CN113469699A - Transfer processing method and device - Google Patents
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- CN113469699A CN113469699A CN202110805735.1A CN202110805735A CN113469699A CN 113469699 A CN113469699 A CN 113469699A CN 202110805735 A CN202110805735 A CN 202110805735A CN 113469699 A CN113469699 A CN 113469699A
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Abstract
The invention provides a transfer processing method and a device, after a customer authorizes a bank risk prevention and control function, a bank identifies the risk of each transfer of the customer, freezes the transfer under the condition of identifying the risk, informs an abnormal transfer contact person, executes the transfer after transfer confirmation information fed back by the abnormal transfer contact person, reduces the risk of transferring money by being cheated by old customers and other easily cheated customers, and ensures the safety of the transfer of the customer.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a transfer processing method and device.
Background
With the development of mobile payment, online transfer has become the most common payment method for people.
The old people are older and have poor ability to contact with social freshness information, so that the old people become a deceptive object of lawless persons. The old client has extremely high transfer risk, and is difficult to find in time after being cheated to transfer to lawless persons online, and cheated funds are difficult to recover in time, so that property loss of the old client is caused.
Disclosure of Invention
In view of the above, the invention provides a transfer processing method and device, after a customer authorizes a bank risk prevention and control function, a bank identifies the risk of each transfer of the customer, and freezes the transfer and informs an abnormal transfer contact person under the condition that the risk is identified, so that the transfer security of the customer is ensured.
In order to achieve the above purpose, the invention provides the following specific technical scheme:
a transfer processing method comprising:
under the condition of receiving a transfer request sent by a client, judging whether the client authorizes a risk prevention and control function;
under the condition that a client authorizes a risk prevention and control function, obtaining the transfer information and the historical transfer characteristic data of the client;
judging whether the account transfer has risks or not according to the account transfer information and the historical account transfer characteristic data of the client;
executing the transfer operation under the condition that the transfer does not have risk;
under the condition that the transfer is at risk, the transfer is frozen, and a customer is informed of a preset abnormal transfer contact person;
executing the transfer operation under the condition of receiving the confirmed transfer information fed back by the abnormal transfer contact person;
and under the condition of receiving the transfer canceling information fed back by the abnormal transfer contact person, terminating the transfer operation.
Optionally, the determining whether the client authorizes the risk prevention and control function includes:
acquiring a client identifier;
inquiring an authorized risk prevention and control function data table according to the client identification;
determining that the client has authorized the risk prevention and control function under the condition that the client identifier exists in the authorized risk prevention and control function data table;
and determining the unauthorized risk prevention and control function of the client under the condition that the client identifier does not exist in the authorized risk prevention and control function data table.
Optionally, the step of judging whether the current transfer has a risk according to the current transfer information and the historical transfer characteristic data of the client includes:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
and determining whether the transfer has a risk or not according to the risk prediction result.
Optionally, the step of judging whether the current transfer has a risk according to the current transfer information and the historical transfer characteristic data of the client includes:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
determining that no risk exists in the transfer under the condition that the risk prediction result indicates that no risk exists;
under the condition that the risk prediction result indicates that the risk exists, judging whether the transfer account transferred at this time is a legal industrial and commercial account or not;
if the account is not a legal industrial and commercial account, determining that the transfer has risk;
if the account is a legal industrial and commercial account, judging whether the transfer account is in a blacklist or not;
if the transfer is in the blacklist, determining that the transfer has risk;
and if the transfer is not in the blacklist, determining that no risk exists in the transfer.
Optionally, the risk prediction model is obtained by training a preset neural network model by using a training sample for marking whether a risk exists in advance, and the training sample includes historical transfer information of different clients and historical transfer characteristic data corresponding to the historical transfer information;
the historical transfer information includes: transfer time, transfer amount and transfer account;
the historical transfer characteristic data comprises: customer age, account balance, historical primary transfer amount interval, frequency of transfers to the transfer account.
Optionally, after notifying the customer of the preset abnormal transfer contact, the method further includes:
and executing the transfer operation if the feedback information of the abnormal transfer contact person is not received within the preset time length.
