Freight logistics enterprise expressway pass loan system

Abstract

The invention discloses a freight logistics enterprise expressway pass loan system, which comprises an expressway ETC data acquisition module, a data processing module, a data analysis module, a credit decision module, a loan issuing and management module and a risk monitoring module, the high-speed ETC data acquisition module is in butt joint with a highway toll collection system to obtain passing data of vehicles in real time, and an original data set is formed; the data processing module cleans each kind of collected data; the data analysis module analyzes the processed data, extracts the passing frequency, the recharging period and the average toll of the enterprise, and expands an original data set; the credit extension decision module determines a loan limit and an interest rate for the freight enterprises and the individual industrial and commercial tenants based on the expanded original data set and a preset credit extension model; and the loan issuing and management module is responsible for issuing loan funds to a specified account according to the fixed loan amount and the interest rate, and monitoring the use condition of the funds.

Description

Technical Field

[0001] The present invention belongs to the technical field of high-speed passage loans and relates to a high-speed passage loan system for freight logistics enterprises. Background Art

[0002] The traditional business practices of the logistics industry of paying on delivery and settling freight after delivery have brought capital turnover pressure to transportation companies, and highway tolls are also a considerable expense. In the existing technology, various types of personal consumption loans commonly seen in ETC cannot meet the operating capital needs of freight logistics companies in highway toll scenarios. Existing loan products are usually based on traditional indicators such as corporate financial statements and credit ratings for credit granting. For groups such as freight logistics companies that are asset-light, have rich operating data but relatively weak financial data, it is difficult to provide accurate and effective loan services. Although some online loan products have simplified the process, they are insufficient in data integration and application, and cannot fully utilize emerging data sources such as ETC toll data for risk assessment and credit decision-making. At present, there are no loan products based on the common highway and banking systems, and the transmission of information and data is mostly offline. Even if there is a system connection between some financial institutions and highways, it is not complete, and the confidentiality between systems is poor. Therefore, it is urgent to develop an efficient, accurate and secure highway toll loan system for freight logistics companies. Summary of the invention

[0003] In order to solve the above technical problems, the purpose of the present invention is to provide a high-speed passage loan system for freight logistics enterprises.

[0004] The present invention provides a high-speed passage loan system for freight logistics enterprises, including: a high-speed ETC data acquisition module, a data processing module, a data analysis module, a credit decision module, a loan issuance and management module and a risk monitoring module;

[0005] The high-speed ETC data acquisition module acquires the vehicle's traffic data in real time by connecting with the highway toll collection system to form an original data set;

[0006] The data processing module cleans each type of collected data to remove abnormalities and missing values;

[0007] The data analysis module analyzes the processed data to extract valuable information, including the enterprise's toll frequency, recharge cycle and average toll, and expands the original data set;

[0008] The credit decision module determines the loan amount and interest rate for freight companies and individual business owners based on the expanded original data set and the preset credit model;

[0009] The loan issuance and management module is responsible for issuing loan funds to designated accounts according to the loan amount and interest rate, and monitoring the use of funds;

[0010] The risk monitoring module monitors the business conditions and loan usage of the enterprise in real time by setting early warning indicators, and promptly identifies potential risks.

[0011] Furthermore, the passage data includes high-speed ETC passage data including passage time, toll amount, recharge amount, recharge time, passage expressway exit, accounting time, accounting expressway exit, etc., as well as financial statement information of small and micro enterprise customers.

[0012] Furthermore, the high-speed ETC data collection module includes: the head office's Huidongni component and the branch's external data component. The traffic data query process is as follows:

[0013] 1) Authorization query: The Huidongni component of the head office triggers the authorization transaction to the external data component of the branch. The Huidongni component of the head office acts as the initiator and sends specific authorization request information. After receiving the request, the external data component of the branch conducts authorization verification. After confirming that the verification is passed, authorization registration is performed. The request is transmitted to the highway toll system through the branch external connection component in an asynchronous manner to realize data query.

[0014] 2) Data push: The branch external liaison component encrypts the queried high-speed traffic data and buffer limit information and pushes them to the Huidongni component of the head office.

