Qualification party determination method and device, electronic equipment and storage medium

Abstract

The invention discloses a capital party determination method and device, electronic equipment and a storage medium, and relates to the technical field of capital party recommendation, and the method comprises the steps: obtaining interface data and loan bill data of candidate capital parties when a loan application is received; determining a qualification screening rule based on the interface data and the loan bill data; obtaining an initial screening rule, and updating the initial screening rule based on the qualification screening rule to obtain a target screening rule; and determining a target qualification party matched with the loan application in the candidate qualification parties according to a target screening rule. According to the technical scheme, the capital party screening rule is obtained by analyzing the interface data and the loan bill data, then the initial screening rule is updated, the target screening rule is obtained, and the target capital party is determined based on the target screening rule, so that the problem that the existing capital party screening rule modification mode cannot quickly respond to the change of the capital party is solved; the fund party pre-screening rule is dynamically updated, and the pushing accuracy and efficiency of the fund party are improved.

Description

Technical Field

[0001] The present invention relates to the field of funding source recommendation technology, and in particular to a funding source determination method, device, electronic device and storage medium. Background Art

[0002] Currently, when customers apply for loans online, financial technology companies connect with funding providers through loan assistance services, and the funding providers decide whether to grant loans to customers. As the types and numbers of funding providers increase, such as consumer finance, small loans, local banks, trusts, etc., each funding provider has its own unique pre-screening rules, but financial technology companies cannot know these pre-screening rules, and changes in the funding provider's pre-screening rules cannot be predicted. When the customer's loan application is pushed to the funding provider, the failure rate is very high if the rules are not met, and the customer's loan needs cannot be met in a timely manner. A method that can pre-screen funding providers online is needed to improve the efficiency and accuracy of the funding provider's push.

[0003] The current common practice is that when accessing the funding party, the business and the funding party confirm the pre-screening rules and manually configure them into the system. The manual confirmation method has the problem of incomplete information, and when the funding party's pre-screening rules change, they are often not synchronized with the fintech company, and cannot respond quickly to changes in the funding party. The fintech company can only passively wait for the business manager to synchronize information and manually configure it into the funding party's pre-screening rules. This method consumes a lot of offline manpower and material costs, and has a strong dependence on manpower. It cannot meet the needs of responding to changes in pre-screening rules of various funding parties in the Internet era. Summary of the invention

[0004] The present invention provides a funding party determination method, device, electronic device and storage medium to improve the funding party's push efficiency and increase the accuracy, automation and digitization of loan application processing.

[0005] According to one aspect of the present invention, a method for determining an investor is provided, comprising:

[0006] When receiving a loan application, obtain the candidate investor's interface data and loan order data;

[0007] Determine a funder screening rule based on the interface data and the loan order data;

[0008] Acquire initial screening rules, and update the initial screening rules based on the investor screening rules to obtain target screening rules;

[0009] A target investor matching the loan application is determined among the candidate investors according to a target screening rule.

[0010] According to another aspect of the present invention, a method for determining an investor is provided, comprising:

[0011] The data acquisition module is used to obtain the interface data and loan order data of the candidate funder when receiving the loan application;

[0012] A screening rule determination module, used to determine the funder screening rule based on the interface data and the loan order data;

[0013] A screening rule updating module, used to obtain an initial screening rule, and update the initial screening rule based on the investor screening rule to obtain a target screening rule;

[0014] The target funder determination module is used to determine the target funder matching the loan application according to the target screening rules.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor;

[0017] and a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the sponsor described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining a sponsor described in any embodiment of the present invention when executed.

[0020] The technical solution of the embodiment of the present invention includes: when receiving a loan application, obtaining the interface data and loan order data of the candidate investor; determining the investor screening rules based on the interface data and the loan order data; obtaining the initial screening rules, and updating the initial screening rules based on the investor screening rules to obtain the target screening rules; determining the target investor that matches the loan application among the candidate investors according to the target screening rules. The technical solution of the present invention obtains the investor screening rules by analyzing the interface data and the loan order data, and then updates the initial screening rules to obtain the target screening rules, so as to determine the target investor based on the target screening rules, thereby solving the problem that the existing investor screening rule modification method cannot quickly respond to the changes of the funding party, and realizes the dynamic update of the funding party pre-screening rules, improves the push efficiency of the funding party, and improves the accuracy, automation and digitization of the loan application processing. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A flowchart of a method for determining a capital provider provided in the first embodiment of the present invention;

