CN113516548A - Financial borrowing and lending method and system based on block chain - Google Patents
Financial borrowing and lending method and system based on block chain Download PDFInfo
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Abstract
The invention discloses a block chain-based financial borrowing and lending method and a block chain-based financial borrowing and lending system, wherein first application information is obtained through the financial borrowing and lending system; performing identity verification on the first user; when the verification is correct, obtaining a first application amount; constructing a fund traffic data set according to the user data; obtaining a first stability assessment result from the fund transaction data set; obtaining a second user with the closest fund exchange with the first user, and obtaining first loan history information of the second user; inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result; performing risk assessment on a first application amount of a first user to obtain a first risk assessment result set; and storing the first risk assessment result set, and determining whether to loan or not according to the risk assessment result set. The technical problems that in the prior art, risk assessment of financial loan users is not accurate enough and information safety of the loan users cannot be effectively guaranteed are solved.
Description
Technical Field
The invention relates to the field of financial loan correlation, in particular to a block chain-based financial loan method and system.
Background
Financial lending is the act of a user lending money to a bank, which may also be called bank loan. The financial loan institutions mainly include domestic banks, foreign banks, investment banks, savings and loan associations, credit agencies, and other financial companies. With the development of society, users who make financial debits for various purposes have emerged.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
the technical problems that risk assessment of financial loan users is not accurate enough and information safety of the loan users cannot be effectively guaranteed exist in the prior art.
Disclosure of Invention
The financial loan method and the system based on the block chain solve the technical problems that in the prior art, risk assessment of financial loan users is not accurate enough and information safety of the loan users cannot be effectively guaranteed, and achieve the technical effects of more accurate assessment of the financial loan users and guarantee of user information safety.
In view of the foregoing, embodiments of the present application provide a block chain-based financial loan method and system.
In a first aspect, the present application further provides a method for block chain based financial lending, the method comprising: obtaining first application information of a first user through the financial loan system; according to the first application information, identity verification is carried out on the first user; when the identity of the first user is verified to be correct, obtaining a first application amount according to the first application information; obtaining, by the financial lending system, user data for a financial transaction with the first user; constructing a fund traffic data set according to the user data; evaluating the stability of the first user according to the fund traffic data set to obtain a first stability evaluation result; obtaining a second user with the closest fund traffic with the first user through the fund traffic data set, and obtaining first loan history information of the second user; inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result; performing risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result to obtain a first risk assessment result set; and storing the first risk assessment result set based on a block chain network, and determining whether to debit or credit according to the risk assessment result set.
In another aspect, the present application further provides a blockchain-based financial loan system, the system comprising: a first obtaining unit, configured to obtain first application information of a first user through the financial loan system; the first verification unit is used for verifying the identity of the first user according to the first application information; the second obtaining unit is used for obtaining a first application quota according to the first application information after the identity of the first user is verified to be correct; a third obtaining unit for obtaining user data of the financial transaction of the first user through the financial lending system; a first construction unit for constructing a fund traffic data set from the user data; a fourth obtaining unit, configured to evaluate the stability of the first user according to the fund traffic data set, and obtain a first stability evaluation result; a fifth obtaining unit, configured to obtain, through the fund traffic data set, a second user most closely transacted with the first user, and obtain first loan history information of the second user; the first input unit is used for inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result; a sixth obtaining unit, configured to perform risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result, so as to obtain a first risk assessment result set; a first determining unit, configured to store the first risk assessment result set based on a block chain network, and determine whether to credit or not according to the risk assessment result set.
