CN110264222B - Method, device and terminal equipment for investigating due-job based on data acquisition - Google Patents
Method, device and terminal equipment for investigating due-job based on data acquisition Download PDFInfo
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Abstract
The invention is applicable to the technical field of data processing, and provides a due diligence investigation method, a device, terminal equipment and a computer readable storage medium based on data acquisition, which comprise the following steps: distributing the task to be completely adjusted to the target client; screening comparison items if the registered data corresponding to all the items to be adjusted are the same as the field data uploaded by the target client, and acquiring the default data and the default reasons corresponding to the comparison items of at least two default enterprises in a database; calculating a difference measurement value between the default data and the field data corresponding to the comparison project; determining a default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to a target client according to the default reason of the target default enterprise, and acquiring enterprise response information corresponding to the reminding call, which is uploaded by the target client; an exhaustion report is generated based on the site data, the breach cause of the target breach of business, and business response information. The invention improves the effect of the due investigation.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a due job investigation method, a device, terminal equipment and a computer readable storage medium based on data acquisition.
Background
With the development of economy, the number of enterprises has increased explosively in recent years, and in the operation process of enterprises, interaction business with banks, such as loans to public or enterprises, is indispensable. For banks, in order to ensure efficient performance of business, the business is investigated for due job before the business is performed.
In the prior art, when an enterprise to be tuned is investigated by a due job, the actual operation condition of the enterprise to be tuned is generally obtained, the actual operation condition is added into a set template to generate a perfect tuning report, so that auditing personnel of a bank, such as a client manager, check the report, and judge whether to develop business with the enterprise to be tuned by the auditing personnel. Because the debug report only contains the actual operation condition of the enterprise to be debugged, the auditor can not rapidly analyze whether the enterprise to be debugged is reliable or not from the debug report, namely the information of the debug report is not comprehensive, and the effect of the due job investigation is poor.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a method, an apparatus, a terminal device, and a computer readable storage medium for performing due-job investigation based on data collection, so as to solve the problem of poor effect of due-job investigation in the prior art.
A first aspect of an embodiment of the present invention provides a method for performing due diligence based on data acquisition, including:
generating an adjustment task corresponding to an enterprise to be adjusted, and distributing the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
determining at least two items to be adjusted preset in the adjustment task, and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
acquiring field data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client, and judging whether the registered data corresponding to the to-be-adjusted item and the field data are the same or not;
if the registered data corresponding to all the items to be adjusted are the same as the on-site data, screening comparison items from the items to be adjusted;
obtaining the default data corresponding to the comparison items of at least two default enterprises in a database, wherein the default reasons of the default enterprises;
calculating a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the difference degree between the default data and the field data;
Determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and acquiring enterprise response information corresponding to the reminding call, which is uploaded by the target client;
generating an adjustment report of the enterprise to be adjusted based on the field data, the reasons for the violations of the target violating enterprise, and the enterprise response information.
A second aspect of an embodiment of the present invention provides a due diligence apparatus based on data acquisition, including:
the allocation unit is used for generating an adjustment task corresponding to an enterprise to be adjusted, and allocating the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
the determining unit is used for determining at least two items to be adjusted preset in the adjustment task and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
the judging unit is used for acquiring the on-site data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client and judging whether the registered data corresponding to the to-be-adjusted item and the on-site data are the same or not;
The acquisition unit is used for screening comparison items from the items to be adjusted if the registered data corresponding to all the items to be adjusted are the same as the field data;
the breach acquisition unit is used for acquiring breach data corresponding to the comparison items of at least two breach enterprises and breach reasons of the breach enterprises in a database;
the computing unit is used for computing a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the degree of difference between the default data and the field data;
the sending unit is used for determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and obtaining enterprise response information which is uploaded by the target client and corresponds to the reminding call;
and the generating unit is used for generating an adjustment report of the enterprise to be adjusted based on the field data, the default reasons of the target default enterprise and the enterprise response information.
A third aspect of an embodiment of the present invention provides a terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
Generating an adjustment task corresponding to an enterprise to be adjusted, and distributing the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
determining at least two items to be adjusted preset in the adjustment task, and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
acquiring field data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client, and judging whether the registered data corresponding to the to-be-adjusted item and the field data are the same or not;
if the registered data corresponding to all the items to be adjusted are the same as the on-site data, screening comparison items from the items to be adjusted;
obtaining the default data corresponding to the comparison items of at least two default enterprises in a database, wherein the default reasons of the default enterprises;
calculating a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the difference degree between the default data and the field data;
determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and acquiring enterprise response information corresponding to the reminding call, which is uploaded by the target client;
Generating an adjustment report of the enterprise to be adjusted based on the field data, the reasons for the violations of the target violating enterprise, and the enterprise response information.