A transfer processing apparatus comprising:
the system comprises an authorization judging unit, a risk prevention and control unit and a risk management unit, wherein the authorization judging unit is used for judging whether a client authorizes a risk prevention and control function or not under the condition of receiving a transfer request sent by the client;
the data acquisition unit is used for acquiring the transfer information and the historical transfer characteristic data of the client under the condition that the client authorizes the risk prevention and control function;
the risk identification unit is used for judging whether the transfer has a risk or not according to the transfer information and the historical transfer characteristic data of the client, if the transfer does not have the risk, the transfer execution unit is triggered, and if the transfer has the risk, the transfer freezing unit is triggered;
the transfer execution unit is used for executing the transfer operation;
the transfer freezing unit is used for freezing the transfer;
the abnormal transfer information receiving and sending unit is used for informing a customer of a preset abnormal transfer contact person, triggering the transfer execution unit under the condition of receiving transfer confirmation information fed back by the abnormal transfer contact person, and triggering the transfer termination unit under the condition of receiving transfer cancellation information fed back by the abnormal transfer contact person;
and the transfer termination unit is used for terminating the transfer operation.
Optionally, the authorization determining unit is specifically configured to:
acquiring a client identifier;
inquiring an authorized risk prevention and control function data table according to the client identification;
determining that the client has authorized the risk prevention and control function under the condition that the client identifier exists in the authorized risk prevention and control function data table;
and determining the unauthorized risk prevention and control function of the client under the condition that the client identifier does not exist in the authorized risk prevention and control function data table.
Optionally, the risk identification unit is specifically configured to:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
and determining whether the transfer has a risk or not according to the risk prediction result.
Optionally, the risk identification unit is specifically configured to:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
determining that no risk exists in the transfer under the condition that the risk prediction result indicates that no risk exists;
under the condition that the risk prediction result indicates that the risk exists, judging whether the transfer account transferred at this time is a legal industrial and commercial account or not;
if the account is not a legal industrial and commercial account, determining that the transfer has risk;
if the account is a legal industrial and commercial account, judging whether the transfer account is in a blacklist or not;
if the transfer is in the blacklist, determining that the transfer has risk;
and if the transfer is not in the blacklist, determining that no risk exists in the transfer.
Optionally, the risk prediction model is obtained by training a preset neural network model by using a training sample for marking whether a risk exists in advance, and the training sample includes historical transfer information of different clients and historical transfer characteristic data corresponding to the historical transfer information;
the historical transfer information includes: transfer time, transfer amount and transfer account;
the historical transfer characteristic data comprises: customer age, account balance, historical primary transfer amount interval, frequency of transfers to the transfer account.
Optionally, the abnormal transfer information transceiver unit is further configured to trigger the transfer execution unit if the feedback information of the abnormal transfer contact is not received within a preset time period.
The invention is equivalent to the prior art, and has the following beneficial effects:
according to the transfer processing method disclosed by the invention, after a customer authorizes a bank risk prevention and control function, a bank identifies the risk of each transfer of the customer, the transfer is frozen under the condition that the risk is identified, an abnormal transfer contact is notified, and the transfer is executed after transfer confirmation information fed back by the abnormal transfer contact, so that the risk that old customers and other clients easy to cheat are cheated in transferring is reduced, and the transfer safety of the customer is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic flow chart of a transfer processing method disclosed in an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another transfer processing method disclosed in the embodiments of the present invention;
FIG. 3 is a schematic structural diagram of a transfer processing device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention discloses a transfer processing method, which is applied to a bank transfer system, after a customer authorizes a bank risk prevention and control function, a bank identifies the risk of each transfer of the customer, and freezes the transfer under the condition of identifying the risk and informs an abnormal transfer contact person, thereby ensuring the safety of the transfer of the customer.
Specifically, referring to fig. 1, the transfer processing method disclosed in this embodiment includes the following steps:
s101: receiving a transfer request sent by a client;
s102: judging whether the client authorizes the risk prevention and control function;
it can be understood that the client with the authorization risk prevention and control function can select authorization to a bank or not, after the client authorizes the bank with the risk prevention and control function, the bank can share and recognize each transfer of the client, the transfer operation is continuously executed under the condition that no risk exists in the transfer, the transfer is temporarily frozen under the condition that the risk exists in the transfer, an abnormal transfer contact preset by the client is informed to confirm, and whether the transfer operation is continuously executed or cancelled is determined according to the confirmation result.