In a third aspect, the present invention provides a blockchain-based financial lending system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the identity of the first user is verified according to application information of the first user, the first application amount of the first user is obtained after verification is carried out without error, data of a fund transaction user of the first user is obtained according to the financial loan system, a fund transaction data set is constructed according to user data, the stability of the first user is evaluated through the fund transaction data set, the stability evaluation result of the first user is obtained, a second user closest to the first user is obtained through the fund transaction data set, first loan history information of the second user is obtained, the first loan history information of the second user is input into a first credit evaluation model, a first credit evaluation result of the second user is obtained according to the first credit evaluation model, and the first application amount of the first user is subjected to the first credit evaluation result and the first stability evaluation result And performing risk assessment to obtain a first risk assessment result set, storing the first risk assessment result set on the basis of a block chain network, and determining whether to perform loan according to the risk assessment result set, so that the safety of the risk assessment result of the first user is ensured, and the technical effect of more comprehensively and accurately assessing the risk of the financial loan of the first user is achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
FIG. 1 is a schematic flow chart illustrating a method for block chain based financial loan in accordance with an embodiment of the present invention;
FIG. 2 is a block chain-based financial loan method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a first verifying unit 12, a second obtaining unit 13, a third obtaining unit 14, a first constructing unit 15, a fourth obtaining unit 16, a fifth obtaining unit 17, a first input unit 18, a sixth obtaining unit 19, a first determining unit 20, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 305.
Detailed Description
The financial loan method and the system based on the block chain solve the technical problems that in the prior art, risk assessment of financial loan users is not accurate enough and information safety of the loan users cannot be effectively guaranteed, and achieve the technical effects of more accurate assessment of the financial loan users and guarantee of user information safety. Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
Financial lending is the act of a user lending money to a bank, which may also be called bank loan. The financial loan institutions mainly include domestic banks, foreign banks, investment banks, savings and loan associations, credit agencies, and other financial companies. With the development of society, users who make financial debits for various purposes have emerged. However, the technical problems that the risk assessment of the financial loan users is not accurate enough and the information security of the loan users cannot be effectively guaranteed exist in the prior art.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides a financial loan method based on a block chain, which comprises the following steps: obtaining first application information of a first user through the financial loan system; according to the first application information, identity verification is carried out on the first user; when the identity of the first user is verified to be correct, obtaining a first application amount according to the first application information; obtaining, by the financial lending system, user data for a financial transaction with the first user; constructing a fund traffic data set according to the user data; evaluating the stability of the first user according to the fund traffic data set to obtain a first stability evaluation result; obtaining a second user with the closest fund traffic with the first user through the fund traffic data set, and obtaining first loan history information of the second user; inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result; performing risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result to obtain a first risk assessment result set; and storing the first risk assessment result set based on a block chain network, and determining whether to debit or credit according to the risk assessment result set.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides a block chain-based financial loan method, where the method includes:
step S100: obtaining first application information of a first user through the financial loan system;
specifically, the finance system of lending is based on the system for financial loan service that internet finance platform built, the system includes at least obtains relevant borrower's information through the internet, carries out the function handled to the information, first user is for applying for the user of finance loan, through the finance system of lending obtains first user's the first application information through the platform of applying for finance loan.
Step S200: according to the first application information, identity verification is carried out on the first user;
specifically, the identity of the first user is authenticated according to personal information of the first user in first application information of the financial loan platform, further, the authentication process may include authenticating the identity of the first user through a camera device connected to the financial loan system, further, the authentication may further include fingerprint collection and identification of the first user, and the authentication may be performed according to the first application information to determine whether the identity of the first user is consistent with the identity information filled in by the application information.
Step S300: when the identity of the first user is verified to be correct, obtaining a first application amount according to the first application information;
specifically, after the identity authentication of the first user is correct, the first application information filled by the first user is used to obtain the application amount information of the first user.
Step S400: obtaining, by the financial lending system, user data for a financial transaction with the first user;
step S500: constructing a fund traffic data set according to the user data;
specifically, the financial lending system obtains the current data of the first user, that is, the fund current information of the first user is obtained under the condition that the first user permits, the fund current information includes but is not limited to the loan of fund and the returning of the user with the first user, the number of borrowing and the amount information, and a fund current data set of the first user is constructed according to the current fund data, and the fund current data set includes the fund and the user information.
Step S600: evaluating the stability of the first user according to the fund traffic data set to obtain a first stability evaluation result;
specifically, the obtaining of the stability assessment result of the first user according to the fund flow data set refers to assessing the stability of the first user according to the fund flow condition of the first user and the fund flow of the first user to the fund flow of the first user, that is, assessing the stability of the first user according to the borrowing time, the appointed repayment time and the actual repayment time of the first user and the fund flow to the fund flow of the first user.
