CN110807702A - Method, device, equipment and storage medium for managing information after loan - Google Patents
Method, device, equipment and storage medium for managing information after loan Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for managing post-loan information, wherein the method classifies and integrates received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-loan information sets corresponding to the post-loan enterprises; then generating enterprise event time axes corresponding to the credited enterprises by combining the corresponding occurrence time points and a preset event name list; and then calculating the probability of the risk event of each post-loan enterprise in a preset time period, and executing corresponding post-loan management operation on each post-loan enterprise according to the probability of the risk event of each post-loan enterprise. The method and the device predict the probability of the occurrence of the risk event of the post-credit enterprise within the preset time period after the occurrence of the event in the event time axis based on the preset event name list, so that the post-credit enterprise can be managed in time according to the probability, the post-credit management operation of the enterprise is simplified, and the management efficiency is improved.
Description
Technical Field
The present invention relates to the field of financial technology (Fintech), and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for managing post-loan information.
Background
With the development of computer technology, more and more technologies (big data, distributed, Blockchain, artificial intelligence, etc.) are applied to the financial field, and the traditional financial industry is gradually changing to financial technology (Fintech), but higher requirements are also put forward on the technologies due to the requirements of security and real-time performance of the financial industry. The business system of the bank needs to provide loan for enterprise legal persons for the turnover of enterprise liquidity funds. In order to ensure the repayment rate of the enterprise and reduce the bad account rate, the enterprise legal system needs to perform post-credit management, that is, enterprise information related to each enterprise in the network, such as enterprise bulletins, financing messages, administrative penalties, and officer bulletins, etc., is acquired. The conventional enterprise post-loan management is to manually determine whether the enterprise faces certain risks in the future or not according to relevant information of enterprises related to various large search engines, industry forums, microblogs or WeChat public accounts. Therefore, the management of the information after the enterprise loan in the prior art is not only complicated in operation but also low in management efficiency.
Disclosure of Invention
The invention mainly aims to provide a method, a device and equipment for managing post-loan information and a computer readable storage medium, and aims to solve the technical problems that the existing enterprise post-loan management is complex in operation and low in management efficiency.
In order to achieve the above object, the present invention provides a method for managing post-loan information, including the steps of:
classifying and integrating the received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-credit information sets corresponding to the post-credit enterprises;
generating an enterprise event time axis corresponding to each credited enterprise according to a preset event name list, enterprise event information in the enterprise credited information set and occurrence time points corresponding to the enterprise event information;
and calculating the probability of the risk event of each post-loan enterprise in a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-loan management operation on each post-loan enterprise according to the probability of the risk event of each post-loan enterprise.
Optionally, the step of generating an enterprise event timeline corresponding to each post-loan enterprise according to a preset event name list, the enterprise event information in the enterprise post-loan information set, and occurrence time points corresponding to the enterprise event information specifically includes:
matching an event title in the enterprise event information with a regular rule expression corresponding to a tertiary event in the event name list, and judging whether the enterprise event information hits the regular rule expression corresponding to the tertiary event;
if the enterprise event information hits the regular rule expression corresponding to the third-level event, combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit third-level event name and the occurrence time point corresponding to the enterprise time information to generate a triple event;
and generating an enterprise event time axis corresponding to each credited enterprise according to the triple event corresponding to each credited enterprise and the occurrence time point corresponding to the triple event.
Optionally, after the step of matching the event title in the enterprise event information with the regular rule expression corresponding to the third-level event in the event name list and judging whether the enterprise event information hits the regular rule expression corresponding to the third-level event, the method further includes:
and if the enterprise event information does not hit the regular rule expression corresponding to the third-level event, marking the enterprise event information as event information to be deleted, and deleting the event information to be deleted in the event set after the enterprise is credited.
Optionally, after the step of generating a triple event by combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit tertiary event name, and the occurrence time point corresponding to the enterprise time information if the enterprise event information hits the regular rule expression corresponding to the tertiary event, the method further includes:
judging whether an event to be merged exists in the triple events corresponding to the credited enterprises, wherein the event to be merged is two or more triple events with the same event title, and the occurrence time points corresponding to the two or more triple events belong to a preset time interval;
if the triple events corresponding to the credited enterprises have events to be combined, combining two or more triple events in the events to be combined into one triple event;
and acquiring the earliest time point from the occurrence time points corresponding to the two or more triple events, and taking the earliest time point as the occurrence time point corresponding to the combined triple event.
Optionally, the step of calculating, according to the event name list and the enterprise event timeline, a probability of occurrence of a risk event of each post-credit enterprise within a preset time period, and performing, according to the probability of occurrence of a risk event of each post-credit enterprise, a corresponding post-credit management operation on each post-credit enterprise specifically includes:
sequentially taking the enterprise event information in the enterprise event timeline as first event information, and sequentially taking the risk events in the event name list as second event information;
calculating the probability of the enterprise to which the enterprise event timeline belongs to generating second event information within the corresponding time after the first event information according to the preset event transition probability, and taking the probability as the probability of the enterprise to which the enterprise event timeline belongs to generating risk events;
and sequentially calculating the probability of the risk event of each post-credit enterprise, and executing corresponding post-credit management operation on each post-credit enterprise according to the probability of the risk event of each post-credit enterprise.
Optionally, before the step of calculating, according to the event name list and the enterprise event timeline, a probability of occurrence of a risk event of each post-credit enterprise within a preset time period, and according to the probability of occurrence of a risk event of each post-credit enterprise, performing corresponding post-credit management operation on each post-credit enterprise, the method further includes:
calculating the event transition probability among the events in the event name list according to a probability calculation formula, wherein the probability calculation formula is as follows:
P(B|A，t)＝NS/(NA+1), where P (B | a, t) is the probability of occurrence of event B within a time interval t after occurrence of event a, A, B is two events in the event name list, t is the time interval after occurrence of an event a, NANumber of triples associated with event A, NSIs the number of times event B occurs within a time interval t after occurrence of event a.