A fourth aspect of the embodiments of the present invention provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of:
generating an adjustment task corresponding to an enterprise to be adjusted, and distributing the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
determining at least two items to be adjusted preset in the adjustment task, and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
acquiring field data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client, and judging whether the registered data corresponding to the to-be-adjusted item and the field data are the same or not;
if the registered data corresponding to all the items to be adjusted are the same as the on-site data, screening comparison items from the items to be adjusted;
obtaining the default data corresponding to the comparison items of at least two default enterprises in a database, wherein the default reasons of the default enterprises;
Calculating a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the difference degree between the default data and the field data;
determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and acquiring enterprise response information corresponding to the reminding call, which is uploaded by the target client;
generating an adjustment report of the enterprise to be adjusted based on the field data, the reasons for the violations of the target violating enterprise, and the enterprise response information.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
in the embodiment of the invention, an adjustment task corresponding to an enterprise to be adjusted is generated, the adjustment task is distributed to a target client, if all the registration data corresponding to the items to be adjusted are the same as the on-site data uploaded by the target client, at least two default enterprises are acquired in a database, the default enterprise corresponding to the default data closest to the on-site data is determined as the target default enterprise, a warning call is sent to the target client according to the default cause of the target default enterprise, enterprise response information corresponding to the warning call and uploaded by the target client is acquired, and finally an adjustment report of the enterprise to be adjusted is generated based on the on-site data, the default cause of the target default enterprise and the enterprise response information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an implementation of a due diligence method based on data collection according to an embodiment of the present invention;
fig. 2 is a flowchart of an implementation of a due diligence method based on data collection according to the second embodiment of the present invention;
FIG. 3 is a flowchart of an implementation of a due diligence method based on data collection according to a third embodiment of the present invention;
fig. 4 is a flowchart of an implementation of a due diligence method based on data collection according to the fourth embodiment of the present invention;
FIG. 5 is a flowchart of an implementation of a due diligence method based on data collection according to a fifth embodiment of the present invention;
fig. 6 is a block diagram of a device for investigating due diligence based on data collection according to a sixth embodiment of the present invention;
fig. 7 is a schematic diagram of a terminal device according to a seventh embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
Fig. 1 shows an implementation flow of a due diligence method based on data collection according to an embodiment of the present invention, which is described in detail below:
in S101, an adjustment task corresponding to the enterprise to be adjusted is generated, and the adjustment task is distributed to a target client, where the target client is one of at least two adjustment clients.
The method and the system for implementing the online investigation are characterized in that a server/client architecture is applied to conduct online and remote investigation of due diligence, firstly, an due diligence task corresponding to an enterprise to be regulated is generated at the server, the due diligence task is distributed to a target client, the target client is one of at least two due diligence clients, and the due diligence client is a preset client for executing the due diligence task and is held by an up diligence of the up diligence investigation. The determining manner of the target client may be determined randomly in all the tunable clients, a tunable client may be designated as the target client, or other determining manners may be applied, which is not limited in the embodiment of the present invention.
In S102, at least two items to be tuned preset in the tuning task are determined, and registration data corresponding to the items to be tuned of the enterprise to be tuned are determined.
According to the main body initiating the due job investigation, such as the actual situation of a bank, at least two items to be adjusted are set in the adjustment task, and the registration data of the enterprise to be adjusted corresponding to the items to be adjusted are determined. The registration data under the to-be-adjusted item can be manually added at the server, the registration data can be identified and added in an application form (due-job investigation application form) provided by the to-be-adjusted enterprise to the bank, and the name of the to-be-adjusted enterprise and the to-be-adjusted item can be used as keywords together to search in a bank database, the Internet or an industrial and commercial department database to obtain the registration data. It should be noted that this step does not limit the necessity of adding registration data under each item to be tuned.
In S103, the on-site data corresponding to the to-be-tuned item of the to-be-tuned enterprise uploaded by the target client is obtained, and whether the registered data corresponding to the to-be-tuned item and the on-site data are the same is determined.