[0015] Furthermore, for the authorization query process, when the Huidongni component of the head office triggers the authorization transaction to the external data component of the branch, the transaction information is encrypted using the national secret SM4 encryption algorithm. After the external data component of the branch receives the encrypted information, it decrypts it using the corresponding decryption algorithm and uses the preset verification rules to verify the integrity and accuracy of the information;

[0016] After receiving the encrypted information, the branch's external data component decrypts it using the corresponding decryption algorithm and verifies the integrity and accuracy of the information using the preset verification rules. After the verification is passed, authorization registration is performed;

[0017] When using asynchronous methods to transmit information through branch external liaison components to the highway toll system for data query, encrypted transmission is also used to ensure the security of information during transmission.

[0018] Furthermore, during the data push phase, the branch external liaison component will encrypt the queried high-speed traffic data and buffer limit information and push them to the head office's Huidongni component; after receiving the data, the head office's Huidongni component will use the corresponding decryption method to obtain the data, and verify the signature or other verification information of the data to ensure that the source of the data is credible and has not been tampered with.

[0019] Furthermore, the head office's Huidongni component pushes the collected data to the data processing module, cleans each type of data, removes anomalies and missing values, and formats the time data.

[0020] Furthermore, the credit model of the credit decision module adopts a Logistic regression model, and the expanded data set is used as the input of the Logistic regression model. The output of the Logistic regression model is the probability value of default of a small enterprise; through the gradient descent optimization algorithm, the model parameters are continuously adjusted to minimize the cross entropy loss and improve the accuracy of the model prediction.

[0021] Further: Dataset division: divide the expanded data set into training set, validation set and test set; use multi-layer cross-validation technology to divide the training set into multiple sub-training sets and sub-validation sets;

[0022] Training evaluation: During model training, the model is trained on each sub-training set and evaluated on the corresponding sub-validation set; through multiple iterations, the performance of the model on different data subsets is evaluated;

[0023] Result integration: Based on the results of each iteration, the performance evaluation indicators of the model on the entire dataset are integrated.

[0024] Furthermore, in the credit decision-making module, a credit score is assigned to small and micro enterprise customers based on the model prediction results. The higher the credit score, the lower the risk of customer default. The loan amount and interest rate are determined based on the credit score and the formulated loan issuance strategy.

[0025] Furthermore, the loan issuance and management module adopts the branch personal loan inclusive component, and the branch personal loan inclusive component performs the loan payment process as follows:

[0026] 1) When the expressway toll collection system sends a branch payment request, the branch's personal loan inclusive component will respond quickly and make the following judgments: First, determine whether the binding relationship between the ETC account and the loan account exists. If it is a binding state, further determine whether the payment time is after the binding time. If it also meets the conditions, determine whether it is the first payment;

[0027] 2) If it is the first time to use the loan, the branch's personal loan inclusive component will call the head office's loan disbursement transaction to perform the disbursement operation, and register the disbursement flow information and disbursement status information in detail, and return the accurate result information to the highway toll collection system in a timely manner;

[0028] 3) If it is a second expenditure, the branch's personal loan inclusive component will first determine the result of the last expenditure. If the result of the last expenditure was successful, no further expenditure will be made and the result information will be directly returned to the highway toll system; if the result of the last expenditure was a failure or undetermined, the result of the last expenditure will be queried and confirmed again in the head office loan component, and then judged whether this expenditure is needed based on the query result returned by the head office.

[0029] A high-speed transit loan system for freight logistics enterprises has the following beneficial effects:

[0030] 1. Compared with the prior art, the present invention can accurately meet the capital needs of freight logistics companies and effectively alleviate their capital turnover pressure.

[0031] 2. Simplify the loan process, reduce the loan cost and time cost of small and micro enterprises, and improve the availability of loans. Alleviate the financing difficulties of small and micro enterprises: This model provides small and micro freight logistics enterprises with a fast and convenient financing channel, effectively alleviating the operational pressure they face due to capital shortage.

[0032] 3. Make full use of ETC traffic data for credit granting and risk control, improving the scientificity and accuracy of loan decisions.