Optionally, before the step of calculating, according to the event name list and the enterprise event timeline, a probability of occurrence of a risk event of each post-credit enterprise within a preset time period, and according to the probability of occurrence of a risk event of each post-credit enterprise, performing corresponding post-credit management operation on each post-credit enterprise, the method further includes:
and when a risk event setting instruction is triggered by user operation, adding a risk event identifier to an event in the risk event setting instruction in the event name list so as to specify a risk event with risk in the event name list.
Optionally, the step of classifying and integrating the received enterprise related information according to enterprise names according to a preset enterprise name list to generate an enterprise post-credit information set corresponding to each post-credit enterprise specifically includes:
carrying out site prefix deletion operation and company suffix deletion operation on the enterprise names in the enterprise name list;
performing regular matching on the deleted enterprise name and information in a preset information base so as to determine to-be-processed enterprise event information corresponding to the enterprise name in the enterprise name list in the information base;
performing word segmentation on the enterprise information of the to-be-processed event to obtain word vectors to be processed corresponding to the enterprise information of the to-be-processed event, and adding the word vectors to be processed to obtain a first document vector;
performing word segmentation on target enterprise event information to obtain target word vectors corresponding to the target enterprise event information, and adding the target word vectors to obtain a second document vector;
calculating the cosine distance between the first document vector and the second document vector, and taking the enterprise event information to be processed as enterprise related information when the cosine distance is greater than a preset threshold value;
and classifying and integrating the enterprise related information according to the enterprise names to generate enterprise post-credit information sets corresponding to the post-credit enterprises.
In order to achieve the above object, the present invention provides a post-loan information management apparatus including:
the information classification module is used for classifying and integrating the received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-credit information sets corresponding to the post-credit enterprises;
the time axis generation module is used for generating enterprise event time axes corresponding to the enterprise after credit according to a preset event name list, the enterprise event information in the enterprise after credit information set and occurrence time points corresponding to the enterprise event information;
and the probability calculation module is used for calculating the probability of the risk event of each post-credit enterprise within a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-credit management operation on each post-credit enterprise according to the probability of the risk event of each post-credit enterprise.
Optionally, the time axis generating module specifically includes:
the event matching unit is used for matching an event title in the enterprise event information with a regular rule expression corresponding to a tertiary event in the event name list and judging whether the enterprise event information hits the regular rule expression corresponding to the tertiary event;
the event generating unit is used for combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit tertiary event name and the occurrence time point corresponding to the enterprise time information to generate a triple event if the enterprise event information hits the regular rule expression corresponding to the tertiary event;
and a time axis generating unit, configured to generate an enterprise event time axis corresponding to each credited enterprise according to the triple event corresponding to each credited enterprise and the occurrence time point corresponding to the triple event.
Optionally, the timeline generation module is further configured to:
and if the enterprise event information does not hit the regular rule expression corresponding to the third-level event, marking the enterprise event information as event information to be deleted, and deleting the event information to be deleted in the event set after the enterprise is credited.
Optionally, the timeline generating module further includes an event merging unit, where the event merging unit is configured to:
judging whether an event to be merged exists in the triple events corresponding to the credited enterprises, wherein the event to be merged is two or more triple events with the same event title, and the occurrence time points corresponding to the two or more triple events belong to a preset time interval;
if the triple events corresponding to the credited enterprises have events to be combined, combining two or more triple events in the events to be combined into one triple event;
and acquiring the earliest time point from the occurrence time points corresponding to the two or more triple events, and taking the earliest time point as the occurrence time point corresponding to the combined triple event.
Optionally, the probability calculation module specifically includes:
the event acquisition unit is used for sequentially taking the enterprise event information in the enterprise event timeline as first event information and sequentially taking the risk events in the event name list as second event information;
the first calculating unit is used for calculating the probability of second event information occurring in the corresponding time after the first event information of the enterprise to which the enterprise event timeline belongs according to a preset event transition probability, and the probability is used as the probability of risk events occurring in the enterprise to which the enterprise event timeline belongs;
and the second calculating unit is used for sequentially calculating the probability of the risk event of each credited enterprise and executing corresponding post-credit management operation on each credited enterprise according to the probability of the risk event of each credited enterprise.
Optionally, the probability calculation module is further specifically configured to:
calculating the event transition probability among the events in the event name list according to a probability calculation formula, wherein the probability calculation formula is as follows:
P(B|A，t)＝NS/(NA+1), where P (B | a, t) is the probability of occurrence of event B within a time interval t after occurrence of event a, A, B is two events in the event name list, t is the time interval after occurrence of an event a, NANumber of triples associated with event A, NSIs the number of times event B occurs within a time interval t after occurrence of event a.
Optionally, the information classification module specifically includes:
the information deleting unit is used for carrying out site prefix deleting operation and company suffix deleting operation on the enterprise names in the enterprise name list;
the information matching unit is used for performing regular matching on the deleted enterprise name and information in a preset information base so as to determine to-be-processed enterprise event information corresponding to the enterprise name in the enterprise name list in the information base;
the first word cutting unit is used for cutting words of the enterprise information of the to-be-processed event to obtain word vectors to be processed corresponding to the enterprise information of the to-be-processed event, and adding the word vectors to be processed to obtain a first document vector;
the second word segmentation unit is used for segmenting words of target enterprise event information to obtain target word vectors corresponding to the target enterprise event information, and adding the target word vectors to obtain a second document vector;
the vector calculation unit is used for calculating the cosine distance between the first document vector and the second document vector and taking the enterprise event information to be processed as enterprise related information when the cosine distance is greater than a preset threshold value;
and the information integration unit is used for classifying and integrating the enterprise related information according to the enterprise name to generate an enterprise post-credit information set corresponding to each post-credit enterprise.