Further, the evaluating the stability of the first user according to the fund traffic data set to obtain a first stability evaluation result, in step S600 of this embodiment of the present application, further includes:
step S610: obtaining a monthly average debit and credit amount of the first user according to the fund traffic data set;
step S620: obtaining the monthly payment amount of the first user according to the fund transaction data set;
step S630: according to the formula
Performing a stability assessment on the first user, wherein S represents a stability assessment result of the first user, m is m months of the assessment of the first user,
the amount of money is debited for each month,
the monthly payment amount;
step S640: a first stability assessment result is obtained.
Specifically, a monthly average loan amount of the first user is obtained through the fund traffic data set, wherein the monthly average loan amount is a ratio of a total amount of borrowed money to a total number of borrowed persons of the first user within one month, the monthly average repayment amount is a ratio of a total repayment amount of the first user within the same month as the first user and the total number of repayment, the first user is evaluated for a period of m months, wherein the m months are at least 6 months, and the method comprises the steps of according to a formula
Performing a stability assessment on the first userS represents the stability assessment result of the first user, m is m months of the assessment of the first user,
the amount of money is debited for each month,
and obtaining the S value for the monthly payment amount, wherein the S value is a first stability evaluation result of the first user.
Step S700: obtaining a second user with the closest fund traffic with the first user through the fund traffic data set, and obtaining first loan history information of the second user;
specifically, according to the fund traffic data set, the number of times of the user making fund traffic with the first user and the fund amount per traffic are analyzed, and a second user having the closest fund traffic with the first user in the fund traffic data set is obtained. Further, the calculation of the degree of closeness of the fund flow is not specifically performed here, and any result may be obtained by performing calculation analysis on the fund flow with the first user according to a certain rule, and on the premise that the second user is allowed, history information of the loan of the second user is obtained through the financial loan system based on the internet, where the history information of the loan includes information of the second user on each platform, and the loan information includes, but is not limited to, the amount of the loan, the repayment date, and the like.
Step S800: inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result;
step S900: performing risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result to obtain a first risk assessment result set;
specifically, the first loan history information of the second user is input into a first credit evaluation model, credit level evaluation is performed on the second user according to the loan amount, repayment time and appointed repayment time of the second user, a first credit evaluation result of the second user is obtained, risk level evaluation is performed on the loan behavior of the first application amount of the first user according to the stability evaluation result of the first user and the first credit evaluation result of the second user, a first risk level evaluation result is obtained, the stability evaluation result and the first credit level evaluation result have different weights for the risk level evaluation of the first user, and therefore loan risk of the first application amount of the first user can be evaluated more accurately. Further, loan risk assessment grades of other users are obtained, namely a second risk assessment result, a third risk assessment result and an Nth risk assessment result, and a first risk assessment result set is obtained according to the assessment results.
Step S1000: and storing the first risk assessment result set based on a block chain network, and determining whether to debit or credit according to the risk assessment result set.
Specifically, the risk level evaluation results in the first risk evaluation result set are stored and encrypted based on a block chain manner, so that the safety of the loan risk level evaluation results is guaranteed, and then the safety of loan is guaranteed, and then whether loan is performed or not is determined through the risk evaluation result set, so that the technical effect of more accurately evaluating the loan risk of the user is achieved.
Further, in the step S700 of obtaining a second user with the closest fund transaction with the first user through the fund transaction data set, and obtaining first loan history information of the second user, the method further includes:
step S710: obtaining information of single-time currency amount and times of currency between all users and the first user in the statistic time of the fund currency data set according to the fund currency data set;
step S720: obtaining a set of single currency amounts and a first number of times of currency of the same user and the first user in a first year;
step S730: according to
Calculating the contact user density of the first user, wherein c represents the calculation year, a1Representing the first transaction amount, a2Representing the amount of the second transaction, abRepresenting the amount of the current b, wherein b is the number of times of current in one year, and K represents the density of current;
step S740: and obtaining a second user closest to the first user according to the contact intimacy degree.