[0023] Figure 2 A flowchart of a method for determining a capital provider provided in Embodiment 2 of the present invention;

[0024] Figure 3 A schematic diagram of the structure of a device for determining a capital provider provided in Embodiment 3 of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment 1

[0029] Figure 1This is a flow chart of a method for determining a funding source provided in the first embodiment of the present invention. This embodiment can be applied to the situation where a financial technology company accurately and efficiently recommends funding sources to a client when receiving a loan application from the client. This method can be executed by a funding source determination device, which can be implemented in the form of hardware and / or software, and can be configured in a computer device. Figure 1 As shown, the method includes:

[0030] S110. When a loan application is received, the interface data and loan order data of the candidate investor are obtained.

[0031] Among them, the loan application can be an application submitted by a customer, and the candidate funder can be multiple funders connected to the fintech company, and the funder can provide the amount required for the loan application. The interface data can be the data related to authorization or loan provided by the candidate funder, and the loan order data can be the data related to loans generated by historical users. For example, the loan order data includes the funder, loan time, loan amount, status: normal, overdue, compensation, buyout, and overdue days.

[0032] Specifically, when a loan application is received, the funding party pre-screening method of the present invention can obtain the interface data and loan order data of the candidate funding party, so as to facilitate subsequent analysis thereof to determine accurate loan screening rules.

[0033] On the basis of the above technical solution, the interface data of the candidate investor is obtained, including: collecting the interface data returned by the data interface of the investor through an interface data center.

[0034] The interface data includes at least one of a credit record and a loan record.

[0035] Specifically, after a customer submits a loan application online, he or she can communicate with the candidate investors through preset interfaces, such as the credit interface, loan interface, etc. The interface data collection center can collect a large amount of data returned by these interfaces and record it in the local database as the basis for subsequent data analysis.

[0036] The interface data mainly includes credit records and loan records. The credit records contain key information such as the funding party, credit time, credit return information, and credit status (success or failure); the loan records may contain key information such as the funding party, loan time, loan return information, and loan status (success or failure).

[0037] S120: Determine a funder screening rule based on the interface data and the loan order data.

[0038] Among them, the funder screening rule is used to screen out the funder who provides loans for the loan application from multiple funders.

[0039] It is understandable that the interface data reflects the feedback of the funding party on the loan application, and the loan order data can be information reflecting the customer's loan situation. Based on the analysis of the loan order data and the interface data, the rules for recommending and screening funding parties can be determined, which can improve the pass rate of pushing funding parties, meet the customer's loan needs, and improve the efficiency and accuracy of the funding party's push.

[0040] In an embodiment of the present invention, determining the investor screening rules based on the interface data and the loan order data includes: analyzing the interface data and the loan order data by an interface data analysis center according to a preset analysis type to obtain the investor screening rules.

[0041] The preset analysis type includes at least one of a parameter analysis type and an association analysis type.

[0042] Specifically, the interface data and loan order data can be analyzed through the interface data analysis center to determine the capital screening rules. During the analysis process of the interface data analysis center, the interface data analysis center can conduct in-depth analysis of the above two types of data according to the preset analysis type. For the parameter analysis type, the analysis process mainly focuses on the specific parameters in the data; for the association analysis type, the analysis process mainly focuses on the association between the data.

[0043] In an embodiment of the present invention, if the preset analysis type is a parameter analysis type, the interface data and the loan order data are analyzed by the interface data analysis center to obtain the investor screening rules, which may include: obtaining the features to be analyzed and the expressions to be used corresponding to the parameter analysis type; determining the feature values ​​to be analyzed corresponding to the features to be analyzed in the interface data and / or the loan order data; inputting the features to be analyzed, the feature values ​​to be analyzed and the expressions to be used into a large model, and obtaining the investor screening rules based on reasoning from the large model.

[0044] Among them, the features to be analyzed can be multiple pre-set features related to borrowing and lending. For example, the features to be analyzed can include name, name length, address, address length, credit bank card, lending bank card, ID card validity period, first cash withdrawal validity period, non-first cash withdrawal validity period, credit time, loan time, credit limit, industry, occupation, purpose of borrowing, etc.