The method for judging whether the client authorizes the risk prevention and control function comprises the following steps:
acquiring a client identifier from transfer information carried by the transfer request;
inquiring an authorized risk prevention and control function data table according to the client identification;
determining the authorized risk prevention and control function of the client under the condition that the client identifier exists in the authorized risk prevention and control function data table;
and under the condition that the client identification does not exist in the authorized risk prevention and control function data table, determining the unauthorized risk prevention and control function of the client.
If the client does not authorize the risk prevention and control function, executing S103: executing the account transfer operation;
if the client authorizes the risk prevention and control function, executing S104: obtaining the transfer information and the historical transfer characteristic data of the customer;
s105: judging whether the account transfer has risks or not according to the account transfer information and the historical account transfer characteristic data of the client;
according to the transfer information and the historical transfer characteristic data of the customer, a plurality of risk identification methods can be provided, such as a risk identification method based on a prediction rule, a risk identification method based on a machine learning model, a risk identification method based on an account blacklist and the like, and the method is not particularly limited.
Taking a risk identification method based on a prediction rule as an example, presetting a plurality of risk identification rules, if the transfer information and the historical transfer characteristic data of the client meet the risk identification rules, determining that the transfer has a risk, otherwise, determining that the transfer does not have a risk.
Taking a risk identification method based on a machine learning model as an example, the transfer information and the historical transfer characteristic data of the client are input into a machine learning model which is constructed in advance, and whether the transfer has risks or not is determined according to the input result of the machine learning model.
Taking a risk identification method based on an account blacklist as an example, writing known accounts with fraud records into the blacklist in advance, if the transfer account of the transfer is not a legal industrial and commercial account or in the blacklist, determining that the transfer has risks, otherwise, determining that the transfer does not have risks.
It should be noted that the above risk identification methods can be used alone or in combination in the actual risk identification process.
Executing S103 under the condition that the transfer does not have risk;
if the transfer is at risk, S106 is executed: freezing the transfer and informing a customer of a preset abnormal transfer contact;
when the client authorizes the bank risk prevention and control function, at least one abnormal transfer contact person needs to be set.
When a customer sets more than one abnormal transfer contact person, the main abnormal transfer contact person, namely the abnormal transfer contact person notified preferentially needs to be determined, and the next abnormal transfer contact person is notified in sequence under the condition that the main abnormal transfer contact person cannot be contacted.
The notification mode for notifying the abnormal transfer contact person can be various, such as short message notification, telephone notification, mobile banking push message notification and the like.
S107: receiving confirmed transfer information fed back by the abnormal transfer contact person, and then executing S103;
s108: receiving transfer canceling information fed back by the abnormal transfer contact person;
s109: the transfer operation is terminated.
The mode of the abnormal transfer contact person feedback information is consistent with the mode of the bank informing the abnormal transfer contact person.
Taking the short message notification as an example, the abnormal transfer contact replies 'Y' or 'yes' to confirm the transfer information, and replies 'N' or 'no' to cancel the transfer information.
Taking the telephone notification as an example, the abnormal transfer contact person informs the confirmed transfer or cancel transfer through telephone voice, and for the convenience of follow-up tracing, the telephone records under the condition of authorization.
Taking a message push notice of a mobile phone bank as an example, the abnormal account transfer contact confirms account transfer or cancels account transfer by operating the mobile phone bank.
Further, in order to avoid the problem that the normal transfer cannot be completed because the abnormal transfer contact person does not feed back information in time, the transfer operation is executed within a preset time length, for example, within 24 hours if the feedback information of the abnormal transfer contact person is not received.
Therefore, according to the transfer processing method disclosed by the embodiment, after a customer authorizes the bank risk prevention and control function, the bank identifies the risk of each transfer of the customer, freezes the transfer under the condition that the risk is identified, and informs an abnormal transfer contact person, and the transfer is executed after transfer confirmation information fed back by the abnormal transfer contact person, so that the risk that the old customer and other clients easy to cheat are subjected to transfer is reduced, and the transfer safety of the customer is ensured.