After the task of the adjustment is distributed to the target client, an adjustment person holding the target client can go to the enterprise to be adjusted to perform the investigation of the end of the job, and the on-site data of the enterprise to be adjusted corresponding to the item to be adjusted is uploaded through the target client, wherein the uploading mode includes but is not limited to text input, photo uploading, sound uploading and video uploading (the data uploading mode of each item to be adjusted can be predefined in the server), and the video uploading mode can be real-time video uploading or uploading of the video file which is already shot. After the server acquires the field data corresponding to the items to be adjusted, judging whether the registered data and the field data under each item to be adjusted are the same, and executing different operations according to different judging results.
Optionally, if it is detected that there is a to-be-tuned item for which the field data is not acquired, an addition prompt is output based on the to-be-tuned item. In the embodiment of the invention, whether the to-be-adjusted item which does not acquire the field data exists or not can be detected, and if the to-be-adjusted item which does not acquire the field data does not exist, the subsequent steps are executed; if the to-be-adjusted items which do not acquire the on-site data exist, an adding prompt is output based on the to-be-adjusted items, and the full-adjustment personnel is prompted to continuously upload the on-site data until the on-site data corresponding to each to-be-adjusted item are acquired. The integrity of the field data is improved through the method.
In S104, if the registration data corresponding to all the to-be-tuned items are the same as the field data, a comparison item is selected from the to-be-tuned items.
The due-job investigation in the embodiment of the invention is to make the bank know the operation condition of the enterprise to be regulated, so as to be convenient for judging whether to develop a service (such as loan service) with the enterprise to be regulated, and part of the items to be regulated may only represent the identity or position of the enterprise to be regulated and the like and are irrelevant to the operation condition, so in this step, if the registration data corresponding to all the items to be regulated are identical to the field data, the comparison items relevant to the operation condition are screened out from the items to be regulated, the comparison items can be appointed in advance, and the quantity is at least one, for example, the comparison items can comprise personnel number, enterprise score, annual income and annual income gain, wherein if the field data only exist under the items to be regulated, the registration data under the items to be regulated are confirmed to be identical to the field data. Otherwise, if the to-be-tuned item exists, the registration data corresponding to the to-be-tuned item is inconsistent with the on-site data, the tuning-out task is paused, the registration data and the on-site data are sent to the auditing party client, whether the tuning-out task is continuously executed is judged according to the auditing result returned by the auditing party client, and the auditing party client can be held by a bank client manager or other personnel with tuning-out authority.
In S105, obtaining, in a database, the breach data of at least two breach enterprises corresponding to the comparison item and the breach reason of the breach enterprise.
In this step, the existing default situation is used as a reference for performing the due investigation on the enterprise to be modulated, specifically, default data corresponding to the comparison item of at least two default enterprises and default reasons of the default enterprises are obtained in a database, wherein the database may be a bank database or an industrial and commercial department database, and the embodiment of the present invention is not limited to this.
In S106, a difference measure value between the breach data and the field data corresponding to the comparison item is calculated, the difference measure value indicating a degree of difference between the breach data and the field data.
After obtaining the default data corresponding to the comparison project of the default enterprise, calculating a difference measurement value between the default data corresponding to the comparison project and the field data, wherein the difference measurement value indicates the difference degree between the default data and the field data, and the specific calculation mode is described later.
In S107, the default enterprise corresponding to the difference measurement value with the lowest value is determined as a target default enterprise, and a reminder call is sent to the target client according to the default reason of the target default enterprise, so as to obtain enterprise response information corresponding to the reminder call, which is uploaded by the target client.
The discrepancy gauge indicates the discrepancy degree between the breach data and the on-site data, so the breach enterprise corresponding to the discrepancy gauge with the lowest value is determined as the closest target breach enterprise to the enterprise to be regulated, and a reminding call is sent to the target client according to the breach reason of the target breach enterprise, wherein the reminding call can be the breach reason itself, and also a sentence formed by adding a custom sentence structure on the basis of the breach reason, for example, on the basis of the breach reason that the breach is "the market reaction is low and the goods backlog is caused, and the fund chain is broken", the reminding call can be the "the perception of inquiring the client about the goods backlog and the fund chain is broken caused by the market reaction is low". After the server sends the reminding call to the target client, the full-call personnel holding the target client can inquire the client (such as the legal person of the enterprise to be regulated) according to the reminding call, and return enterprise response information replied by the client to the server through the target client.
In S108, an adjustment report of the enterprise to be adjusted is generated based on the field data, the cause of the breach of the goal breach of the business, and the business response information.