[0033] 4. It has achieved data and capital coordination among banks, highways and enterprises, and improved the efficiency and quality of financial services.

[0034] 5. Promote the healthy development of the logistics industry: By improving the capital turnover rate and operational efficiency of logistics companies, the healthy development of the entire logistics industry has been promoted. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a principle block diagram of a high-speed passage loan system for freight logistics enterprises of the present invention. DETAILED DESCRIPTION

[0036] like Figure 1 As shown, a high-speed passage loan system for freight logistics enterprises of the present invention includes: a high-speed ETC data acquisition module, a data processing module, a data analysis module, a credit decision module, a loan issuance and management module and a risk monitoring module.

[0037] The high-speed ETC data acquisition module obtains vehicle traffic data in real time by connecting to the highway toll collection system to form an original data set. The data processing module cleans each type of collected data, removes anomalies and missing values, and formats the time data. The data analysis module analyzes the processed data, extracts valuable information, including the company's traffic frequency, recharge cycle and average toll, and expands the original data set. The credit decision module determines the loan amount and interest rate for freight companies and individual industrial and commercial households based on the expanded original data set and the preset credit model. The loan issuance and management module is responsible for issuing loan funds to designated accounts according to the fixed loan amount and interest rate, and monitoring the use of funds. The risk monitoring module monitors the company's operating conditions and loan usage in real time by setting early warning indicators, and promptly discovers potential risks.

[0038] In specific implementation, the passage data include: high-speed ETC passage data including passage time, toll amount, recharge amount, recharge time, passage expressway exit, accounting time, accounting expressway exit, etc., as well as financial statement information of small and micro enterprise customers.

[0039] In specific implementation, the high-speed ETC data collection module includes: the Huidongni component of the head office and the external data component of the branch. The traffic data query process is as follows:

[0040] 1) Authorization query: The Huidongni component of the head office triggers the authorization transaction to the external data component of the branch. The Huidongni component of the head office acts as the initiator and sends specific authorization request information. After receiving the request, the external data component of the branch conducts authorization verification. After confirming that the verification is passed, authorization registration is performed. The request is asynchronously transmitted to the highway toll system through the branch external component to realize data query.

[0041] For the authorization query process, when the Huidongni component of the head office triggers the authorization transaction to the branch external data component, the transaction information is encrypted using the national secret SM4 encryption algorithm. After the branch external data component receives the encrypted information, it decrypts it through the corresponding decryption algorithm, and uses the preset verification rules to verify the integrity and accuracy of the information; after the branch external data component receives the encrypted information, it decrypts it through the corresponding decryption algorithm, and uses the preset verification rules to verify the integrity and accuracy of the information. After the verification passes, authorization registration is performed; when using asynchronous methods to send information through the branch external component to the highway toll system for data query, encrypted transmission is also used to ensure the security of information during transmission.

[0042] 2) Data push: The branch external liaison component encrypts the queried high-speed traffic data and buffer limit information and pushes them to the Huidongni component of the head office.

[0043] During the data push phase, the branch's external liaison component will encrypt the queried high-speed traffic data and buffer limit information and push them to the head office's Huidongni component; after receiving the data, the head office's Huidongni component uses the corresponding decryption method to obtain the data, and verifies the data's signature or other verification information to ensure that the source of the data is credible and has not been tampered with.

[0044] In specific implementation, the credit model of the credit decision module adopts a Logistic regression model, and the expanded data set is used as the input of the Logistic regression model. The output of the Logistic regression model is the probability value of default of a small enterprise; through the gradient descent optimization algorithm, the model parameters are continuously adjusted to minimize the cross entropy loss and improve the accuracy of the model prediction.

[0045] Before using the Logistic regression model to predict the probability of default of micro-enterprises, the importance of the data in the data set can be evaluated. Use the same data set as the Logistic regression model to build a LightGBM model, use the feature importance evaluation function of LightGBM to understand which data features have the greatest impact on the prediction results, and select the most valuable data features for credit score prediction to form the input data set of the Logistic regression model.

[0046] Before training the Logistic regression model, the data set is divided: the expanded data set is divided into a training set, a validation set, and a test set; the training set is divided into multiple sub-training sets and sub-validation sets using multi-layer cross-validation technology.