[0045] The expression to be used may include: contains, does not contain, is greater than, is greater than or equal to, is equal to, is less than, is less than or equal to, is not equal to, range, etc. The feature value to be analyzed may be a specific value corresponding to the feature to be analyzed. The capital screening rule includes the feature to be analyzed, the target expression of the feature to be analyzed, and the target feature value corresponding to the feature to be analyzed.

[0046] Specifically, the features to be analyzed corresponding to the parameter analysis type can be pre-set, so that the features to be analyzed can be determined to obtain the capital screening rules. Then, the feature values ​​corresponding to the features to be analyzed, that is, the actual data values, can be extracted from the interface data and loan order data for the subsequent large model reasoning process.

[0047] After obtaining the features to be analyzed, the feature values ​​to be analyzed, and the expressions to be used, this information can be input into the pre-trained large model, which can perform reasoning and analysis based on the input features to be analyzed, the feature values ​​to be analyzed, and the expressions to be used to obtain the capital screening rules. The capital screening rules include the features to be analyzed, the target expressions of the features to be analyzed, and the target feature values.

[0048] For example, when the feature to be analyzed is "industry", multiple feature values ​​to be analyzed extracted from the interface data or loan order data all have corresponding credit failures for "financial industry", which means that the investor cannot grant credit to customers in the "financial industry". The investor screening rule "industry does not include financial industry" can be generated, that is, the feature to be analyzed is "industry", the target expression is "does not include", and the target feature value is "financial industry".

[0049] Here are some pre-screening rules:

[0050] 1. The name cannot contain the characters *, -,.

[0051] 2. The name length cannot exceed A

[0052] 3. The length of the residential address is between AB

[0053] 4. Residential address with province and city, residential address without province and city

[0054] 5. The credit and loan bank cards are inconsistent, so the A funding party cannot be pushed.

[0055] 6. The industry cannot be A or B

[0056] 7. The purpose of the loan cannot be A

[0057] 8. A funder’s dark period adjustment time B

[0058] 9. The validity period for the first withdrawal of funder A is B days, and the validity period for non-first withdrawal is C days

[0059] S130: Acquire initial screening rules, and update the initial screening rules based on the capital screening rules to obtain target screening rules.

[0060] Among them, the initial screening rules can be pre-set investor screening rules, which can be general rules set based on historical experience, or obtained by business personnel through investors. As investors flexibly change their loan approval requirements, the initial screening rules may not meet the changed investors. Therefore, the initial screening rules can be updated based on the investor screening rules. Specifically, the investor screening rules and the initial screening rules can be combined to obtain target screening rules that are closer to the actual approval standards of investors.

[0061] S140: Determine a target investor among the candidate investors that matches the loan application according to a target screening rule.

[0062] It is understandable that financial technology companies usually have access to multiple candidate investors and can generate a candidate investor set, which includes all investors who may be pushed loan applications. Furthermore, each investor in the candidate investor set can be evaluated one by one according to the target screening rules to determine which investors are most compatible with the current loan application, and select one or more target investors who are most compatible with the loan application. In this way, compared to manually configuring pre-screening rules, there are problems such as high labor costs, high communication costs, untimely communication, and easy information asymmetry. The present invention can complete the pre-screening of investors more quickly and efficiently based on the target screening rules, and the pre-screening effect is more accurate.

[0063] The technical solution of the embodiment of the present invention includes: upon receiving a loan application, obtaining the interface data and loan form data of the candidate investor; determining the investor screening rules based on the interface data and the loan form data; obtaining the initial screening rules, and updating the initial screening rules based on the investor screening rules to obtain the target screening rules; and determining the target investor among the candidate investors that matches the loan application according to the target screening rules. The technical solution of the present invention obtains the investor screening rules by analyzing the interface data and the loan form data, and then updates the initial screening rules to obtain the target screening rules, so as to determine the target investor based on the target screening rules, thereby solving the problem that the existing investor screening rule modification method cannot quickly respond to changes in the funding party, and realizes the dynamic update of the funding party pre-screening rules, improves the funding party's push efficiency, and improves the accuracy, automation, and digitization of loan application processing.

[0064] Embodiment 2

[0065] Figure 2 This is a flowchart of a method for determining a capital source provided in the second embodiment of the present invention. Based on the above embodiment, this embodiment further illustrates the implementation method when the preset analysis type is an associated analysis type. The specific implementation method can refer to the technical solution of this embodiment. Among them, the technical terms that are the same as or corresponding to the above embodiment are not repeated here. Figure 2 As shown, the method includes:

[0066] S210. When a loan application is received, the interface data and loan order data of the candidate investor are obtained.