Referring to fig. 2, the embodiment discloses another transfer processing method for performing multiple risk identification on the transfer, which specifically includes the following steps:
s201: receiving a transfer request sent by a client;
s202: judging whether the client authorizes the risk prevention and control function;
if the client does not authorize the risk prevention and control function, executing S203: executing the account transfer operation;
if the client authorizes the risk prevention and control function, executing S204: obtaining the transfer information and the historical transfer characteristic data of the customer;
s205: inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
s206: judging whether a risk prediction result is that a risk exists or not;
if the risk prediction result indicates that no risk exists, S207 is executed: determining that no risk exists in the account transfer, and then executing S203;
if the risk prediction result indicates that there is a risk, S208 is executed: judging whether the transfer account of the transfer is a legal industrial and commercial account or not;
if not, executing S209: determining that the transfer has risk;
if the account is a legal industrial account, executing S210: judging whether the transfer account is in a blacklist or not;
if the name is in the blacklist, executing S209: determining that the transfer has risk;
if not, executing S207: and determining that no risk exists in the transfer.
If the transfer is not risky, S203 is executed;
if the transfer is at risk, S211 is executed: freezing the transfer and informing a customer of a preset abnormal transfer contact;
s212: receiving confirmed transfer information fed back by the abnormal transfer contact person, and then executing S203;
s213: receiving transfer canceling information fed back by the abnormal transfer contact person;
s214: the transfer operation is terminated.
According to the method and the device, after the transfer information and the historical transfer characteristic data of the customer are obtained, multiple recognition is carried out on the transfer, accurate risk recognition of the transfer is achieved based on risk recognition of a risk recognition model, risk recognition whether the transfer account is a legal industrial and commercial account or not and risk recognition whether the transfer account is in a blacklist or not, and therefore the safety of the customer transfer is guaranteed.
Specifically, the risk identification model in the embodiment is obtained by training a preset neural network model by using a training sample for marking whether risks exist in advance, wherein the training sample comprises historical transfer information of different clients and historical transfer characteristic data corresponding to the historical transfer information; the historical transfer information includes: transfer time, transfer amount and transfer account; the historical transfer characteristic data comprises: customer age, account balance, historical primary transfer amount interval, frequency of transfers to transfer accounts.
The method for acquiring the training sample comprises the following steps:
taking a target customer group identified by risks as an old customer as an example, acquiring historical transfer information of the old customer in historical transfer data, including transfer time, transfer amount and transfer account, marking whether risks exist for each historical transfer information according to subsequent tracking or informed cheating conditions, and respectively determining corresponding historical transfer characteristic data for each historical transfer information, wherein the historical transfer characteristic data comprises: customer age, account balance, historical primary transfer amount interval, frequency of transfers to transfer accounts.
And aiming at each historical transfer information, the client age is the client age when the transfer occurs, the account balance is the client balance when the transfer occurs, the historical main transfer amount interval is the main transfer amount interval obtained before the transfer occurs according to the client historical transfer amount, and the transfer frequency to the transfer account is the account transfer frequency of the client in the transfer to the historical transfer record.
After the training sample is obtained, determining a BP neural network structure according to the quantity of input data and the quantity of output data of the model, and further determining the quantity of parameters needing to be optimized in a genetic algorithm in the model training process. According to the kolmogorov principle, a three-layer BP neural network is enough to complete any mapping from n dimension to m dimension, and generally only one hidden layer is needed. And determining the number of nodes of the output layer by taking the number of the extracted characteristic data as the number of nodes of the input layer and taking whether risks exist as output data of the output layer, and determining the number of nodes of the hidden layer by adopting a trial and error method so as to determine the BP neural network structure. And (3) performing BP neural network training and learning by using the optimal individual output by the genetic algorithm as an initial weight and a threshold of the BP neural network, and establishing an accurate risk identification model.
Based on the method for processing account transfer disclosed in the above embodiment, the embodiment correspondingly discloses an apparatus for processing account transfer, please refer to fig. 3, and the apparatus includes:
an authorization judging unit 100, configured to judge whether a customer authorizes a risk prevention and control function when receiving a transfer request sent by the customer;
the data acquisition unit 200 is used for acquiring the transfer information and the historical transfer characteristic data of the client under the condition that the client authorizes the risk prevention and control function;
the risk identification unit 300 is used for judging whether the transfer has a risk or not according to the transfer information and the historical transfer characteristic data of the client, triggering the transfer execution unit 400 if the transfer does not have the risk, and triggering the transfer freezing unit 500 if the transfer has the risk;
the transfer execution unit 400 is configured to execute the transfer operation of this time;
the transfer freezing unit 500 is used for freezing the transfer;
an abnormal transfer information transceiving unit 600 for notifying a customer of an abnormal transfer contact preset, triggering the transfer execution unit 400 in case of receiving transfer confirmation information fed back by the abnormal transfer contact, and triggering the transfer termination unit 700 in case of receiving transfer cancellation information fed back by the abnormal transfer contact;
the transfer termination unit 700 is configured to terminate the transfer operation.