In addition, to achieve the above object, the present invention provides a post-loan information management apparatus including: the system comprises a memory, a processor and a management program of the post-credit information, wherein the management program of the post-credit information is stored on the memory and can run on the processor, and when being executed by the processor, the management program of the post-credit information realizes the steps of the management method of the post-credit information.
In addition, to achieve the above object, the present invention further provides a computer-readable storage medium, in which a management program of post-loan information is stored, and the management program of post-loan information, when executed by a processor, implements the steps of the method for managing post-loan information as described above.
The invention provides a method for managing post-loan information, which classifies and integrates received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-loan information sets corresponding to various post-loan enterprises; generating an enterprise event time axis corresponding to each credited enterprise according to a preset event name list, enterprise event information in the enterprise credited information set and occurrence time points corresponding to the enterprise event information; and calculating the probability of the risk event of each post-loan enterprise in a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-loan management operation on each post-loan enterprise according to the probability of the risk event of each post-loan enterprise. Through the mode, the enterprise condition of the enterprise after the loan is determined based on the enterprise event time axis, the probability of the occurrence of the risk event of the enterprise in the preset time period after the occurrence of the event in the event time axis is predicted based on the preset event name list, so that the enterprise after the loan is managed in time according to the probability, the enterprise after the loan management operation is simplified, the management efficiency is improved, and the technical problems that the existing enterprise after the loan management is complex in operation and low in management efficiency are solved.
Drawings
FIG. 1 is a schematic diagram of an apparatus architecture of a hardware operating environment according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a method for managing post-loan information according to a first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.
The post-credit information management device in the embodiment of the invention can be a PC or a server device, and a Java virtual machine runs on the post-credit information management device.
As shown in fig. 1, the post-loan information management apparatus may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 1 is not intended to be limiting of the apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include an operating system, a network communication module, a user interface module, and a management program of post-loan information.
In the device shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call a management program of the post-loan information stored in the memory 1005 and perform operations in the post-loan information management method described below.
Based on the above hardware structure, an embodiment of the method for managing post-loan information according to the present invention is provided.
Referring to fig. 2, fig. 2 is a schematic flowchart illustrating a method for managing post-loan information according to a first embodiment of the present invention, where the method for managing post-loan information includes:
step S10, according to a preset enterprise name list, classifying and integrating the received enterprise related information according to enterprise names to generate enterprise post-loan information sets corresponding to the post-loan enterprises;
the conventional enterprise post-loan management is to manually determine whether the enterprise faces certain risks in the future or not according to relevant information of enterprises related to various large search engines, industry forums, microblogs or WeChat public accounts. Then, the method that the expert searches enterprise information of the enterprise and analyzes the enterprise information is low in efficiency, the number of enterprises which can be processed every day is limited, and when the number of the enterprises is increased to ten thousands or even ten thousands, the expert can hardly analyze all the enterprises. In addition, the expert judges the risks faced by the enterprise based on personal experience knowledge, the expert is required to have rich background knowledge, and the judgment result is easy to deviate due to the existence of subjective factors. Therefore, the management of the information after the enterprise loan in the prior art is not only complicated in operation but also low in management efficiency. In this embodiment, in order to solve the above problem, a method for managing post-loan information is provided, where an enterprise situation of a post-loan enterprise is determined based on an enterprise event timeline, and a probability of occurrence of a risk event of the post-loan enterprise within a preset time period after occurrence of an event in the event timeline is predicted based on a preset event name list, so that the post-loan enterprise is managed in time according to the probability, thereby simplifying post-loan management operations of the enterprise, and improving management efficiency. Specifically, the enterprise-related information includes, but is not limited to, enterprise event information, enterprise microblog information, enterprise forum information, and the like, and the post-loan enterprise information to be managed is listed in a preset enterprise name list in advance. For example, a list of 4000 ten thousand business names registered by domestic workers is currently collected. And then, collecting and storing all enterprise information on the Internet by means of an automatic public opinion collecting technology or a public opinion data purchasing mode, and then classifying and integrating the enterprise related information according to enterprise names so as to attribute the enterprise related information corresponding to each enterprise to the enterprise information, namely generating an enterprise post-loan information set corresponding to each post-loan enterprise.
Specifically, step S10 specifically includes:
carrying out site prefix deletion operation and company suffix deletion operation on the enterprise names in the enterprise name list;
performing regular matching on the deleted enterprise name and information in a preset information base so as to determine to-be-processed enterprise event information corresponding to the enterprise name in the enterprise name list in the information base;
performing word segmentation on the enterprise information of the to-be-processed event to obtain word vectors to be processed corresponding to the enterprise information of the to-be-processed event, and adding the word vectors to be processed to obtain a first document vector;
performing word segmentation on target enterprise event information to obtain target word vectors corresponding to the target enterprise event information, and adding the target word vectors to obtain a second document vector;
calculating the cosine distance between the first document vector and the second document vector, and taking the enterprise event information to be processed as enterprise related information when the cosine distance is greater than a preset threshold value;
and classifying and integrating the enterprise related information according to the enterprise names to generate enterprise post-credit information sets corresponding to the post-credit enterprises.