Specifically, according to the fund transaction data set, counting the single transaction amount and the transaction times information of all the users and the first user within the time according to the fund transaction data set, wherein the single transaction amount and the transaction times refer to the transaction times information and the amount information of each transaction of the first user and the same user within one year, and according to the fund transaction data set
Calculating the contact user density of the first user, wherein c represents the calculation year, a1Representing the first transaction amount, a2Representing the amount of the second transaction, abRepresenting the amount of the b-th transaction, b being the number of times of the transaction in one year, and K representing the contact density, obtaining the K value of the user with the first user in the transaction according to the formula, and comparing the K value to obtain the user with the maximum K value, namely the second user with the closest contact with the first user.
Further, step S800 in the embodiment of the present application further includes:
step S810: obtaining basic information of the second user;
step S820: obtaining a first historical loan amount of the second user according to the basic information;
step S830: obtaining a first repayment time of the second user according to the first historical loan amount;
step S840: judging whether the first repayment time is within the agreed repayment time of the second user and a lending institution;
step S850: when the first repayment time is not within the agreed repayment time of the second user and the lending institution, obtaining a first influence factor;
step S860: and obtaining the first credit evaluation result according to the first influence factor and the first historical loan amount.
Specifically, the method includes the steps of obtaining basic information of a second user on the premise that the second user permits, obtaining a first historical loan amount of the first user according to the basic information, obtaining a first repayment time of the first historical loan amount of the first user, obtaining an agreed repayment time between the second user and a lending mechanism, judging whether the first repayment time is within the agreed repayment time range, obtaining a first influence factor when the first repayment time is not within the agreed repayment time between the second user and the lending mechanism, evaluating credit of the second user according to the first influence factor and the first historical loan amount, and performing the above evaluation according to other historical loan information of the second user to obtain a first credit evaluation result.
Further, the obtaining the first credit evaluation result according to the first influencing factor and the first historical loan amount in step S860 of this embodiment of the present application further includes:
step S861: inputting the first influencing factor and the first historical loan amount into a first credit assessment model, wherein the first credit assessment model is obtained by training multiple sets of training data, and each set of the training data comprises: the first influencing factor, the first historical debit amount, and identification information identifying the first credit evaluation result;
step S862: a first output result is obtained, the first output result comprising a first credit evaluation result.
Specifically, the first credit evaluation model is a Neural network model in machine learning, and a Neural Network (NN) is a complex Neural network system formed by widely interconnecting a large number of simple processing units (called neurons), which reflects many basic features of human brain functions, and is a highly complex nonlinear dynamical learning system. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. And inputting the first influencing factor and the first historical loan amount into a neural network model through training of a large amount of training data, and then obtaining the first credit evaluation result.
Furthermore, the training process further includes a supervised learning process, each set of supervised data includes the first influence factor, the first historical loan amount and identification information identifying the first credit evaluation result, the first influence factor and the first historical loan amount are input into a neural network model, the neural network model performs continuous self-correction and adjustment according to the identification information identifying the first credit evaluation result, and the set of supervised learning is ended until the obtained output result is consistent with the identification information, and the next set of supervised learning is performed; and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, finishing the supervised learning process. Through supervised learning of the neural network model, the neural network model can process the input information more accurately, so that a more accurate first credit evaluation result is obtained, and a foundation is laid for more accurate risk evaluation tamping in the follow-up process.
Further, the performing risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result to obtain a first risk assessment result set, where step S900 in this embodiment of the present application further includes:
step S910: obtaining the application limit grade based on the big data;
step S920: obtaining a first application quota level where the first application quota is located according to the application quota level;
step S930: obtaining a first predetermined risk level threshold;
step S940: obtaining a first risk level of the first user under the first application amount level according to the first stability evaluation result and the first credit evaluation result;
step S950: determining whether the first risk level satisfies the first predetermined risk level threshold
Step S960: and obtaining a first risk assessment result set according to the judgment result.