In order to record the due job investigation process by the people, in this step, an adjustment report is generated based on the acquired field data, the default reason of the target default enterprise and the enterprise response information, and in order to facilitate the checking of the adjustment report, the adjustment report may be uploaded to a preset storage platform for storage. The bank client manager or other personnel with the adjustment authority can acquire the adjustment report through the auditing party client, judge whether the enterprise to be adjusted is reliable according to the adjustment report, and judge whether to develop business with the enterprise to be adjusted.
As can be seen from the embodiment shown in fig. 1, in the embodiment of the present invention, an adjustment task is allocated to a target client, registration data corresponding to items to be adjusted are compared with field data uploaded by the target client, if all the registration data corresponding to the items to be adjusted are identical to the field data, the comparison items are screened out, the default data and the default reasons of at least two default enterprises are obtained in a database, the default enterprise corresponding to the default data closest to the field data is determined as a target default enterprise, a warning call is sent to the target client based on the default reasons of the target default enterprise, and enterprise response information corresponding to the warning call is obtained and uploaded by the target client, finally an adjustment report is generated based on the field data, the default reasons of the target default enterprise and the enterprise response information.
Fig. 2 shows a method for investigating due diligence obtained by refining a process of generating an adjustment task corresponding to an enterprise to be adjusted on the basis of the first embodiment of the present invention. The embodiment of the invention provides a realization flow chart of a due-job investigation method based on data acquisition, as shown in fig. 2, the due-job investigation method can comprise the following steps:
in S201, blacklist checking is performed on the enterprise to be tuned.
Before allocating the task of dispatching out, the server may check the blacklist of the enterprise to be dispatched, specifically, may search the preset blacklist by using the name of the enterprise to be dispatched as a search condition, where the blacklist may be a blacklist in a bank, and may also be a trust-lost enterprise list or an abnormal operation list provided by a national enterprise information display system.
In S202, if the to-be-tuned enterprise is not located in the preset blacklist, generating an adjustment task corresponding to the to-be-tuned enterprise.
If the name of the enterprise to be adjusted is not in the blacklist, the task of the enterprise to be adjusted is proved to be effective, so that the task of the enterprise to be adjusted is generated at the server side.
In S203, if the enterprise to be investigated is located in the blacklist, an error prompt is output.
If the name of the enterprise to be adjusted is in the blacklist, an error prompt is output for related personnel to further check in order to prevent human resource waste caused by executing invalid adjustment tasks.
As can be seen from the embodiment shown in fig. 2, in the embodiment of the present invention, blacklist checking is performed on an enterprise to be tuned, and if the enterprise to be tuned is not located in a preset blacklist, an adjustment task corresponding to the enterprise to be tuned is generated; if the enterprise to be investigated is located in the blacklist, an error prompt is output, and the blacklist checking is performed on the enterprise to be investigated, so that the effective rate of the generated adjustment task is improved, and resource waste caused by executing the invalid adjustment task is avoided.
Fig. 3 shows a method for investigating due diligence obtained by refining a process of assigning an adjustment task to a target client based on the first embodiment of the present invention. The embodiment of the invention provides a realization flow chart of a due-job investigation method based on data acquisition, as shown in fig. 3, the due-job investigation method can comprise the following steps:
in S301, the task information of the task to be tuned is issued to all the tuning clients satisfying the set tuning condition.
In order to reasonably distribute the task of the exhaustion, in the embodiment of the invention, issuing task information of the task to all the clients satisfying the set condition, specifically, different adjustment levels can be set for different adjustment clients, and adjustment conditions are set to be specific levels; the client state may also be set in advance for the tunable client, the client state including a non-tunable state and a tunable state, and the tunable condition may be set to the client state as the tunable state. The task information includes, but is not limited to, an enterprise name of the enterprise to be tuned and a geographic location of the enterprise to be tuned.
In S302, if the client response information about the task information returned by the tunable client is received, the tunable client corresponding to the earliest received client response information is determined to be the target client, and the tunable task is allocated to the target client.
After the task information is released to the tunable client which meets the tunable conditions, an tunable person holding the tunable client can judge whether to return the client response information to the server through the tunable client according to the task information. If the server receives the client response information of the tunable client about the task information, determining the tunable client corresponding to the earliest received client response information as a target client, and distributing the tunable task to the target client.
