CN115376254A - Artificial intelligence-based anti-swallow method and related equipment - Google Patents
Artificial intelligence-based anti-swallow method and related equipment Download PDFInfo
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Abstract
The anti-swallowing method based on artificial intelligence and the related equipment can be applied to the field of artificial intelligence or the field of finance, and the anti-swallowing method based on artificial intelligence and the related equipment are applied to ATM equipment and can be used for collecting biological characteristic information of a client transacting transaction business on the ATM equipment; obtaining the operation duration of each step of transacting business on ATM equipment by a client; and determining whether the client belongs to a group easy to swallow the card or not by utilizing the biological characteristic information and the operation duration, and if so, sending preset card-swallowing risk prompt information to the client. According to the method and the system, potential easily-swallowed card clients can be identified in advance through the biological characteristic information of the clients and the operation frequency during transaction service handling, the card-swallowing risk prompt information is sent out, the clients are helped to know the card-swallowing risk in advance, and the card-swallowing event is prevented from happening.
Description
Technical Field
The disclosure relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based anti-swallowing method and related equipment.
Background
Most of the existing ATM equipment is not provided with a card swallowing prevention protection mechanism, the potential card swallowing risks of a client cannot be found in advance, and when the card swallowing condition occurs, the client usually needs to take a valid certificate to a network point where the card swallowing equipment is located to confirm the identity and then can take back the card, so that the flow is complicated.
Disclosure of Invention
In view of the above problems, the present disclosure provides an artificial intelligence based anti-jamming method and related apparatus, which overcome or at least partially solve the above problems, and the technical solutions are as follows:
an artificial intelligence-based anti-swallow card method applied to an ATM device, the method comprising:
collecting biometric information of a customer transacting transaction services on the ATM device;
obtaining the operation duration of each step of transacting the transaction service on the ATM equipment by the client;
and determining whether the client belongs to a group easy to swallow the card or not by using the biological characteristic information and the operation duration, and if so, sending preset card-swallowing risk prompt information to the client.
Optionally, after sending the preset card-swallowing risk prompt message to the client, the method further includes:
and under the condition that the ATM equipment buckles the bank card of the customer, if the biological characteristic information input by the customer is obtained within a preset card swallowing self-service retrieving time range, returning the buckled bank card to the customer.
Optionally, the determining, by using the biometric information and the operation duration, whether the customer belongs to a swallowable card group includes:
inputting the biological characteristic information into a pre-trained age prediction model to obtain an age group which is output by the age prediction model and corresponds to the biological characteristic information;
calculating the operation duration of each step to obtain the average operation duration of each step when the client transacts the transaction service;
and under the condition that the age group is a preset elderly group or the average operation time length is greater than a preset time length threshold value, determining that the client belongs to a group easy to swallow cards.
Optionally, the biometric information includes face information and fingerprint information.
An artificial intelligence-based card swallowing prevention device applied to ATM equipment comprises: a biological characteristic information acquisition unit, an operation duration acquisition unit, an easy card-swallowing client determination unit and a card-swallowing risk prompt unit,
the biological characteristic information acquisition unit is used for acquiring biological characteristic information of a client transacting transaction business on the ATM equipment;
the operation duration obtaining unit is used for obtaining the operation duration of each step of transacting the transaction service on the ATM equipment by the client;
the easy-to-swallow card client determining unit is used for determining whether the client belongs to an easy-to-swallow card group or not by utilizing the biological characteristic information and the operation duration, and if so, triggering the card-swallowing risk prompting unit;
and the card-swallowing risk prompt unit is used for sending preset card-swallowing risk prompt information to the client.
Optionally, the apparatus further comprises: the bank card is returned to the unit,
the bank card returning unit is used for sending preset card swallowing risk prompt information to the customer, and then under the condition that the ATM equipment is used for buckling the bank card of the customer, if the biological characteristic information input by the customer is obtained within the preset card swallowing self-service fetching time range, the bank card is returned to the customer.
Optionally, the easy-swallow card client determining unit includes: a first obtaining subunit, a second obtaining subunit and an easy-to-swallow card group determining subunit,
the first obtaining subunit is configured to input the biometric information into a pre-trained age prediction model, and obtain an age group corresponding to the biometric information and output by the age prediction model;
the second obtaining subunit is configured to calculate the operation duration of each step, and obtain an average operation duration of each step when the client handles the transaction service;
the easy-to-swallow card group determining subunit is configured to determine that the customer belongs to the easy-to-swallow card group when the age group is a preset elderly group or the average operation time length is greater than a preset time length threshold.
Optionally, the biometric information includes face information and fingerprint information.
A computer-readable storage medium having stored thereon a program which, when executed by a processor, implements an artificial intelligence based anti-swallowing method as in any one of the above.
An ATM apparatus comprising at least one processor, and at least one memory connected to the processor, a bus; the processor and the memory complete mutual communication through the bus; the processor is configured to call program instructions in the memory to perform any of the artificial intelligence based anti-swallow card methods described above.
By means of the technical scheme, the anti-swallowing card method based on artificial intelligence and the related equipment can be applied to the field of artificial intelligence or finance, and the anti-swallowing card method based on artificial intelligence is applied to ATM equipment and can be used for collecting biological characteristic information of a client transacting transaction business on the ATM equipment; obtaining the operation duration of each step of transacting business on ATM equipment by a client; and determining whether the client belongs to a group easy to swallow the card or not by utilizing the biological characteristic information and the operation duration, and if so, sending preset card-swallowing risk prompt information to the client. According to the method and the system, potential easily-swallowed card clients can be identified in advance through the biological characteristic information of the clients and the operation frequency during transaction service handling, the card-swallowing risk prompt information is sent out, the clients are helped to know the card-swallowing risk in advance, and the card-swallowing event is prevented from happening.