Specifically, the application quota grades are divided for different application quota based on big data, the application quota grade where the first application quota is located is obtained according to the divided application quota grades, the first application quota grade is recorded as a first application quota grade, a first preset risk grade is obtained through a big data pair, wherein the first predetermined risk level threshold is a risk controllable threshold for risk levels within a certain threshold obtained based on big data calculations, obtaining a first risk level of the first user under the first application limit level according to the first stability evaluation result and the first credit evaluation result, judging whether the first risk level meets the first preset risk level threshold value or not, and obtaining the first risk assessment result set according to the judgment result, and judging whether to carry out financial loan on the user according to the risk level assessment result set.
Further, the storing the first risk assessment result set based on a block chain network, and determining whether to loan or not according to the risk assessment result set, in step S1000 according to the embodiment of the present application, further includes:
step S1010: obtaining a first risk evaluation result and a second risk evaluation result in the first risk evaluation result set until an Nth risk evaluation result, wherein N is a natural number greater than 1;
step S1020: inputting the first risk evaluation result into a first encryption model to obtain a first verification code;
step S1030: inputting the second risk assessment result and the first verification code into the first encryption model to obtain a second verification code;
step S1040: inputting the Nth risk evaluation result and the Nth-1 verification code into the first encryption model to obtain an Nth verification code;
step S1050: and respectively storing the risk evaluation result and the verification code.
In particular, the blockchain technique, also referred to as a distributed ledger technique, is an emerging technique in which several computing devices participate in "accounting" together, and maintain a complete distributed database together. The blockchain technology has been widely used in many fields due to its characteristics of decentralization, transparency, participation of each computing device in database records, and rapid data synchronization between computing devices. Inputting the first risk evaluation result into a first encryption model to obtain a first verification code, wherein the first verification code corresponds to the first risk evaluation result one by one; generating a second verification code according to the second risk assessment result and the first verification code, wherein the second verification code corresponds to the second risk assessment result one to one; and so on, generating an nth verification code according to the nth risk assessment result and an nth-1 verification code, wherein N is a natural number greater than 1, the first risk assessment result and the first verification code are stored on one device as a first block, the second risk assessment result and the second verification code are stored on one device as a second block, the nth risk assessment result and the nth verification code are stored on one device as an nth block, when the risk assessment result needs to be called, after receiving data stored by a previous node, each subsequent node checks and stores the data through a common identification mechanism, and each storage unit is connected in series through a hash function, so that training data is not easy to lose and damage, and the risk assessment result is encrypted through logic of a block chain, the safety of the risk assessment result is ensured.
In summary, the financial loan method and system based on the block chain provided by the embodiment of the present application have the following technical effects:
1. the identity of the first user is verified according to application information of the first user, a first application amount of the first user is obtained after verification is carried out without error, data of a fund transaction user of the first user is obtained according to the financial loan system, a fund transaction data set is constructed according to user data, a stability evaluation result of the first user is obtained through the stability evaluation of the fund transaction data set on the first user, a second user closest to the first user is obtained through the fund transaction data set, first loan history information of the second user is obtained, the first loan history information of the second user is input into a first credit evaluation model, a first credit evaluation result of the second user is obtained according to the first credit evaluation model, and the first application amount of the first user is verified according to the first credit evaluation result and the first stability evaluation result And carrying out risk evaluation on the quota to obtain a first risk evaluation result set, storing the first risk evaluation result set on the basis of a block chain network, and determining whether to carry out loan according to the risk evaluation result set, so that the safety of the risk evaluation result of the first user is ensured, and the technical effect of more comprehensively and accurately evaluating the risk of the financial loan of the first user is achieved.
2. The method for carrying out storage based on the block chain network is adopted, so that the safety of the loan risk level evaluation result is ensured, the loan safety is ensured, and then whether the loan is carried out or not is determined through the risk evaluation result set, so that the technical effect of more accurate evaluation on the loan risk of the user is realized.
3. Due to the adoption of the mode of supervising and learning the neural network model, the input information processed by the neural network model is more accurate, so that a more accurate first credit evaluation result is obtained, and a foundation is tamped for more accurate risk evaluation in the follow-up process.