[0047] Perform training evaluation: During model training, the model is trained on each sub-training set and evaluated on the corresponding sub-validation set; through multiple iterations, the performance of the model on different data subsets is evaluated.

[0048] Result integration: Based on the results of each iteration, the performance evaluation indicators of the model on the entire dataset are integrated.

[0049] After obtaining the probability value of micro-enterprise default, the credit decision-making module assigns a credit score to the micro-enterprise customer based on the model prediction results. The higher the credit score, the lower the risk of customer default. The loan amount and interest rate are determined based on the credit score and the formulated loan issuance strategy.

[0050] The loan issuance and management module adopts the branch personal loan inclusive component. After determining the loan amount and interest rate, the branch personal loan inclusive component performs the loan payment process as follows:

[0051] 1) When the expressway toll collection system sends a branch payment request, the branch's personal loan inclusive component will respond quickly and make the following judgments: First, determine whether the binding relationship between the ETC account and the loan account exists. If it is a binding state, further determine whether the payment time is after the binding time. If it also meets the conditions, determine whether it is the first payment;

[0052] 2) If it is the first time to use the loan, the branch's personal loan inclusive component will call the head office's loan disbursement transaction to perform the disbursement operation, and register the disbursement flow information and disbursement status information in detail, and return the accurate result information to the highway toll collection system in a timely manner;

[0053] 3) If it is a second expenditure, the branch's personal loan inclusive component will first determine the result of the last expenditure. If the result of the last expenditure was successful, no further expenditure will be made and the result information will be directly returned to the highway toll system; if the result of the last expenditure was a failure or undetermined, the result of the last expenditure will be queried and confirmed again in the head office loan component, and then judged whether this expenditure is needed based on the query result returned by the head office.

[0054] 4) Financial verification: The branch will conduct a detailed reconciliation of the previous day's expenditure data. For expenditure records marked as failed or uncertain, the head office will be requested to query and confirm the records one by one. After completing all confirmation work, the accurate reconciliation documents will be sorted and sent to the highway toll system.

[0055] The branch's personal loan inclusive component will regularly query the highway toll data of customers who have applied for highway cloud loans, and accurately send this data to the head office's post-loan risk monitoring module for early warning analysis.

[0056] The branch's personal loan inclusive component will also receive the ETC account status sent regularly by the highway toll system, and send the status information to the head office's post-loan risk monitoring module in a timely manner for early warning processing.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the concept of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A freight logistics enterprise high-speed transit loan system, characterized in that: include: High-speed ETC data collection module, data processing module, data analysis module, credit decision module, loan issuance and management module and risk monitoring module; The high-speed ETC data acquisition module acquires the vehicle's traffic data in real time by connecting with the highway toll collection system to form an original data set; The data processing module cleans each type of collected data to remove abnormalities and missing values; The data analysis module analyzes the processed data to extract valuable information, including the enterprise's toll frequency, recharge cycle and average toll, and expands the original data set; The credit decision module determines the loan amount and interest rate for freight companies and individual business owners based on the expanded original data set and the preset credit model; The loan issuance and management module is responsible for issuing loan funds to designated accounts according to the loan amount and interest rate, and monitoring the use of funds; The risk monitoring module monitors the business conditions and loan usage of the enterprise in real time by setting early warning indicators, and promptly identifies potential risks.

2. The freight logistics enterprise high-speed transit loan system as claimed in claim 1, characterized in that: The passage data include: high-speed ETC passage data including passage time, toll amount, recharge amount, recharge time, passage expressway exit, accounting time, accounting expressway exit, etc., as well as financial statement information of small and micro enterprise customers.

3. The freight logistics enterprise high-speed transit loan system as claimed in claim 1, characterized in that: The high-speed ETC data collection module includes: the head office's Huidongni component and the branch's external data component. The traffic data query process is as follows: 1) Authorization query: The Huidongni component of the head office triggers the authorization transaction to the external data component of the branch. The Huidongni component of the head office acts as the initiator and sends specific authorization request information. After receiving the request, the external data component of the branch conducts authorization verification. After confirming that the verification is passed, authorization registration is performed. The request is transmitted to the highway toll system through the branch external connection component in an asynchronous manner to realize data query. 2) Data push: The branch external liaison component encrypts the queried high-speed traffic data and buffer limit information and pushes them to the Huidongni component of the head office.