In this embodiment, for each name in the 4000 ten thousand enterprise name lists, prefixes indicating locations are removed (a list of names of public counties and provinces across the country is found on the network, and filtering is implemented by means of string matching), and suffixes such as "stock limited", "development stock limited", "group stock limited", are removed, so as to obtain an abbreviation of each enterprise. In addition, enterprises can be manually designated for short for some enterprises, and the recall rate of the public opinion classification results is increased. For example, the enterprise obtained by processing "Shenzhen XX Bank Limited company" is called "XX bank" for short. Then, for any enterprise event information, whether the enterprise event information contains the abbreviation of a certain enterprise or not is searched in a regular matching mode, and if not, the processing of the enterprise event information is ended; if yes, cutting words of the enterprise event information, adding word vectors of all words to obtain an enterprise event information document vector X, simultaneously cutting words of the matched business operation range description of the enterprise, namely [ the matched business operation range of the enterprise ], namely matching the enterprise through the enterprise event information, and then inquiring the business operation information according to the enterprise name. The target enterprise event information is enterprise business operation information. And adding the word vectors of all the words to obtain a document vector Y, and classifying the enterprise event information under the enterprise if the cosine distance between the vector X and the vector Y is greater than 0.5. (mainly to solve the following problems: if only the enterprise event information of "enterprise includes enterprise abbreviation" is used to classify the enterprise event information of "chinese bank", the following two enterprise event information a are obtained.) the chinese bank again enters the global system importance bank and becomes a financial institution that has been continuously selected for 6 years. B) The content of the enterprise event information B is not for China banks, but is simply provided once, and the division of the enterprise event information B under China banks is not suitable. By combining the information of the business operation range of the business bank, the enterprise event information A and the business operation range thereof can be found to refer to words such as 'bank', 'finance', and the like (similar semantically), and the distances between the document vectors obtained through word vector calculation are also similar. And the backsight business event information B is different in terms distribution and the description of the business operation range, so that the distance between the document vectors is far. Therefore, the enterprise related information is classified and integrated according to enterprise names, and enterprise post-loan information sets corresponding to the post-loan enterprises are generated.
Step S20, generating enterprise event time axes corresponding to the credited enterprises according to a preset event name list, the enterprise event information in the enterprise credited information set and the occurrence time points corresponding to the enterprise event information;
in this embodiment, for each enterprise, a memorandum of the enterprise on a time axis is generated, and an enterprise event information, such as a triple event, is used to represent an event occurring at a certain time point, that is, an enterprise is referred to as an event name, and an event occurrence time. The list of event names is shown in the following table:
each tertiary event has a corresponding canonical regular expression. And matching the title of each enterprise event information with the regular rule expressions of all the three-level events in sequence, skipping if no rule is hit, and combining the enterprise to which the enterprise event information belongs, the name of the hit three-level event and the issuing time of the enterprise event information into a triple and outputting the triple if the rule is hit. Therefore, enterprise event information corresponding to each post-credit enterprise is sequentially summarized according to the sequence of the event occurrence time points from first to last, and an enterprise event time axis corresponding to each post-credit enterprise is generated. In a specific embodiment, instead of processing a complete 4000 ten thousand enterprises, an enterprise event timeline is generated for only a part of the enterprises, and then an event transition probability matrix is calculated on the small part of the enterprise event information set.
And step S30, calculating the probability of the risk event of each post-loan enterprise within a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-loan management operation on each post-loan enterprise according to the probability of the risk event of each post-loan enterprise.
In this embodiment, a list of events with risks, such as "high management leaving", "company referee", "stockholder withdrawing", "returning", "stop", "owing loan", "fund chain fracture", "cash flow tension", "company closing", "company logout", "bankruptcy reorganization", "supervision stop", etc., is specified in advance in the event name list. And then acquiring triple events of the enterprise to be processed within a preset time period, such as the latest 12 months, sequentially using the triple events as an event A, sequentially using the events in a risk event list specified in an event name list as an event B, and calculating P (B | A, 3), P (B | A, 6) and P (B | A, 12), namely the probability of the occurrence of the event B within 3 months after the occurrence of the event A, the probability of the occurrence of the event B within 6 months after the occurrence of the event A and the probability of the occurrence of the event B within 12 months after the occurrence of the event A. If the conditional probability of some risk event is greater than 0.5, it indicates that the enterprise has a certain risk in the future, and the loan bank may perform corresponding post-loan management operations, such as terminating loan issuance. Specifically, before the step S30, the method further includes: and when a risk event setting instruction is triggered by user operation, adding a risk event identifier to an event in the risk event setting instruction in the event name list so as to specify a risk event with risk in the event name list.
The embodiment provides a method for managing post-loan information, which includes classifying and integrating received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-loan information sets corresponding to each post-loan enterprise; generating an enterprise event time axis corresponding to each credited enterprise according to a preset event name list, enterprise event information in the enterprise credited information set and occurrence time points corresponding to the enterprise event information; and calculating the probability of the risk event of each post-loan enterprise in a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-loan management operation on each post-loan enterprise according to the probability of the risk event of each post-loan enterprise. Through the mode, the enterprise condition of the enterprise after the loan is determined based on the enterprise event time axis, the probability of the occurrence of the risk event of the enterprise in the preset time period after the occurrence of the event in the event time axis is predicted based on the preset event name list, so that the enterprise after the loan is managed in time according to the probability, the enterprise after the loan management operation is simplified, the management efficiency is improved, and the technical problems that the existing enterprise after the loan management is complex in operation and low in management efficiency are solved.
Further, a second embodiment of the method for managing post-loan information according to the present invention is proposed based on the first embodiment of the method for managing post-loan information according to the present invention.
In this embodiment, the step S20 specifically includes:
matching an event title in the enterprise event information with a regular rule expression corresponding to a tertiary event in the event name list, and judging whether the enterprise event information hits the regular rule expression corresponding to the tertiary event;
if the enterprise event information hits the regular rule expression corresponding to the third-level event, combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit third-level event name and the occurrence time point corresponding to the enterprise time information to generate a triple event;
and generating an enterprise event time axis corresponding to each credited enterprise according to the triple event corresponding to each credited enterprise and the occurrence time point corresponding to the triple event.