Example two
Based on the same inventive concept as the block chain-based financial loan method in the previous embodiment, the present invention further provides a block chain-based financial loan system, as shown in fig. 2, the system comprising:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first application information of a first user through the financial loan system;
a first verification unit 12, wherein the first verification unit 12 is configured to verify the identity of the first user according to the first application information;
a second obtaining unit 13, where the second obtaining unit 13 is configured to obtain a first application quota according to the first application information after the identity of the first user is verified to be correct;
a third obtaining unit 14, wherein the third obtaining unit 14 is configured to obtain user data of the financial transaction of the first user through the financial lending system;
a first construction unit 15, said first construction unit 15 being adapted to construct a fund traffic data set from said user data;
a fourth obtaining unit 16, where the fourth obtaining unit 16 is configured to evaluate the stability of the first user according to the fund traffic data set, and obtain a first stability evaluation result;
a fifth obtaining unit 17, where the fifth obtaining unit 17 is configured to obtain, through the fund traffic data set, a second user who has the closest fund traffic to the first user, and obtain first loan history information of the second user;
a first input unit 18, where the first input unit 18 is configured to input the first loan history information into a first credit evaluation model to obtain a first credit evaluation result;
a sixth obtaining unit 19, where the sixth obtaining unit 19 is configured to perform risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result, and obtain a first risk assessment result set;
a first determining unit 20, where the first determining unit 20 is configured to store the first risk assessment result set based on a block chain network, and determine whether to credit or not according to the risk assessment result set.
A seventh obtaining unit, configured to obtain a monthly average loan amount of the first user according to the fund traffic data set;
an eighth obtaining unit, configured to obtain a monthly payment amount of the first user according to the fund traffic data set;
a first evaluation unit for evaluating the first evaluation unit according to a formula
Performing a stability assessment on the first user, wherein S represents a stability assessment result of the first user, m is m months of the assessment of the first user,
the amount of money is debited for each month,
the monthly payment amount;
a ninth obtaining unit for obtaining a first stability evaluation result.
Further, the system further comprises:
a tenth obtaining unit, configured to obtain, according to the fund traffic data set, information of a single traffic amount and traffic times of all users and the first user within a statistical time of the fund traffic data set;
an eleventh obtaining unit, configured to obtain a set of single currency amounts and a first number of times of currency between the same user and the first user in a first year;
a twelfth obtaining unit for obtaining the data according to
Calculating the contact user density of the first user, wherein c represents the calculation year, a1Representing the first transaction amount, a2Representing the amount of the second transaction, abRepresenting the amount of the current b, wherein b is the number of times of current in one year, and K represents the density of current;
a thirteenth obtaining unit, configured to obtain, according to the closeness of the round, a second user closest to the first user.
Further, the system further comprises:
a fourteenth obtaining unit, configured to obtain basic information of the second user;
a fifteenth obtaining unit, configured to obtain a first historical loan amount of the second user according to the basic information;
a sixteenth obtaining unit, configured to obtain a first repayment time of the second user according to the first historical loan amount;
the first judging unit is used for judging whether the first repayment time is within the appointed repayment time of the second user and the lending institution;
a seventeenth obtaining unit, configured to obtain a first influencing factor when the first repayment time is not within an agreed repayment time of the second user and a lending institution;
an eighteenth obtaining unit configured to obtain the first credit evaluation result according to the first influence factor and the first historical loan amount;
further, the system further comprises:
a second input unit, configured to input the first influence factor and the first historical loan amount into a first credit evaluation model, where the first credit evaluation model is obtained through training of multiple sets of training data, and each set of the training data includes: the first influencing factor, the first historical debit amount, and identification information identifying the first credit evaluation result;
a nineteenth obtaining unit to obtain a first output result, the first output result comprising a first credit evaluation result.