4. The freight logistics enterprise high-speed transit loan system as claimed in claim 3 is characterized in that: For the authorization query process, when the Huidongni component of the head office triggers the authorization transaction to the external data component of the branch, the transaction information is encrypted using the national secret SM4 encryption algorithm. After the external data component of the branch receives the encrypted information, it decrypts it using the corresponding decryption algorithm and uses the preset verification rules to verify the integrity and accuracy of the information; After receiving the encrypted information, the branch's external data component decrypts it using the corresponding decryption algorithm and verifies the integrity and accuracy of the information using the preset verification rules. After the verification is passed, authorization registration is performed; When using asynchronous methods to transmit information through branch external liaison components to the highway toll system for data query, encrypted transmission is also used to ensure the security of information during transmission.

5. The freight logistics enterprise high-speed transit loan system as claimed in claim 3 is characterized in that: During the data push phase, the branch's external liaison component will encrypt the queried high-speed traffic data and buffer limit information and push them to the head office's Huidongni component; after receiving the data, the head office's Huidongni component uses the corresponding decryption method to obtain the data, and verifies the data's signature or other verification information to ensure that the source of the data is credible and has not been tampered with.

6. The freight logistics enterprise high-speed transit loan system as claimed in claim 1, characterized in that: The head office's Huidongni component pushes the collected data to the data processing module, cleans each type of data, removes anomalies and missing values, and formats the time data.

7. The freight logistics enterprise high-speed transit loan system as claimed in claim 1, characterized in that: The credit model of the credit decision module adopts a Logistic regression model, and the expanded data set is used as the input of the Logistic regression model. The output of the Logistic regression model is the probability value of default of a small enterprise; through the gradient descent optimization algorithm, the model parameters are continuously adjusted to minimize the cross entropy loss and improve the accuracy of the model prediction.

8. The freight logistics enterprise high-speed transit loan system as claimed in claim 7, characterized in that: Dataset division: Divide the expanded dataset into training set, validation set and test set; use multi-layer cross-validation technology to divide the training set into multiple sub-training sets and sub-validation sets; Training evaluation: During model training, the model is trained on each sub-training set and evaluated on the corresponding sub-validation set; through multiple iterations, the performance of the model on different data subsets is evaluated; Result integration: Based on the results of each iteration, the performance evaluation indicators of the model on the entire dataset are integrated.

9. The freight logistics enterprise high-speed transit loan system as claimed in claim 7, characterized in that: In the credit decision-making module, small and micro enterprise customers are assigned a credit score based on the model prediction results. The higher the credit score, the lower the risk of customer default. The loan amount and interest rate are determined based on the credit score and the formulated loan issuance strategy.

10. The freight logistics enterprise high-speed transit loan system as claimed in claim 1, characterized in that: The loan issuance and management module adopts the branch personal loan inclusive component, and the loan payment process of the branch personal loan inclusive component is as follows: 1) When the expressway toll collection system sends a branch payment request, the branch's personal loan inclusive component will respond quickly and make the following judgments: First, determine whether the binding relationship between the ETC account and the loan account exists. If it is a binding state, further determine whether the payment time is after the binding time. If it also meets the conditions, determine whether it is the first payment; 2) If it is the first time to use the loan, the branch's personal loan inclusive component will call the head office's loan disbursement transaction to perform the disbursement operation, and register the disbursement flow information and disbursement status information in detail, and return the accurate result information to the highway toll collection system in a timely manner; 3) If it is a second expenditure, the branch's personal loan inclusive component will first determine the result of the last expenditure. If the result of the last expenditure was successful, no further expenditure will be made and the result information will be directly returned to the highway toll system; if the result of the last expenditure was a failure or undetermined, the result of the last expenditure will be queried and confirmed again in the head office loan component, and then judged whether this expenditure is needed based on the query result returned by the head office.

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