And if the enterprise event information does not hit the regular rule expression corresponding to the third-level event, marking the enterprise event information as event information to be deleted, and deleting the event information to be deleted in the event set after the enterprise is credited.
In this embodiment, an event occurring at a certain time point, that is, an enterprise is referred to as an event name, and an event occurrence time, is represented by a triple event. Each tertiary event has a corresponding canonical regular expression. And then matching the title of each enterprise event information with the regular rule expressions of all the three-level events in sequence, if the rule is not hit, marking the enterprise event information as event information to be deleted, and deleting the event information to be deleted in the event set after the enterprise credits, namely skipping the addition of the enterprise event information. If the rule is hit, combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit third-level event name and the enterprise event information release time into a triple and outputting the triple. And then adding the triple time into an enterprise event time axis of the corresponding enterprise, wherein the event time axis summarizes all the enterprise event information of the enterprise according to the sequence of the event occurrence time points from first to last.
Further, after the step of combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit tertiary event name, and the occurrence time point corresponding to the enterprise time information to generate a triple event if the enterprise event information hits the regular rule expression corresponding to the tertiary event, the method further includes:
judging whether an event to be merged exists in the triple events corresponding to the credited enterprises, wherein the event to be merged is two or more triple events with the same event title, and the occurrence time points corresponding to the two or more triple events belong to a preset time interval;
if the triple events corresponding to the credited enterprises have events to be combined, combining two or more triple events in the events to be combined into one triple event;
and acquiring the earliest time point from the occurrence time points corresponding to the two or more triple events, and taking the earliest time point as the occurrence time point corresponding to the combined triple event.
In this embodiment, triple events under each enterprise are merged. If an enterprise has the same triple of events in three levels in continuous days or within the time interval not more than one week, the triples are combined into a triple, and the event occurrence time in the triple takes the value with the earliest time. Such as business event information for which 25 reports XX bank wins on 2019-03-01, there were 13 reports of XX bank winning business event information on 2019-03-02 days, there are 6 reports of business event information that XX bank won a prize on 2019-03-05, then 18 enterprise event information reporting XX bank winning prizes on 2019-06-01 days, simple analysis can show that the probability that the winning enterprise event information reported on 1 day, 2 days and 5 days of 3 months is the same winning enterprise event information, it can be merged into an event triplet (XX bank, winning, 2019-03-01), while the report of day 1 of 6 month and 3 month are separated by a longer time interval, and the probability is that another winning business event information is in the report XX bank, so that the event triplet cannot be merged with the triplet of month 3.
Further, a third embodiment of the method for managing post-loan information according to the present invention is provided based on the second embodiment of the method for managing post-loan information according to the present invention.
In this embodiment, the step S30 specifically includes:
sequentially taking the enterprise event information in the enterprise event timeline as first event information, and sequentially taking the risk events in the event name list as second event information;
calculating the probability of the enterprise to which the enterprise event timeline belongs to generating second event information within the corresponding time after the first event information according to the preset event transition probability, and taking the probability as the probability of the enterprise to which the enterprise event timeline belongs to generating risk events;
and sequentially calculating the probability of the risk event of each post-credit enterprise, and executing corresponding post-credit management operation on each post-credit enterprise according to the probability of the risk event of each post-credit enterprise.
In this embodiment, triple events of an enterprise to be processed in a preset time period, for example, in the last 12 months, are obtained, and are sequentially used as an event a, that is, first event information, and events in a risk event list specified in an event name list are sequentially used as an event B, that is, second event information, and P (B | a, 3), P (B | a, 6), and P (B | a, 12), that is, a probability that an event B occurs within 3 months after the event a occurs, a probability that an event B occurs within 6 months after the event a occurs, and a probability that an event B occurs within 12 months after the event a occurs are calculated. And then calculating the probability of occurrence of the risk event after the enterprise event information in the enterprise event time axis corresponding to each post-loan enterprise, judging whether each probability is greater than a preset threshold value, such as 0.5, if so, indicating that the enterprise has a certain risk in the future, and performing corresponding post-loan management operation by a loan issuing bank, such as terminating loan issuing and the like.
Further, before the step of calculating, according to the event name list and the enterprise event timeline, the probability of occurrence of a risk event of each post-lended enterprise within a preset time period, and according to the probability of occurrence of a risk event of each post-lended enterprise, performing corresponding post-lending management operation on each post-lended enterprise, the method further includes:
calculating the event transition probability among the events in the event name list according to a probability calculation formula, wherein the probability calculation formula is as follows:
P(B|A，t)＝NS/(NA+1), where P (B | a, t) is the probability of occurrence of event B within a time interval t after occurrence of event a, A, B is two events in the event name list, t is the time interval after occurrence of an event a, NANumber of triples associated with event A, NSIs the number of times event B occurs within a time interval t after occurrence of event a.
In this embodiment, a global event transition probability is calculated, that is, an event transition probability between events in the event name list is calculated in advance: suppose that the event extraction module extracts the event triples of 4000 ten thousand enterprises, and the triple related to the event A has NAAccording to the tripletsEvent occurrence time statistics the number of occurrences of event B within t months after occurrence of event A is NSThe probability of occurrence of event B within t months after occurrence of event a can be expressed as P (B | a, t) ═ NS/(NA+1), the denominator plus 1 serves to prevent anomalies from occurring at 0, while also smoothing the probability values. All events are followed and the time interval t is assigned 3,6,12, respectively, and then all P (B | a, t) are calculated. The transition probability among the events is calculated according to the big data preferentially, and then the probability of the subsequent risk event of the enterprise after each credit is predicted according to the enterprise event information which has occurred in the existing enterprise event time axis of the enterprise after each credit.