As can be seen from the embodiment shown in fig. 3, in the embodiment of the present invention, task information of an adjustment task is issued to all adjustment clients that meet a set adjustment condition, if client response information about the task information returned by the adjustment client is received, an adjustment client corresponding to the earliest received client response information is determined as a target client, and the adjustment task is assigned to the target client.
Fig. 4 shows a method for investigating due diligence obtained by expanding a process before acquiring field data corresponding to a to-be-tuned item of a to-be-tuned enterprise uploaded by a target client. The embodiment of the invention provides a realization flow chart of a due-job investigation method based on data acquisition, as shown in fig. 4, the due-job investigation method can comprise the following steps:
in S401, it is detected whether the target client satisfies a set upload condition.
In order to prevent the full-fitter from carrying out false investigation and uploading false field data, in the embodiment of the invention, an uploading condition is set, and whether the target client side meets the uploading condition is detected, wherein the uploading condition is used for judging whether the full-fitter is carrying out full-job investigation. Specifically, the uploading condition may be set such that the distance between the target client and the address of the enterprise to be tuned is smaller than a preset distance threshold (e.g., 100 meters); the uploading condition can also be set to be the same as the legal image of the enterprise to be adjusted in the result of face recognition of the image shot by the target client.
In S402, if the target client meets the upload condition, the upload authority of the target client is opened.
If the target client side is detected to meet the uploading condition, the due staff is proved to be truly effective in due staff investigation, and uploading authority of uploading the field data by the target client side is opened; if the target client side is detected to not meet the uploading condition, the uploading authority of the target client side is kept in a closed state until the target client side meets the uploading condition.
As can be seen from the embodiment shown in fig. 4, in the embodiment of the present invention, whether the target client meets the set uploading condition is detected, if the target client meets the uploading condition, the uploading authority of the target client is opened, and whether the target client meets the uploading condition is detected, so that whether the due job investigation process is real and effective is determined, and the effective rate of the received field data is improved.
Fig. 5 shows a dead-end investigation method obtained by refining the process of calculating the difference measurement value between the default data and the on-site data corresponding to the comparison item on the basis of the first embodiment of the present invention. The embodiment of the invention provides a realization flow chart of a due-job investigation method based on data acquisition, as shown in fig. 5, the due-job investigation method can comprise the following steps:
In S501, a weight coefficient and a scaling coefficient corresponding to the comparison item are determined, where the weight coefficient indicates a degree of importance of the comparison item.
When the difference measurement value is calculated, firstly, a weight coefficient and a scaling coefficient corresponding to the comparison item are determined, the weight coefficient indicates the importance degree of the comparison item, the larger the weight coefficient is, the higher the importance degree of the corresponding comparison item is, and the weight coefficient of different comparison items can be set according to the due investigation requirement of a banking party in practice; the scaling factor is used for scaling the data corresponding to the comparison items, so that differences formed by different dimensions among the data corresponding to different comparison items are omitted, and calculation is facilitated.
In S502, scaling the on-site data and the default data corresponding to the comparison item according to the scaling coefficient, calculating an initial difference value between the scaled on-site data and the default data, and weighting the initial difference value according to the weight coefficient to obtain the difference measurement value.
After the weight coefficient and the scaling coefficient corresponding to the comparison project are determined, scaling is carried out on the field data and the default data corresponding to the comparison project according to the scaling coefficient. For example, for a comparison item of staff number, a scaling factor may be set to be 1/100, if the field data corresponding to the comparison item is 200 persons and the default data is 190 persons, the field data obtained by scaling according to the scaling factor is 200×1/100=2, and the default data obtained by scaling is 190×1/100=1.9. Calculating an initial difference value between the scaled field data and the default data, wherein the initial difference value can be a difference value between the scaled field data and the scaled default data, such as a value obtained by subtracting the scaled default data from the scaled field data or a value obtained by subtracting the scaled field data from the scaled default data; the initial difference value can also be the ratio between the scaled field data and the scaled default data, and the specific calculation mode can be determined according to the actual application scene. Then, the initial difference values are weighted according to the weight coefficients to obtain difference value, and when the number of the comparison items is at least two, the initial difference values corresponding to the comparison items are weighted and summed according to the weight coefficients to obtain difference value, for example, the weight coefficient corresponding to the comparison item A is x 1 The corresponding initial difference value is y 1 The weight coefficient corresponding to the comparison item B is x 2 The corresponding initial difference value is y 2 The final difference measurement value is x 1 ·y 1 +x 2 ·y 2 。