Optionally, the authorization determining unit 100 is specifically configured to:
acquiring a client identifier;
inquiring an authorized risk prevention and control function data table according to the client identification;
determining that the client has authorized the risk prevention and control function under the condition that the client identifier exists in the authorized risk prevention and control function data table;
and determining the unauthorized risk prevention and control function of the client under the condition that the client identifier does not exist in the authorized risk prevention and control function data table.
Optionally, the risk identifying unit 300 is specifically configured to:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
and determining whether the transfer has a risk or not according to the risk prediction result.
Optionally, the risk identifying unit 300 is specifically configured to:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
determining that no risk exists in the transfer under the condition that the risk prediction result indicates that no risk exists;
under the condition that the risk prediction result indicates that the risk exists, judging whether the transfer account transferred at this time is a legal industrial and commercial account or not;
if the account is not a legal industrial and commercial account, determining that the transfer has risk;
if the account is a legal industrial and commercial account, judging whether the transfer account is in a blacklist or not;
if the transfer is in the blacklist, determining that the transfer has risk;
and if the transfer is not in the blacklist, determining that no risk exists in the transfer.
Optionally, the risk prediction model is obtained by training a preset neural network model by using a training sample for marking whether a risk exists in advance, and the training sample includes historical transfer information of different clients and historical transfer characteristic data corresponding to the historical transfer information;
the historical transfer information includes: transfer time, transfer amount and transfer account;
the historical transfer characteristic data comprises: customer age, account balance, historical primary transfer amount interval, frequency of transfers to the transfer account.
Optionally, the abnormal transfer information transceiver unit 600 is further configured to trigger the transfer execution unit if the feedback information of the abnormal transfer contact is not received within a preset time period.
According to the transfer processing device disclosed by the embodiment, after a customer authorizes the bank risk prevention and control function, the bank conducts risk identification on each transfer of the customer, the transfer is frozen under the condition that the risk is identified, an abnormal transfer contact is notified, the transfer is executed after transfer confirmation information fed back by the abnormal transfer contact, the risk that old customers and other clients easy to cheat are cheated in transfer is reduced, and the transfer safety of the customer is guaranteed.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above embodiments can be combined arbitrarily, and the features described in the embodiments in the present specification can be replaced or combined with each other in the above description of the disclosed embodiments, so that those skilled in the art can implement or use the present application.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of account transfer processing, comprising:
under the condition of receiving a transfer request sent by a client, judging whether the client authorizes a risk prevention and control function;
under the condition that a client authorizes a risk prevention and control function, obtaining the transfer information and the historical transfer characteristic data of the client;
judging whether the account transfer has risks or not according to the account transfer information and the historical account transfer characteristic data of the client;
executing the transfer operation under the condition that the transfer does not have risk;
under the condition that the transfer is at risk, the transfer is frozen, and a customer is informed of a preset abnormal transfer contact person;
executing the transfer operation under the condition of receiving the confirmed transfer information fed back by the abnormal transfer contact person;
and under the condition of receiving the transfer canceling information fed back by the abnormal transfer contact person, terminating the transfer operation.
2. The method of claim 1, wherein determining whether the customer authorizes the risk prevention and control function comprises:
acquiring a client identifier;
inquiring an authorized risk prevention and control function data table according to the client identification;
determining that the client has authorized the risk prevention and control function under the condition that the client identifier exists in the authorized risk prevention and control function data table;
and determining the unauthorized risk prevention and control function of the client under the condition that the client identifier does not exist in the authorized risk prevention and control function data table.
3. The method as recited in claim 1, wherein the determining whether the transfer is at risk according to the transfer information and the historical transfer characteristic data of the customer comprises:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
and determining whether the transfer has a risk or not according to the risk prediction result.