The present invention also provides a post-loan information management apparatus including:
the information classification module is used for classifying and integrating the received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-credit information sets corresponding to the post-credit enterprises;
the time axis generation module is used for generating enterprise event time axes corresponding to the enterprise after credit according to a preset event name list, the enterprise event information in the enterprise after credit information set and occurrence time points corresponding to the enterprise event information;
and the probability calculation module is used for calculating the probability of the risk event of each post-credit enterprise within a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-credit management operation on each post-credit enterprise according to the probability of the risk event of each post-credit enterprise.
Further, the time axis generation module specifically includes:
the event matching unit is used for matching an event title in the enterprise event information with a regular rule expression corresponding to a tertiary event in the event name list and judging whether the enterprise event information hits the regular rule expression corresponding to the tertiary event;
the event generating unit is used for combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit tertiary event name and the occurrence time point corresponding to the enterprise time information to generate a triple event if the enterprise event information hits the regular rule expression corresponding to the tertiary event;
and a time axis generating unit, configured to generate an enterprise event time axis corresponding to each credited enterprise according to the triple event corresponding to each credited enterprise and the occurrence time point corresponding to the triple event.
Further, the timeline generation module is further configured to:
and if the enterprise event information does not hit the regular rule expression corresponding to the third-level event, marking the enterprise event information as event information to be deleted, and deleting the event information to be deleted in the event set after the enterprise is credited.
Further, the timeline generating module specifically further includes an event merging unit, where the event merging unit is configured to:
judging whether an event to be merged exists in the triple events corresponding to the credited enterprises, wherein the event to be merged is two or more triple events with the same event title, and the occurrence time points corresponding to the two or more triple events belong to a preset time interval;
if the triple events corresponding to the credited enterprises have events to be combined, combining two or more triple events in the events to be combined into one triple event;
and acquiring the earliest time point from the occurrence time points corresponding to the two or more triple events, and taking the earliest time point as the occurrence time point corresponding to the combined triple event.
Further, the probability calculation module specifically includes:
the event acquisition unit is used for sequentially taking the enterprise event information in the enterprise event timeline as first event information and sequentially taking the risk events in the event name list as second event information;
the first calculating unit is used for calculating the probability of second event information occurring in the corresponding time after the first event information of the enterprise to which the enterprise event timeline belongs according to a preset event transition probability, and the probability is used as the probability of risk events occurring in the enterprise to which the enterprise event timeline belongs;
and the second calculating unit is used for sequentially calculating the probability of the risk event of each credited enterprise and executing corresponding post-credit management operation on each credited enterprise according to the probability of the risk event of each credited enterprise.
Further, the probability calculation module is specifically further configured to:
calculating the event transition probability among the events in the event name list according to a probability calculation formula, wherein the probability calculation formula is as follows:
P(B|A，t)＝NS/(NA+1), where P (B | a, t) is the probability of occurrence of event B within a time interval t after occurrence of event a, A, B is two events in the event name list, t is the time interval after occurrence of an event a, NANumber of triples associated with event A, NSIs the number of times event B occurs within a time interval t after occurrence of event a.
Further, the information classification module is further configured to:
and when a risk event setting instruction is triggered by user operation, adding a risk event identifier to an event in the risk event setting instruction in the event name list so as to specify a risk event with risk in the event name list.
Further, the information classification module specifically includes:
the information deleting unit is used for carrying out site prefix deleting operation and company suffix deleting operation on the enterprise names in the enterprise name list;
the information matching unit is used for performing regular matching on the deleted enterprise name and information in a preset information base so as to determine to-be-processed enterprise event information corresponding to the enterprise name in the enterprise name list in the information base;
the first word cutting unit is used for cutting words of the enterprise information of the to-be-processed event to obtain word vectors to be processed corresponding to the enterprise information of the to-be-processed event, and adding the word vectors to be processed to obtain a first document vector;
the second word segmentation unit is used for segmenting words of target enterprise event information to obtain target word vectors corresponding to the target enterprise event information, and adding the target word vectors to obtain a second document vector;
the vector calculation unit is used for calculating the cosine distance between the first document vector and the second document vector and taking the enterprise event information to be processed as enterprise related information when the cosine distance is greater than a preset threshold value;
and the information integration unit is used for classifying and integrating the enterprise related information according to the enterprise name to generate an enterprise post-credit information set corresponding to each post-credit enterprise.
The methods executed by the program modules may refer to various embodiments of the method for managing post-loan information according to the present invention, and are not described herein again.
The invention also provides a computer readable storage medium.
The computer-readable storage medium of the present invention stores thereon a post-loan information management program that, when executed by a processor, implements the steps of the post-loan information management method described above.
The method implemented when the management program of the post-credit information running on the processor is executed may refer to each embodiment of the management method of the post-credit information of the present invention, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (17)
1. A method for managing post-loan information, the method comprising the steps of:
classifying and integrating the received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-credit information sets corresponding to the post-credit enterprises;
generating an enterprise event time axis corresponding to each credited enterprise according to a preset event name list, enterprise event information in the enterprise credited information set and occurrence time points corresponding to the enterprise event information;
and calculating the probability of the risk event of each post-loan enterprise in a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-loan management operation on each post-loan enterprise according to the probability of the risk event of each post-loan enterprise.