As can be seen from the embodiment shown in fig. 5, in the embodiment of the present invention, the weight coefficient and the scaling coefficient corresponding to the comparison item are determined, the on-site data and the default data corresponding to the comparison item are scaled according to the scaling coefficient, the initial difference value between the scaled on-site data and the default data is calculated, and the initial difference value is weighted according to the weight coefficient to obtain the difference measurement value.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
Corresponding to the data acquisition-based due diligence method described in the above embodiments, fig. 6 shows a block diagram of a data acquisition-based due diligence apparatus according to an embodiment of the present invention, and referring to fig. 6, the due diligence apparatus includes:
The allocation unit 61 is configured to generate an adjustment task corresponding to an enterprise to be adjusted, and allocate the adjustment task to a target client, where the target client is one of at least two adjustment clients;
the determining unit 62 is configured to determine at least two to-be-tuned items preset in the tuning task, and determine registration data corresponding to the to-be-tuned items of the to-be-tuned enterprise;
a judging unit 63, configured to obtain field data corresponding to the to-be-tuned item of the to-be-tuned enterprise uploaded by the target client, and judge whether the registered data corresponding to the to-be-tuned item and the field data are the same;
an obtaining unit 64, configured to screen out a comparison item from the items to be adjusted if the registration data corresponding to all the items to be adjusted are the same as the field data;
the breach obtaining unit 65 is configured to obtain breach data corresponding to the comparison item of at least two breach enterprises and breach reasons of the breach enterprises in a database;
a calculation unit 66 for calculating a difference measure value between the breach data and the field data corresponding to the comparison item, the difference measure value indicating a degree of difference between the breach data and the field data;
A sending unit 67, configured to determine the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, send a reminder to the target client according to the default reason of the target default enterprise, and obtain enterprise response information corresponding to the reminder, which is uploaded by the target client;
a generating unit 68, configured to generate an adjustment report of the to-be-adjusted enterprise based on the field data, the breach cause of the target breach of the business, and the business response information.
Optionally, the distribution unit 61 comprises:
the checking unit is used for checking the blacklist of the enterprise to be adjusted;
the allocation subunit is used for generating an adjustment task corresponding to the enterprise to be adjusted if the enterprise to be adjusted is not located in a preset blacklist;
and the output unit is used for outputting an error prompt if the enterprise to be investigated is located in the blacklist.
Optionally, the distribution unit 61 comprises:
the issuing unit is used for issuing the task information of the task to all the adjustment clients meeting the set adjustment conditions;
and the target client determining unit is used for determining the up-regulation client corresponding to the earliest received client response information as a target client and distributing the up-regulation task to the target client if the client response information about the task information returned by the up-regulation client is received.
Optionally, the judging unit 63 further includes:
the detection unit is used for detecting whether the target client side meets a set uploading condition;
and the opening unit is used for opening the uploading authority of the target client if the target client meets the uploading condition.
Optionally, the computing unit 66 includes:
the coefficient determining unit is used for determining a weight coefficient and a scaling coefficient corresponding to the comparison item, wherein the weight coefficient indicates the importance degree of the comparison item;
and the weighting unit is used for scaling the on-site data and the default data corresponding to the comparison item according to the scaling coefficient, calculating an initial difference value between the scaled on-site data and the default data, and weighting the initial difference value according to the weighting coefficient to obtain a difference measurement value.
Therefore, the due-job investigation device based on data acquisition provided by the embodiment of the invention generates the adjustment report based on the field data, the default reasons of the target default enterprises and the enterprise response information, so that the auditor can rapidly analyze whether the enterprise to be adjusted is reliable according to the adjustment report, and the comprehensiveness of the adjustment report and the effect of the due-job investigation are improved.
Fig. 7 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 7, the terminal device 7 of this embodiment includes: a processor 70, a memory 71 and a computer program 72 stored in the memory 71 and executable on the processor 70, for example a due diligence program based on data acquisition. The processor 70, when executing the computer program 72, implements the steps of the various data acquisition-based due diligence method embodiments described above, such as steps S101 through S108 shown in fig. 1. Alternatively, the processor 70, when executing the computer program 72, performs the functions of the units of the data acquisition-based due diligence apparatus embodiments described above, such as the units 61-68 of fig. 6.