[0067] S220. If the preset analysis type is an association analysis type, obtain a plurality of association features to be analyzed corresponding to the association analysis type, and determine association feature values ​​to be analyzed corresponding to the association features to be analyzed in the interface data and / or the loan order data.

[0068] Specifically, if the preset analysis type is an association analysis type, it is necessary to obtain multiple association features to be analyzed corresponding to the association analysis type, and the association features to be analyzed may be pre-configured. The values ​​corresponding to the association features to be analyzed may be searched in the interface data and / or the loan order data, that is, the association feature values ​​to be analyzed may be obtained.

[0069] S230 , combining any two of the to-be-analyzed associated features to obtain a candidate feature combination, and determining the support and confidence of the candidate feature combination based on the to-be-analyzed associated feature values.

[0070] Among them, support indicates the frequency of two features appearing at the same time, while confidence indicates the probability of one feature appearing when the other feature also appears.

[0071] Specifically, any two associated features to be analyzed are combined to form a candidate feature combination. For each candidate feature combination, its support and confidence can be calculated based on the associated feature value to be analyzed.

[0072] S240: Determine the sponsor screening rule based on the candidate feature combination that meets the preset support and preset confidence.

[0073] Specifically, according to preset support and confidence thresholds, qualified candidate feature combinations can be screened out, and the screened feature combinations can be used as the capital screening rules.

[0074] For example, when the preset analysis type is the association analysis type, the obtained capital screening rule may be:

[0075] 1. When the industry of A’s funding party is A, the occupation cannot be B

[0076] 2. Funding party A has overdue loans and cannot push funding party B

[0077] 3. Funding party A has a loan repayment and cannot push funding party B

[0078] 4. If the same user's loan from funding party A is overdue, he cannot push funding party A again

[0079] 5. The same user who borrows money from funding party A cannot push funding party A again.

[0080] 6. Within B days after the credit of funding party A fails, the credit of funding party A cannot be pushed.

[0081] 7. Funding party A fails to release the loan within B days, and cannot push funding party A

[0082] 8. If the credit of funding party A fails within C days, the credit of funding party B cannot be pushed.

[0083] 9. Funding party A fails to release the loan within C days, and cannot push it to funding party B

[0084] 10. After the credit approval of funding party A fails, the loan application is pushed to funding party A again after B times of application.

[0085] 11. After the A funding party fails to release the loan, it sends the B loan application to the A funding party again.

[0086] 12. After the credit approval of funding party A fails, the loan application is pushed to funding party C again after B times of application.

[0087] 13. After the A funding party fails to release the loan, it sends the loan application to the C funding party again after B times of loan application.

[0088] 14. Funder A has a credit record and cannot push to Funder B

[0089] 15. Funding party A has a loan record, so it cannot be pushed to funding party B

[0090] S250: Acquire initial screening rules, and update the initial screening rules based on the capital screening rules to obtain target screening rules.

[0091] Specifically, by obtaining the funding party's interface data in real time through the above process, the changes of the funding party can be dynamically monitored to form parameter rules. At the same time, the funding party's interface data can also be combined with the loan order data to form association rules. Different strategy sets are formed for different funding parties and applied to target screening rules to improve the push success rate of the funding party.

[0092] S260: Display the target screening rule based on the expert system, receive an editing operation for the target screening rule, and update the target screening rule based on the editing operation.

[0093] Specifically, the expert system can provide a user interaction interface to display the target screening rules, through which the expert can directly view, edit and approve the target screening rules. The expert can review the target screening rules and then use the approved target screening rules as the final rules.

[0094] It should also be noted that in order to make the target screening rules easier to pass the review, a knowledge base can be established for the target screening rules before and after the update. The reasoning process can be optimized based on the established knowledge base in the subsequent reasoning process of determining the capital screening rules.

[0095] S270: Determine a target sponsor that matches the loan application from the candidate sponsors based on the updated target screening rule.

[0096] In the embodiment of the present invention, after determining the target investor that matches the loan application among the candidate investors according to the target screening rules, the method further includes: obtaining the actual approval result of the target investor for the loan application; and revising the target screening rules in real time based on the actual approval result and the loan application.