Further, the system further comprises:
a twentieth obtaining unit, configured to obtain the application quota level based on the big data;
a twenty-first obtaining unit, configured to obtain, according to the application quota level, a first application quota level where the first application quota is located;
a twenty-second obtaining unit for obtaining a first predetermined risk level threshold;
a twenty-third obtaining unit, configured to obtain, according to the first stability assessment result and the first credit assessment result, a first risk level of the first user under the first application quota level;
a second determination unit for determining whether the first risk level satisfies the first predetermined risk level threshold
A twenty-fourth obtaining unit, configured to obtain a first risk assessment result set according to the determination result.
Further, the system further comprises:
a twenty-fifth obtaining unit, configured to obtain a first risk assessment result and a second risk assessment result in the first risk assessment result set until an nth risk assessment result, where N is a natural number greater than 1;
a twenty-sixth obtaining unit, configured to input the first risk assessment result into a first encryption model, and obtain a first verification code;
a twenty-seventh obtaining unit, configured to input the second risk assessment result and the first verification code into the first encryption model, and obtain a second verification code;
a twenty-eighth obtaining unit, configured to input the nth risk assessment result and the nth-1 verification code into the first encryption model, and obtain an nth verification code;
the first storage unit is used for storing the risk assessment result and the verification code respectively.
While various modifications and embodiments of a chain-of-blocks-based financial loan method in the first embodiment of fig. 1 are also applicable to a chain-of-blocks-based financial loan system of this embodiment, it will be apparent to those skilled in the art from the foregoing detailed description of a chain-of-blocks-based financial loan method that a method of implementing a chain-of-blocks-based financial loan system of this embodiment is not described in detail herein for the sake of brevity.
Exemplary electronic device
The electronic device of the embodiment of the present application is described below with reference to fig. 3.
Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of a blockchain-based financial loan method as in the previous embodiment, the present invention further provides a blockchain-based financial loan system, on which a computer program is stored, which when executed by a processor implements the steps of any one of the above-described blockchain-based financial loan methods.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The embodiment of the invention provides a financial borrowing and lending method based on a block chain, which comprises the following steps: obtaining first application information of a first user through the financial loan system; according to the first application information, identity verification is carried out on the first user; when the identity of the first user is verified to be correct, obtaining a first application amount according to the first application information; obtaining, by the financial lending system, user data for a financial transaction with the first user; constructing a fund traffic data set according to the user data; evaluating the stability of the first user according to the fund traffic data set to obtain a first stability evaluation result; obtaining a second user with the closest fund traffic with the first user through the fund traffic data set, and obtaining first loan history information of the second user; inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result; performing risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result to obtain a first risk assessment result set; and storing the first risk assessment result set based on a block chain network, and determining whether to debit or credit according to the risk assessment result set. The technical problems that in the prior art, risk assessment of financial loan users is not accurate enough and information safety of the loan users cannot be effectively guaranteed are solved, and the technical effects of more accurately assessing the financial loan users and guaranteeing the information safety of the users are achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. A block chain based financial loan method, wherein the method is applied to a financial loan system, the method comprising:
obtaining first application information of a first user through the financial loan system;
according to the first application information, identity verification is carried out on the first user;
when the identity of the first user is verified to be correct, obtaining a first application amount according to the first application information;
obtaining, by the financial lending system, user data for a financial transaction with the first user;
constructing a fund traffic data set according to the user data;
evaluating the stability of the first user according to the fund traffic data set to obtain a first stability evaluation result;
obtaining a second user with the closest fund traffic with the first user through the fund traffic data set, and obtaining first loan history information of the second user;
inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result;
performing risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result to obtain a first risk assessment result set;
and storing the first risk assessment result set based on a block chain network, and determining whether to debit or credit according to the risk assessment result set.
2. The method of claim 1, wherein the evaluating stability of the first user from the set of funding transaction data obtains a first stability evaluation result, the method further comprising:
obtaining a monthly average debit and credit amount of the first user according to the fund traffic data set;
obtaining the monthly payment amount of the first user according to the fund transaction data set;
according to the formula
Performing a stability assessment on the first user, wherein S represents a stability assessment result of the first user, m is m months of the assessment of the first user,
the amount of money is debited for each month,
the monthly payment amount;
a first stability assessment result is obtained.