2. The method according to claim 1, wherein the step of generating the enterprise event timeline corresponding to each post-loan enterprise according to a preset event name list, the enterprise event information in the enterprise post-loan information set, and the occurrence time point corresponding to the enterprise event information specifically comprises:
matching an event title in the enterprise event information with a regular rule expression corresponding to a tertiary event in the event name list, and judging whether the enterprise event information hits the regular rule expression corresponding to the tertiary event;
if the enterprise event information hits the regular rule expression corresponding to the third-level event, combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit third-level event name and the occurrence time point corresponding to the enterprise time information to generate a triple event;
and generating an enterprise event time axis corresponding to each credited enterprise according to the triple event corresponding to each credited enterprise and the occurrence time point corresponding to the triple event.
3. The method for managing post-credit information according to claim 2, wherein after the step of matching the event title in the enterprise event information with the regular expression corresponding to the third-level event in the event name list and determining whether the enterprise event information hits the regular expression corresponding to the third-level event, the method further comprises:
and if the enterprise event information does not hit the regular rule expression corresponding to the third-level event, marking the enterprise event information as event information to be deleted, and deleting the event information to be deleted in the event set after the enterprise is credited.
4. The method for managing post-credit information according to claim 2, wherein after the step of generating a triple event by combining the business name of the business to which the business event information belongs, the hit tertiary event name, and the occurrence time point corresponding to the business time information if the business event information hits the regular rule expression corresponding to the tertiary event, the method further comprises:
judging whether an event to be merged exists in the triple events corresponding to the credited enterprises, wherein the event to be merged is two or more triple events with the same event title, and the occurrence time points corresponding to the two or more triple events belong to a preset time interval;
if the triple events corresponding to the credited enterprises have events to be combined, combining two or more triple events in the events to be combined into one triple event;
and acquiring the earliest time point from the occurrence time points corresponding to the two or more triple events, and taking the earliest time point as the occurrence time point corresponding to the combined triple event.
5. The method according to claim 2, wherein the step of calculating the probability of occurrence of the risk event of each lended enterprise within a preset time period according to the event name list and the enterprise event timeline, and performing the corresponding post-lending management operation on each lended enterprise according to the probability of occurrence of the risk event of each lended enterprise specifically comprises:
sequentially taking the enterprise event information in the enterprise event timeline as first event information, and sequentially taking the risk events in the event name list as second event information;
calculating the probability of the enterprise to which the enterprise event timeline belongs to generating second event information within the corresponding time after the first event information according to the preset event transition probability, and taking the probability as the probability of the enterprise to which the enterprise event timeline belongs to generating risk events;
and sequentially calculating the probability of the risk event of each post-credit enterprise, and executing corresponding post-credit management operation on each post-credit enterprise according to the probability of the risk event of each post-credit enterprise.
6. The method for managing post-loan information according to claim 5, wherein before the step of calculating the probability of occurrence of the risk event of each post-loan enterprise within a preset time period according to the event name list and the enterprise event timeline, and performing the corresponding post-loan management operation on each post-loan enterprise according to the probability of occurrence of the risk event of each post-loan enterprise, the method further comprises:
calculating the event transition probability among the events in the event name list according to a probability calculation formula, wherein the probability calculation formula is as follows:
P(B|A，t)＝NR/(NA+1), where P (B | a, t) is the probability of occurrence of event B within a time interval t after occurrence of event a, A, B is two events in the event name list, t is the time interval after occurrence of an event a, NANumber of triples associated with event A, NBIs the number of times event B occurs within a time interval t after occurrence of event a.
7. The method for managing post-loan information according to claim 5, wherein before the step of calculating the probability of occurrence of the risk event of each post-loan enterprise within a preset time period according to the event name list and the enterprise event timeline, and performing the corresponding post-loan management operation on each post-loan enterprise according to the probability of occurrence of the risk event of each post-loan enterprise, the method further comprises:
and when a risk event setting instruction is triggered by user operation, adding a risk event identifier to an event in the risk event setting instruction in the event name list so as to specify a risk event with risk in the event name list.
8. The method for managing post-loan information according to any one of claims 1 to 7, wherein the step of classifying and integrating the received enterprise-related information according to enterprise names according to a preset enterprise name list to generate an enterprise post-loan information set corresponding to each post-loan enterprise specifically includes:
carrying out site prefix deletion operation and company suffix deletion operation on the enterprise names in the enterprise name list;
performing regular matching on the deleted enterprise name and information in a preset information base so as to determine to-be-processed enterprise event information corresponding to the enterprise name in the enterprise name list in the information base;
performing word segmentation on the enterprise information of the to-be-processed event to obtain word vectors to be processed corresponding to the enterprise information of the to-be-processed event, and adding the word vectors to be processed to obtain a first document vector;
performing word segmentation on target enterprise event information to obtain target word vectors corresponding to the target enterprise event information, and adding the target word vectors to obtain a second document vector;
calculating the cosine distance between the first document vector and the second document vector, and taking the enterprise event information to be processed as enterprise related information when the cosine distance is greater than a preset threshold value;
and classifying and integrating the enterprise related information according to the enterprise names to generate enterprise post-credit information sets corresponding to the post-credit enterprises.
9. An apparatus for managing post-loan information, comprising:
the information classification module is used for classifying and integrating the received enterprise related information according to enterprise names according to a preset enterprise name list to generate enterprise post-credit information sets corresponding to the post-credit enterprises;
the time axis generation module is used for generating enterprise event time axes corresponding to the enterprise after credit according to a preset event name list, the enterprise event information in the enterprise after credit information set and occurrence time points corresponding to the enterprise event information;
and the probability calculation module is used for calculating the probability of the risk event of each post-credit enterprise within a preset time period according to the event name list and the enterprise event time axis, and executing corresponding post-credit management operation on each post-credit enterprise according to the probability of the risk event of each post-credit enterprise.