[0097] Specifically, after confirming that the loan application has been submitted to the target investor, the actual approval result of the target investor for the loan application can be obtained. The actual approval result can be approval, rejection, or an indication of the need for further review. Furthermore, the actual approval result can be analyzed to fine-tune the target screening rules in a timely manner. For example, if the loan application is often rejected by a certain investor, it means that the target screening rules of the investor are not accurate enough, and the target screening rules of the investor can be adjusted.

[0098] The technical solution of the embodiment of the present invention, when the preset analysis type is the association analysis type, obtains multiple association features to be analyzed corresponding to the association analysis type, and determines the association feature values ​​to be analyzed corresponding to the association features to be analyzed in the interface data and / or the loan order data. Then, any two of the association features to be analyzed are combined to obtain a candidate feature combination, and the support and confidence of the candidate feature combination are determined based on the association feature values ​​to be analyzed. Furthermore, the investor screening rules are determined based on the candidate feature combinations that meet the preset support and preset confidence; and the target investor that matches the loan application is determined among the candidate investors according to the target screening rules. The technical solution of the present invention can realize the determination of different types of rules, improve the comprehensiveness of the target screening rules, and can also edit, review and update the target screening rules, dynamically update the funder pre-screening rules, and further improve the effectiveness and flexibility of the target screening rules.

[0099] Embodiment 3

[0100] Figure 3 This is a schematic diagram of the structure of a funding party determination device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device comprises:

[0101] The data acquisition module 310 is used to acquire the interface data and loan order data of the candidate funder when receiving the loan application;

[0102] A screening rule determination module 320, for determining a funding screening rule based on the interface data and the loan order data;

[0103] A screening rule updating module 330 is used to obtain an initial screening rule, and update the initial screening rule based on the capital screening rule to obtain a target screening rule;

[0104] The target funder determination module 340 is used to determine the target funder matching the loan application according to the target screening rule.

[0105] The technical solution of the embodiment of the present invention includes: upon receiving a loan application, obtaining the interface data and loan form data of the candidate investor; determining the investor screening rules based on the interface data and the loan form data; obtaining the initial screening rules, and updating the initial screening rules based on the investor screening rules to obtain the target screening rules; and determining the target investor among the candidate investors that matches the loan application according to the target screening rules. The technical solution of the present invention obtains the investor screening rules by analyzing the interface data and the loan form data, and then updates the initial screening rules to obtain the target screening rules, so as to determine the target investor based on the target screening rules, thereby solving the problem that the existing investor screening rule modification method cannot quickly respond to changes in the funding party, and realizes the dynamic update of the funding party pre-screening rules, improves the funding party's push efficiency, and improves the accuracy, automation, and digitization of loan application processing.

[0106] Optionally, the data acquisition module 310 includes:

[0107] An interface data center, used to collect the interface data returned by the data interface of the capital party;

[0108] The interface data includes at least one of a credit record and a loan record.

[0109] Optionally, the screening rule determination module 320 includes:

[0110] The interface data analysis center is used to analyze the interface data and the loan order data according to a preset analysis type to obtain the capital screening rules;

[0111] The preset analysis type includes at least one of a parameter analysis type and an association analysis type.

[0112] Optionally, if the preset analysis type is a parameter analysis type, the screening rule determination module 320 is specifically used to:

[0113] Obtain the features to be analyzed and the expressions to be used corresponding to the parameter analysis type;

[0114] Determining a feature value to be analyzed corresponding to the feature to be analyzed in the interface data and / or the loan order data;

[0115] Inputting the feature to be analyzed, the feature value to be analyzed and the expression to be used into a large model, and obtaining the capital screening rule based on the large model by inference;

[0116] The capital screening rules include the feature to be analyzed, the target expression of the feature to be analyzed, and the target feature value corresponding to the feature to be analyzed.

[0117] Optionally, if the preset analysis type is an association analysis type, the screening rule determination module 320 is specifically used to:

[0118] Acquire a plurality of to-be-analyzed association features corresponding to the association analysis type, and determine to-be-analyzed association feature values ​​corresponding to the to-be-analyzed association features in the interface data and / or the loan order data;

[0119] Combining any two of the to-be-analyzed associated features to obtain a candidate feature combination, and determining the support and confidence of the candidate feature combination based on the to-be-analyzed associated feature values;

[0120] The investor screening rule is determined based on a candidate feature combination that meets a preset support level and a preset confidence level.

