predicted industry trend to generate the correlation index, and the industry trend prediction model further includes using natural language processing to determine the correlation between the purpose of the loan application and the predicted industry trend.

8. The method for providing a trial loan application interest rate suggestion to assist in credit approval as described in Request 6, wherein the credit interest rate assessment server uses the industry trend prediction model corresponding to the industry of the credit applicant to predict the industry trend of the credit applicant's industry for the future loan application period and generate the industry prospect index, further comprising importing external industry trend data and using the industry trend prediction model corresponding to the industry of the credit applicant to predict the industry trend of the credit applicant's industry for the future loan application period and generate the industry prospect index.

9. The method for providing a trial loan interest rate suggestion to assist in credit approval as described in Request 6, wherein the credit interest rate assessment server analyzes the revenue ratio of the credit application identification information in the credit customer's industry category, further including importing external business data and combining it with the queried credit customer's transaction history records to analyze the revenue ratio of the credit application identification information in the credit customer's industry category.

10. The method for providing a trial loan application interest rate suggestion to assist in credit approval as described in claim 6, wherein the credit interest rate assessment server comprehensively calculates a net benefit of the credit application information based on the credit limit, the loan application interest rate suggestion information, an industry risk weight, a capital adequacy ratio, a capital cost ratio, and a funding cost ratio, and generates an approval suggestion information based on the net benefit to provide an approval suggestion to the credit approval terminal device for display on the credit application approval page.

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