Credit granting method

Abstract

The invention belongs to the technical field of data processing, and particularly relates to a credit granting method, credit granting analysis data required by enterprise loan is acquired in advance, and a reasonable access model and a credit granting model are established, so that when an enterprise initiates a loan request, a system can obtain required evaluation data in time, automatic evaluation of the loan is realized, and the efficiency is improved. Therefore, the quality and efficiency of risk management and control of credit products are ensured while the second-batch and second-loan is realized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of data processing, and particularly relates to a credit granting method. BACKGROUND

[0002] Science and technology small and micro enterprises play an important role in the national innovation-driven development strategy. However, due to their light asset, high growth and high risk characteristics, traditional credit models are difficult to meet their financing needs. Traditional credit services usually rely on manual review, which is tedious and inefficient, and it is difficult to accurately assess the credit risk of science and technology enterprises. In addition, science and technology enterprises often lack traditional collateral, making it difficult for them to obtain financing. Chinese patent CN112102064A discloses an intelligent credit granting method for science and technology small and medium-sized enterprises, which discloses specific methods for qualification identification, enterprise life cycle division, enterprise growth assessment and enterprise credit limit determination of science and technology small and medium-sized enterprises. This credit granting method requires a variety of data to be collected, and the data collection and evaluation operation is difficult, making it still difficult to balance the approval efficiency and risk control of credit. SUMMARY

[0003] The purpose of the present application is to provide a credit granting method that can effectively improve the efficiency of credit services and reduce risks.

[0004] To achieve the above purpose, the technical solution adopted by the present application is as follows: a credit granting method, comprising the following steps:

[0005] A. Pre-collecting data;

[0006] Collecting credit analysis data of enterprises identified as science and technology enterprises and storing them in a cloud server;

[0007] B. Initiating a loan request;

[0008] The enterprise initiates a loan request online. After the credit granting system accepts the loan request, it determines whether the requesting enterprise is identified as a science and technology enterprise. If so, it obtains the credit analysis data of the requesting enterprise from the cloud server and proceeds to step C. If not, it proceeds to the regular loan process;

[0009] C. Data processing;

[0010] The credit granting system obtains credit analysis data from the cloud server, including enterprise tax data, business data, credit data and intellectual property data, and standardizes the credit analysis data into a preset format;

[0011] D. Access evaluation;

[0012] The credit granting system inputs the information obtained in step C into a preset access model to obtain the access score of the requesting enterprise. If the access score of the requesting enterprise reaches a preset threshold, it proceeds to step E. Otherwise, it rejects the loan request;

[0013] E, credit assessment;

[0014] The credit system inputs the information obtained in the step C into a preset credit model to obtain a credit limit and a rate of interest of the requesting enterprise, and then issues a loan.

[0015] Compared with the prior art, the present application has the following technical effects: the credit analysis data required by the enterprise for a loan is collected in advance, and a reasonable access model and a credit model are established, so that when the enterprise initiates a loan request, the system can obtain the required evaluation data in time, thereby realizing automatic evaluation of the loan, and further realizing "second approval and second loan" while ensuring the risk control and quality of the credit product. DETAILED DESCRIPTION

[0016] The specific embodiments of the present application will be further described in detail below through examples.

[0017] A credit method, comprising the following steps:

[0018] A, pre-collection of data;

[0019] The credit analysis data of the enterprises identified as technology-based enterprises are collected and stored in the cloud server.

[0020] The credit analysis data includes enterprise tax data, business data, credit data, intellectual property data, etc. These data can be used to evaluate the business development of the enterprise, and can also be used by banks, financial institutions or commercial institutions to analyze the credit status, repayment ability and repayment willingness of the enterprise. The credit analysis data is summarized in the cloud server, and after the authorized user obtains authorization, all the required data can be obtained at one time, and then the credit assessment link can be quickly entered, thereby speeding up the credit approval efficiency.

[0021] B, initiation of a loan request;

[0022] The enterprise in need of a loan initiates a loan request online, and after the credit system accepts the loan request, it first determines whether the requesting enterprise is identified as a technology-based enterprise. If yes, the credit analysis data of the requesting enterprise is obtained from the cloud server and step C is entered. If no, the conventional loan process is entered.

[0023] Usually, the credit system receives the loan request at the same time and obtains the authorization of the enterprise, and then the relevant data of the enterprise can be obtained from other systems. First, determine whether the requesting enterprise is a technology-based enterprise. If yes, all the required credit analysis data can be obtained from the cloud server at one time, and the lengthy and complex data acquisition process is omitted, and the credit analysis process specially set for technology-based enterprises is quickly entered.

[0024] C, data processing;

[0025] The credit analysis data obtained by the credit system from the cloud server includes enterprise tax data, business data, credit data, and intellectual property data, and the credit analysis data is standardized into a preset format. After cleaning and standardizing the data, the data is obtained in a unified format and matched with the subsequent analysis model.

[0026] D. Access evaluation;

[0027] The credit system inputs the information obtained by the standardization process in step C into a preset access model to obtain the access score of the requesting enterprise. If the access score of the requesting enterprise reaches a preset threshold, it proceeds to step E, otherwise it rejects the loan request.