10. The apparatus for managing post-loan information according to claim 9, wherein the time axis generation module specifically includes:
the event matching unit is used for matching an event title in the enterprise event information with a regular rule expression corresponding to a tertiary event in the event name list and judging whether the enterprise event information hits the regular rule expression corresponding to the tertiary event;
the event generating unit is used for combining the enterprise name of the enterprise to which the enterprise event information belongs, the hit tertiary event name and the occurrence time point corresponding to the enterprise time information to generate a triple event if the enterprise event information hits the regular rule expression corresponding to the tertiary event;
and a time axis generating unit, configured to generate an enterprise event time axis corresponding to each credited enterprise according to the triple event corresponding to each credited enterprise and the occurrence time point corresponding to the triple event.
11. The apparatus for managing post-credit information of claim 10, wherein the timeline generation module is further configured to:
and if the enterprise event information does not hit the regular rule expression corresponding to the third-level event, marking the enterprise event information as event information to be deleted, and deleting the event information to be deleted in the event set after the enterprise is credited.
12. The apparatus for managing post-loan information according to claim 10, wherein the time axis generation module further includes an event merging unit, the event merging unit being configured to:
judging whether an event to be merged exists in the triple events corresponding to the credited enterprises, wherein the event to be merged is two or more triple events with the same event title, and the occurrence time points corresponding to the two or more triple events belong to a preset time interval;
if the triple events corresponding to the credited enterprises have events to be combined, combining two or more triple events in the events to be combined into one triple event;
and acquiring the earliest time point from the occurrence time points corresponding to the two or more triple events, and taking the earliest time point as the occurrence time point corresponding to the combined triple event.
13. The apparatus for managing post-loan information according to claim 10, wherein the probability calculation module specifically includes:
the event acquisition unit is used for sequentially taking the enterprise event information in the enterprise event timeline as first event information and sequentially taking the risk events in the event name list as second event information;
the first calculating unit is used for calculating the probability of second event information occurring in the corresponding time after the first event information of the enterprise to which the enterprise event timeline belongs according to a preset event transition probability, and the probability is used as the probability of risk events occurring in the enterprise to which the enterprise event timeline belongs;
and the second calculating unit is used for sequentially calculating the probability of the risk event of each credited enterprise and executing corresponding post-credit management operation on each credited enterprise according to the probability of the risk event of each credited enterprise.
14. The apparatus for managing post-loan information according to claim 13, wherein the probability calculation module is further specifically configured to:
calculating the event transition probability among the events in the event name list according to a probability calculation formula, wherein the probability calculation formula is as follows:
P(B|A，t)＝Ns/(NA+1), where P (B | a, t) is the probability of occurrence of event B within a time interval t after occurrence of event a, A, B is two events in the event name list, t is the time interval after occurrence of an event a, NANumber of triples associated with event A, NSIs the number of times event B occurs within a time interval t after occurrence of event a.
15. The apparatus for managing post-loan information according to any of claims 9-14, wherein the information classification module specifically comprises:
the information deleting unit is used for carrying out site prefix deleting operation and company suffix deleting operation on the enterprise names in the enterprise name list;
the information matching unit is used for performing regular matching on the deleted enterprise name and information in a preset information base so as to determine to-be-processed enterprise event information corresponding to the enterprise name in the enterprise name list in the information base;
the first word cutting unit is used for cutting words of the enterprise information of the to-be-processed event to obtain word vectors to be processed corresponding to the enterprise information of the to-be-processed event, and adding the word vectors to be processed to obtain a first document vector;
the second word segmentation unit is used for segmenting words of target enterprise event information to obtain target word vectors corresponding to the target enterprise event information, and adding the target word vectors to obtain a second document vector;
the vector calculation unit is used for calculating the cosine distance between the first document vector and the second document vector and taking the enterprise event information to be processed as enterprise related information when the cosine distance is greater than a preset threshold value;
and the information integration unit is used for classifying and integrating the enterprise related information according to the enterprise name to generate an enterprise post-credit information set corresponding to each post-credit enterprise.
16. A post-loan information management apparatus, characterized by comprising: memory, a processor and a post-credit management program stored on the memory and executable on the processor, the post-credit management program, when executed by the processor, implementing the steps of the method for managing post-credit information according to any one of claims 1 to 8.
17. A computer-readable storage medium, on which a management program of post-loan information is stored, the management program of post-loan information realizing the steps of the management method of post-loan information according to any one of claims 1 to 8 when executed by a processor.
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| CN201911074708.0A CN110807702A (en) | 2019-11-05 | 2019-11-05 | Method, device, equipment and storage medium for managing information after loan |
| PCT/CN2020/126225 WO2021088820A1 (en) | 2019-11-05 | 2020-11-03 | Post-loan information management method and apparatus, device, and storage medium |
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| WO2021088820A1 (en) * | 2019-11-05 | 2021-05-14 | 深圳前海微众银行股份有限公司 | Post-loan information management method and apparatus, device, and storage medium |
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| US8260653B1 (en) * | 2009-07-23 | 2012-09-04 | Bank Of America Corporation | Computer-implemented change risk assessment |
| CN108564465A (en) * | 2018-05-03 | 2018-09-21 | 上海第二工业大学 | A kind of enterprise credit management method |
| CN109670724A (en) * | 2018-12-29 | 2019-04-23 | 重庆誉存大数据科技有限公司 | Methods of risk assessment and device |
| CN110111198A (en) * | 2019-04-23 | 2019-08-09 | 上海淇玥信息技术有限公司 | User's financial risks predictor method, device, electronic equipment and readable medium |
| CN110222249B (en) * | 2019-05-06 | 2024-05-31 | 平安科技（深圳）有限公司 | Data storage method, device, computer equipment and storage medium |
| CN110807702A (en) * | 2019-11-05 | 2020-02-18 | 深圳前海微众银行股份有限公司 | Method, device, equipment and storage medium for managing information after loan |
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