[0121] Optionally, the target investor determination module 340 includes:

[0122] An expert system, configured to display the target screening rule based on an expert system, receive an editing operation for the target screening rule, and update the target screening rule based on the editing operation;

[0123] A target sponsor matching the loan application is determined from the candidate sponsors based on the updated target screening rule.

[0124] Optionally, the device further includes an updating module, configured to:

[0125] After determining the target investor matching the loan application among the candidate investors according to the target screening rules, obtaining the actual approval result of the target investor for the loan application; and modifying the target screening rules in real time based on the actual approval result and the loan application.

[0126] The investor determination device provided in the embodiment of the present invention can execute the investor determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0127] Embodiment 4

[0128] Figure 4 A schematic diagram of the structure of an electronic device provided for Embodiment 4 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0129] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0130] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0131] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for determining the capital side.

[0132] In some embodiments, the method for determining the capital provider may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for determining the capital provider described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method for determining the capital provider in any other appropriate manner (e.g., by means of firmware).

[0133] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0134] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0135] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0136] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0137] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0138] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0139] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0140] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining an investor, characterized in that: include: When receiving a loan application, obtain the candidate investor's interface data and loan order data; Determine a funder screening rule based on the interface data and the loan order data; Acquire initial screening rules, and update the initial screening rules based on the investor screening rules to obtain target screening rules; A target investor matching the loan application is determined among the candidate investors according to a target screening rule.

2. The method according to claim 1, characterized in that The interface data for obtaining candidate investors includes: Collecting the interface data returned by the data interface of the investor through the interface data center; The interface data includes at least one of a credit record and a loan record.

3. The method according to claim 1, characterized in that The determining of the funder screening rules based on the interface data and the loan order data includes: According to the preset analysis type, the interface data and the loan order data are analyzed by the interface data analysis center to obtain the capital screening rules; The preset analysis type includes at least one of a parameter analysis type and an association analysis type.

4. The method according to claim 3, characterized in that If the preset analysis type is a parameter analysis type, the interface data and the loan order data are analyzed by the interface data analysis center to obtain the capital screening rules, including: Obtain the features to be analyzed and the expressions to be used corresponding to the parameter analysis type; Determining a feature value to be analyzed corresponding to the feature to be analyzed in the interface data and / or the loan order data; Inputting the feature to be analyzed, the feature value to be analyzed and the expression to be used into a large model, and obtaining the capital screening rule based on the large model by inference; The capital screening rules include the feature to be analyzed, the target expression of the feature to be analyzed, and the target feature value corresponding to the feature to be analyzed.

5. The method according to claim 3, characterized in that: If the preset analysis type is an associated analysis type, the interface data and the loan order data are analyzed by the interface data analysis center to obtain the capital screening rules, including: Acquire a plurality of to-be-analyzed association features corresponding to the association analysis type, and determine to-be-analyzed association feature values ​​corresponding to the to-be-analyzed association features in the interface data and / or the loan order data; Combining any two of the to-be-analyzed associated features to obtain a candidate feature combination, and determining the support and confidence of the candidate feature combination based on the to-be-analyzed associated feature values; The investor screening rule is determined based on a candidate feature combination that meets a preset support level and a preset confidence level.

6. The method according to claim 1, characterized in that The step of determining a target investor matching the loan application from among the candidate investors according to a target screening rule includes: Displaying the target screening rule based on an expert system, receiving an editing operation on the target screening rule, and updating the target screening rule based on the editing operation; A target sponsor matching the loan application is determined from the candidate sponsors based on the updated target screening rule.

7. The method according to claim 1, characterized in that After determining the target investor matching the loan application among the candidate investors according to the target screening rule, the method further includes: Obtaining the actual approval result of the target investor for the loan application; The target screening rules are modified in real time based on the actual approval result and the loan application.

8. A device for determining an investor, characterized in that: include: The data acquisition module is used to obtain the interface data and loan order data of the candidate funder when receiving the loan application; A screening rule determination module, used to determine the funder screening rule based on the interface data and the loan order data; A screening rule updating module, used to obtain an initial screening rule, and update the initial screening rule based on the investor screening rule to obtain a target screening rule; The target funder determination module is used to determine the target funder matching the loan application according to the target screening rules.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the method for determining the sponsor according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the capital provider according to any one of claims 1 to 7 when executed.

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