By way of example, the computer program 72 may be divided into one or more units, which are stored in the memory 71 and executed by the processor 70 to accomplish the present invention. The one or more units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 72 in the terminal device 7. For example, the computer program 72 may be divided into an allocation unit, a determination unit, a judgment unit, an acquisition unit, a violation acquisition unit, a calculation unit, a transmission unit, and a generation unit, each unit functioning specifically as follows:
The allocation unit is used for generating an adjustment task corresponding to an enterprise to be adjusted, and allocating the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
the determining unit is used for determining at least two items to be adjusted preset in the adjustment task and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
the judging unit is used for acquiring the on-site data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client and judging whether the registered data corresponding to the to-be-adjusted item and the on-site data are the same or not;
the acquisition unit is used for screening comparison items from the items to be adjusted if the registered data corresponding to all the items to be adjusted are the same as the field data;
the breach acquisition unit is used for acquiring breach data corresponding to the comparison items of at least two breach enterprises and breach reasons of the breach enterprises in a database;
the computing unit is used for computing a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the degree of difference between the default data and the field data;
The sending unit is used for determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and obtaining enterprise response information which is uploaded by the target client and corresponds to the reminding call;
and the generating unit is used for generating an adjustment report of the enterprise to be adjusted based on the field data, the default reasons of the target default enterprise and the enterprise response information.
The terminal device 7 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 70, a memory 71. It will be appreciated by those skilled in the art that fig. 7 is merely an example of the terminal device 7 and does not constitute a limitation of the terminal device 7, and may include more or less components than illustrated, or may combine certain components, or different components, e.g., the terminal device may further include an input-output device, a network access device, a bus, etc.
The processor 70 may be a central processing unit (Central Processing Unit, CPU), or may be another general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 71 may be an internal storage unit of the terminal device 7, such as a hard disk or a memory of the terminal device 7. The memory 71 may be an external storage device of the terminal device 7, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the terminal device 7. The memory 71 is used for storing the computer program as well as other programs and data required by the terminal device. The memory 71 may also be used for temporarily storing data that has been output or is to be output.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units is illustrated, and in practical application, the above-mentioned functional allocation may be performed by different functional units, that is, the internal structure of the terminal device is divided into different functional units, so as to perform all or part of the above-mentioned functions. The functional units in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present application. The specific working process of the units in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed terminal device and method may be implemented in other manners. For example, the above-described terminal device embodiments are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (4)
1. The due diligence investigation method based on data acquisition is characterized by comprising the following steps:
generating an adjustment task corresponding to an enterprise to be adjusted, and distributing the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
determining at least two items to be adjusted preset in the adjustment task, and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
acquiring field data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client, and judging whether the registered data corresponding to the to-be-adjusted item and the field data are the same or not;
If the registered data corresponding to all the items to be adjusted are the same as the on-site data, screening comparison items from the items to be adjusted;
obtaining the default data corresponding to the comparison items of at least two default enterprises in a database, wherein the default reasons of the default enterprises;
calculating a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the difference degree between the default data and the field data;
determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and acquiring enterprise response information corresponding to the reminding call, which is uploaded by the target client;
generating an adjustment report of the enterprise to be adjusted based on the field data, the default reason of the target default enterprise and the enterprise response information;
the generating the task of the adjustment corresponding to the enterprise to be adjusted comprises the following steps:
performing blacklist checking on enterprises to be tuned;
if the enterprise to be adjusted is not located in the preset blacklist, generating an adjustment task corresponding to the enterprise to be adjusted;
If the enterprise to be regulated is located in the blacklist, outputting an error prompt;
the assigning the task to the target client includes:
issuing the task information of the task to all the adjustment clients meeting the set adjustment conditions;
if the client response information about the task information returned by the tunable client is received, determining the tunable client corresponding to the earliest received client response information as a target client, and distributing the tunable task to the target client;
before the obtaining the field data, corresponding to the to-be-tuned item, of the to-be-tuned enterprise uploaded by the target client, the method further includes:
detecting whether the target client meets a set uploading condition;
if the target client side meets the uploading condition, opening the uploading authority of the target client side;
the calculating a difference measurement value between the breach data and the on-site data corresponding to the comparison item includes:
determining a weight coefficient and a scaling coefficient corresponding to the comparison item, wherein the weight coefficient indicates the importance degree of the comparison item;
Scaling the on-site data and the default data corresponding to the comparison item according to the scaling coefficient, calculating an initial difference value between the scaled on-site data and the default data, and weighting the initial difference value according to the weight coefficient to obtain a difference measurement value.