4. The method as recited in claim 1, wherein the determining whether the transfer is at risk according to the transfer information and the historical transfer characteristic data of the customer comprises:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
determining that no risk exists in the transfer under the condition that the risk prediction result indicates that no risk exists;
under the condition that the risk prediction result indicates that the risk exists, judging whether the transfer account transferred at this time is a legal industrial and commercial account or not;
if the account is not a legal industrial and commercial account, determining that the transfer has risk;
if the account is a legal industrial and commercial account, judging whether the transfer account is in a blacklist or not;
if the transfer is in the blacklist, determining that the transfer has risk;
and if the transfer is not in the blacklist, determining that no risk exists in the transfer.
5. The method according to claim 3 or 4, wherein the risk prediction model is obtained by training a preset neural network model in advance by using a training sample for marking whether risks exist, and the training sample comprises historical transfer information of different clients and historical transfer characteristic data corresponding to the historical transfer information;
the historical transfer information includes: transfer time, transfer amount and transfer account;
the historical transfer characteristic data comprises: customer age, account balance, historical primary transfer amount interval, frequency of transfers to the transfer account.
6. The method as claimed in claim 1, wherein after notifying the customer of the pre-set abnormal transfer contact, the method further comprises:
and executing the transfer operation if the feedback information of the abnormal transfer contact person is not received within the preset time length.
7. A transfer processing apparatus, comprising:
the system comprises an authorization judging unit, a risk prevention and control unit and a risk management unit, wherein the authorization judging unit is used for judging whether a client authorizes a risk prevention and control function or not under the condition of receiving a transfer request sent by the client;
the data acquisition unit is used for acquiring the transfer information and the historical transfer characteristic data of the client under the condition that the client authorizes the risk prevention and control function;
the risk identification unit is used for judging whether the transfer has a risk or not according to the transfer information and the historical transfer characteristic data of the client, if the transfer does not have the risk, the transfer execution unit is triggered, and if the transfer has the risk, the transfer freezing unit is triggered;
the transfer execution unit is used for executing the transfer operation;
the transfer freezing unit is used for freezing the transfer;
the abnormal transfer information receiving and sending unit is used for informing a customer of a preset abnormal transfer contact person, triggering the transfer execution unit under the condition of receiving transfer confirmation information fed back by the abnormal transfer contact person, and triggering the transfer termination unit under the condition of receiving transfer cancellation information fed back by the abnormal transfer contact person;
and the transfer termination unit is used for terminating the transfer operation.
8. The apparatus according to claim 7, wherein the authorization determination unit is specifically configured to:
acquiring a client identifier;
inquiring an authorized risk prevention and control function data table according to the client identification;
determining that the client has authorized the risk prevention and control function under the condition that the client identifier exists in the authorized risk prevention and control function data table;
and determining the unauthorized risk prevention and control function of the client under the condition that the client identifier does not exist in the authorized risk prevention and control function data table.
9. The apparatus according to claim 7, wherein the risk identification unit is specifically configured to:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
and determining whether the transfer has a risk or not according to the risk prediction result.
10. The apparatus according to claim 7, wherein the risk identification unit is specifically configured to:
inputting the transfer information and the historical transfer characteristic data of the customer into a pre-constructed risk prediction model to obtain a risk prediction result;
determining that no risk exists in the transfer under the condition that the risk prediction result indicates that no risk exists;
under the condition that the risk prediction result indicates that the risk exists, judging whether the transfer account transferred at this time is a legal industrial and commercial account or not;
if the account is not a legal industrial and commercial account, determining that the transfer has risk;
if the account is a legal industrial and commercial account, judging whether the transfer account is in a blacklist or not;
if the transfer is in the blacklist, determining that the transfer has risk;
and if the transfer is not in the blacklist, determining that no risk exists in the transfer.
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| CN202110805735.1A CN113469699A (en) | 2021-07-16 | 2021-07-16 | Transfer processing method and device |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113888153A (en) * | 2021-11-10 | 2022-01-04 | 建信金融科技有限责任公司 | Transfer abnormity prediction method, device, equipment and readable storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113888153A (en) * | 2021-11-10 | 2022-01-04 | 建信金融科技有限责任公司 | Transfer abnormity prediction method, device, equipment and readable storage medium |
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