3. The method of claim 1, wherein the obtaining a second user most closely funded to the first user through the set of funding transaction data, obtaining first loan history information for the second user, the method further comprising:
obtaining information of single-time currency amount and times of currency between all users and the first user in the statistic time of the fund currency data set according to the fund currency data set;
obtaining a set of single currency amounts and a first number of times of currency of the same user and the first user in a first year;
according to
Calculating the contact user density of the first user, wherein c represents the calculation year, a1Representing the first transaction amount, a2Representing the amount of the second transaction, abRepresenting the amount of the current b, wherein b is the number of times of current in one year, and K represents the density of current;
and obtaining a second user closest to the first user according to the contact intimacy degree.
4. The method of claim 3, wherein the method further comprises:
obtaining basic information of the second user;
obtaining a first historical loan amount of the second user according to the basic information;
obtaining a first repayment time of the second user according to the first historical loan amount;
judging whether the first repayment time is within the agreed repayment time of the second user and a lending institution;
when the first repayment time is not within the agreed repayment time of the second user and the lending institution, obtaining a first influence factor;
and obtaining the first credit evaluation result according to the first influence factor and the first historical loan amount.
5. The method of claim 4, wherein said obtaining said first credit assessment result is based on said first influencing factor and said first historical debit amount, said method further comprising:
inputting the first influencing factor and the first historical loan amount into a first credit assessment model, wherein the first credit assessment model is obtained by training multiple sets of training data, and each set of the training data comprises: the first influencing factor, the first historical debit amount, and identification information identifying the first credit evaluation result;
a first output result is obtained, the first output result comprising a first credit evaluation result.
6. The method of claim 1, wherein a first application amount of the first user is risk-assessed according to the first stability assessment result and the first credit assessment result to obtain a first risk assessment result set, and the method further comprises:
obtaining the application limit grade based on the big data;
obtaining a first application quota level where the first application quota is located according to the application quota level;
obtaining a first predetermined risk level threshold;
obtaining a first risk level of the first user under the first application amount level according to the first stability evaluation result and the first credit evaluation result;
determining whether the first risk level meets the first predetermined risk level threshold;
and obtaining a first risk assessment result set according to the judgment result.
7. The method of claim 1, wherein the storing the first set of risk assessment results is based on a blockchain network, determining whether to credit based on the set of risk assessment results, the method further comprising:
obtaining a first risk evaluation result and a second risk evaluation result in the first risk evaluation result set until an Nth risk evaluation result, wherein N is a natural number greater than 1;
inputting the first risk evaluation result into a first encryption model to obtain a first verification code;
inputting the second risk assessment result and the first verification code into the first encryption model to obtain a second verification code;
inputting the Nth risk evaluation result and the Nth-1 verification code into the first encryption model to obtain an Nth verification code;
and respectively storing the risk evaluation result and the verification code.
8. A blockchain based financial lending system, wherein the system comprises:
a first obtaining unit, configured to obtain first application information of a first user through the financial loan system;
the first verification unit is used for verifying the identity of the first user according to the first application information;
the second obtaining unit is used for obtaining a first application quota according to the first application information after the identity of the first user is verified to be correct;
a third obtaining unit for obtaining user data of the financial transaction of the first user through the financial lending system;
a first construction unit for constructing a fund traffic data set from the user data;
a fourth obtaining unit, configured to evaluate the stability of the first user according to the fund traffic data set, and obtain a first stability evaluation result;
a fifth obtaining unit, configured to obtain, through the fund traffic data set, a second user most closely transacted with the first user, and obtain first loan history information of the second user;
the first input unit is used for inputting the first loan history information into a first credit evaluation model to obtain a first credit evaluation result;
a sixth obtaining unit, configured to perform risk assessment on the first application amount of the first user according to the first stability assessment result and the first credit assessment result, so as to obtain a first risk assessment result set;
a first determining unit, configured to store the first risk assessment result set based on a block chain network, and determine whether to credit or not according to the risk assessment result set.
9. A blockchain based financial lending system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method of any one of claims 1 to 7.
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