[0028] The access model is used to screen enterprises that meet the loan conditions. The evaluation indicators input into the access model include enterprise establishment time, registered capital, shareholder members, number of intellectual property rights, technology field of intellectual property rights, patent quality, R&D investment proportion, technical innovation ability, industry prospect of the enterprise, market competitiveness, customer evaluation information, etc.

[0029] E. Credit evaluation;

[0030] The credit system inputs the information obtained by the standardization process in step C into a preset credit model to obtain the credit limit and interest rate of the requesting enterprise, and then issues a loan.

[0031] The credit model is used to evaluate the repayment ability and risk level of the enterprise, and then provide a reference for the specific credit limit and interest rate of the enterprise. The evaluation indicators input into the credit model include sales revenue growth rate, net profit rate, operating cash flow, enterprise historical operating data volatility, core customer concentration, patent quality, technology achievement transformation ability, industry growth potential, and policy support intensity.

[0032] At this point, the credit service is completed online from application to approval. The enterprise submits a loan application through an online channel, and the credit system automatically calls the access model and the credit model for evaluation, thereby realizing "second batch second loan", that is, after the application is submitted, the credit system completes the approval and issues a loan in a short time.

[0033] Further, to ensure repayment, it further includes step F, that is, after the loan is issued, the credit system continuously obtains the credit analysis data of the requesting enterprise from the cloud server, and inputs the data obtained by the standardization process into a preset risk evaluation model, and when the requesting enterprise has a repayment risk, it is warned.

[0034] In this embodiment, after obtaining the latest credit analysis data of the requesting enterprise from the cloud server, the current credit-related information is input into a preset credit model to obtain the current credit limit and interest rate of the requesting enterprise. If the difference between the current credit limit and interest rate and the credit limit and interest rate when the loan is issued in step E exceeds a threshold, a risk warning is issued.

[0035] In other embodiments, other warning methods can also be used. For example, in step F, the current credit-related information of the requesting enterprise is input into a preset credit model to obtain the current credit limit and interest rate of the requesting enterprise. If the difference between the current credit limit and interest rate and the credit limit and interest rate when the loan is issued in step E exceeds a threshold, the current credit-related information of the requesting enterprise is input into a preset access model to obtain the current access score of the requesting enterprise. If the current access score does not meet a preset threshold, a risk warning is issued; otherwise, the requesting enterprise is evaluated again after a certain period of time.

Claims

1. A credit granting method, characterized in that, Includes the following steps: A. Pre-collected data; Credit analysis data of enterprises identified as technology-based enterprises is collected and stored on cloud servers; B. Initiate a loan request; When a company initiates a loan request online, the credit system will determine whether the requesting company is recognized as a technology-based enterprise. If so, it will retrieve the credit analysis data of the requesting company from the cloud server and proceed to step C. If not, it will proceed to the regular loan process. C. Data processing; The credit analysis data obtained by the credit system from the cloud server includes corporate tax data, business registration data, credit information data, and intellectual property data. The credit analysis data is then standardized and processed into a preset format. D. Access assessment; The credit granting system inputs the information obtained from the standardized processing in step C into the preset access model to obtain the access score of the requesting enterprise. If the access score of the requesting enterprise reaches the preset threshold, it proceeds to step E; otherwise, the loan request is rejected. E. Credit assessment; The credit granting system inputs the information obtained from the standardized processing in step C into a preset credit granting model to obtain the credit limit and interest rate of the requesting enterprise, and then issues the loan.

2. The credit granting method according to claim 1, characterized in that: In step D, the information input into the admission model includes the company's establishment time, registered capital, shareholders, number of intellectual property rights, the technical field of the intellectual property rights, patent quality, R&D investment ratio, technological innovation capability, industry prospects, market competitiveness, and customer evaluation information.

3. The credit granting method according to claim 1, characterized in that: The information input into the credit model in step E includes sales revenue growth rate, net profit margin, operating cash flow, volatility of the company's historical operating data, core customer concentration, patent quality, technology transfer capability, industry growth potential, and policy support.

4. The credit granting method according to claim 1, characterized in that: It also includes step F, in which, after the loan is issued, the credit system continuously obtains the credit analysis data of the requesting enterprise from the cloud server, and inputs the standardized data into a preset risk assessment model, and issues an early warning when the requesting enterprise has a repayment risk.

5. The credit granting method according to claim 4, characterized in that: In step F, the current credit information of the requesting enterprise is input into a preset credit model to obtain the current credit limit and interest rate of the requesting enterprise. If the difference between the current credit limit and interest rate and the credit limit and interest rate when the loan is issued in step E exceeds a threshold, a risk warning is issued.

6. The credit granting method according to claim 4, characterized in that: In step F, the current credit information of the requesting enterprise is input into a preset credit model to obtain the current credit limit and interest rate of the requesting enterprise. If the difference between the current credit limit and interest rate and the credit limit and interest rate at the time of loan disbursement in step E exceeds a threshold, The current credit information of the requesting enterprise is input into a preset access model to obtain the current access score of the requesting enterprise. If the current access score does not meet the preset threshold, a risk warning is issued.