2. A data acquisition-based due diligence apparatus for implementing the data acquisition-based due diligence method of claim 1, the data acquisition-based due diligence apparatus comprising:
the allocation unit is used for generating an adjustment task corresponding to an enterprise to be adjusted, and allocating the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
the determining unit is used for determining at least two items to be adjusted preset in the adjustment task and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
the judging unit is used for acquiring the on-site data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client and judging whether the registered data corresponding to the to-be-adjusted item and the on-site data are the same or not;
The acquisition unit is used for screening comparison items from the items to be adjusted if the registered data corresponding to all the items to be adjusted are the same as the field data;
the breach acquisition unit is used for acquiring breach data corresponding to the comparison items of at least two breach enterprises and breach reasons of the breach enterprises in a database;
the computing unit is used for computing a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the degree of difference between the default data and the field data;
the sending unit is used for determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and obtaining enterprise response information which is uploaded by the target client and corresponds to the reminding call;
and the generating unit is used for generating an adjustment report of the enterprise to be adjusted based on the field data, the default reasons of the target default enterprise and the enterprise response information.
3. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
Generating an adjustment task corresponding to an enterprise to be adjusted, and distributing the adjustment task to a target client, wherein the target client is one of at least two adjustment clients;
determining at least two items to be adjusted preset in the adjustment task, and determining registration data of the enterprise to be adjusted, which correspond to the items to be adjusted;
acquiring field data, corresponding to the to-be-adjusted item, of the to-be-adjusted enterprise uploaded by the target client, and judging whether the registered data corresponding to the to-be-adjusted item and the field data are the same or not;
if the registered data corresponding to all the items to be adjusted are the same as the on-site data, screening comparison items from the items to be adjusted;
obtaining the default data corresponding to the comparison items of at least two default enterprises in a database, wherein the default reasons of the default enterprises;
calculating a difference measurement value between the default data and the field data corresponding to the comparison project, wherein the difference measurement value indicates the difference degree between the default data and the field data;
determining the default enterprise corresponding to the difference measurement value with the lowest value as a target default enterprise, sending a reminding call to the target client according to the default reason of the target default enterprise, and acquiring enterprise response information corresponding to the reminding call, which is uploaded by the target client;
Generating an adjustment report of the enterprise to be adjusted based on the field data, the default reason of the target default enterprise and the enterprise response information;
the generating the task of the adjustment corresponding to the enterprise to be adjusted comprises the following steps:
performing blacklist checking on enterprises to be tuned;
if the enterprise to be adjusted is not located in the preset blacklist, generating an adjustment task corresponding to the enterprise to be adjusted;
if the enterprise to be regulated is located in the blacklist, outputting an error prompt;
the assigning the task to the target client includes:
issuing the task information of the task to all the adjustment clients meeting the set adjustment conditions;
if the client response information about the task information returned by the tunable client is received, determining the tunable client corresponding to the earliest received client response information as a target client, and distributing the tunable task to the target client;
before the obtaining the field data, corresponding to the to-be-tuned item, of the to-be-tuned enterprise uploaded by the target client, the method further includes:
detecting whether the target client meets a set uploading condition;
If the target client side meets the uploading condition, opening the uploading authority of the target client side;
the calculating a difference measurement value between the breach data and the on-site data corresponding to the comparison item includes:
determining a weight coefficient and a scaling coefficient corresponding to the comparison item, wherein the weight coefficient indicates the importance degree of the comparison item;
scaling the on-site data and the default data corresponding to the comparison item according to the scaling coefficient, calculating an initial difference value between the scaled on-site data and the default data, and weighting the initial difference value according to the weight coefficient to obtain a difference measurement value.
4. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the due diligence method of claim 1.
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| CN112116274A (en) * | 2020-09-28 | 2020-12-22 | 中国建设银行股份有限公司 | Automatic generation method and device of survey report |
| CN112884573A (en) * | 2021-03-12 | 2021-06-01 | 中国工商银行股份有限公司 | Online exhaustive call processing method and device |
| CN113988871A (en) * | 2021-10-29 | 2022-01-28 | 平安银行股份有限公司 | Bidirectional authentication method, device, equipment and storage medium based on image recognition |
| CN116739396B (en) * | 2023-01-03 | 2024-08-06 | 国家电投集团科学技术研究院有限公司 | Intelligent evaluation service platform for new energy projects |
| CN116708702A (en) * | 2023-06-05 | 2023-09-05 | 深圳市银雁科技有限公司 | Video verification method, platform, medium and system for financial institution customer |
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