The foregoing description is only an overview of the technical solutions of the present disclosure, and the embodiments of the present disclosure are described below in order to make the technical means of the present disclosure more clearly understood and to make the above and other objects, features, and advantages of the present disclosure more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the disclosure. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a schematic flow chart diagram illustrating an embodiment of an artificial intelligence-based anti-transcytosis method provided by an embodiment of the present disclosure;
fig. 2 is a schematic flow chart diagram illustrating another implementation manner of an artificial intelligence-based anti-transcytosis method according to an embodiment of the disclosure;
fig. 3 is a schematic flow chart diagram illustrating another implementation manner of the artificial intelligence based anti-transcytosis method according to the embodiment of the disclosure;
fig. 4 shows a schematic structural diagram of an artificial intelligence-based anti-swallow card device provided in an embodiment of the disclosure;
fig. 5 shows a schematic structural diagram of an ATM apparatus provided by an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The artificial intelligence anti-card-swallowing method provided by the embodiment of the disclosure can be applied to ATM (Automated Teller Machine) equipment. The ATM device swallows the card, i.e., the ATM device places the customer's bank card in a retaining manner. In general, the reasons why the ATM device holds the bank card include: firstly, the card is forgotten to be taken after the transaction of the card holder is finished for more than 30 seconds, and the ATM equipment automatically swallows the card to prevent the card from being picked up by others. Secondly, the machine tool or the system of the ATM equipment is in failure. And thirdly, card swallowing processing is carried out on the loss report card, the stolen card, the fraud card and the like according to the requirements of the card issuing bank.
In daily life, many people have a history of card swallowing by ATM devices. Generally, the cardholder needs to go to the website where the card-swallowing device is located to handle the "card-retrieving" service by using the valid certificate on the next day. However, when the card-swallowing point is far away or the "swallowed" bank card and the ATM device are not a bank, the card-holding customer may experience very badly. According to statistics, most of 'card swallowing' is caused by forgetting to take the card after the cardholder finishes the transaction for more than 30 seconds.
As shown in fig. 1, a schematic flow chart of an implementation manner of an artificial intelligence-based anti-jamming method provided in an embodiment of the present disclosure may include:
s100, collecting the biological characteristic information of a client transacting transaction business on the ATM equipment.
Wherein the transaction may be a banking transaction provided to the cardholder on an ATM device. Alternatively, the transaction service may include a deposit service, a withdrawal service, and a transfer service.
Alternatively, the biometric information may be information characterizing a unique identity of the customer. Optionally, the biometric information includes face information and fingerprint information.
It will be appreciated that the ATM device may be provided with a face capture camera and a fingerprint capture device. The embodiment of the disclosure can collect the face information of the client through the face collecting camera and collect the fingerprint information of the client through the fingerprint collecting equipment.
S200, obtaining the operation duration of each step of transacting business on the ATM equipment by the client.
It will be appreciated that the transaction at an ATM facility requires a number of steps to complete. For example: if the transaction service is a withdrawal, the transaction steps of the transaction service may include inputting a withdrawal password, inputting a withdrawal amount, and inputting a short message verification code.
The embodiment of the disclosure respectively times the staying time of the client on each operation page for transacting the transaction service, and obtains the operation duration of the client in each step.
S300, determining whether the customer belongs to the swallowable card group or not by using the biological characteristic information and the operation duration, and if so, executing the step S400.
The easily swallowed card group can be a customer group which is preset by a bank and is easily buckled with a bank card by the ATM equipment.
Optionally, based on the method shown in fig. 1, as shown in fig. 2, a schematic flow chart of another implementation manner of the artificial intelligence-based anti-jamming method provided in the embodiment of the present disclosure, step S300 may include:
and S310, inputting the biological characteristic information into a pre-trained age prediction model, and obtaining an age group which is output by the age prediction model and corresponds to the biological characteristic information.
The age prediction model may be a neural network model. The age presetting model can judge the biological characteristic information, identify the age of the client and further determine the age group to which the age belongs. Alternatively, the age group may include a preset elderly group and a preset non-elderly group. The age range of the pre-set elderly population group may be 60 years or older. The pre-set non-elderly group may be under the age of 60.
And S320, calculating the operation duration of each step to obtain the average operation duration of each step when the client transacts business.
The method and the device for processing the transaction service can calculate the operation duration of each step through a client operation perception algorithm constructed by utilizing the probability distribution function, so that the average operation duration of each step when a client transacts the transaction service is determined.
The customer operation awareness algorithm is based on the notion of a statistical probability distribution function, and is generated based on a large amount of historical ATM customer usage data (average duration of operation per step in the transaction process).
S330, determining that the client belongs to the group easy to swallow the card under the condition that the age group is a preset old people group or the average operation time length is larger than a preset time length threshold value.
The preset time threshold value can be set according to actual requirements.
And S400, sending preset card swallowing risk prompt information to the client.
The preset card-swallowing risk prompt message can be a risk prompt message provided by at least one of a text prompt mode, a voice prompt mode, a short message mode and a telephone prompt mode.
The anti-card swallowing method based on the artificial intelligence can be applied to the field of artificial intelligence or the field of finance, is applied to ATM equipment, and can acquire biological characteristic information of a client transacting transaction business on the ATM equipment; obtaining the operation duration of each step of transacting business on the ATM equipment by a client; and determining whether the client belongs to a group easy to swallow the card or not by utilizing the biological characteristic information and the operation duration, and if so, sending preset card-swallowing risk prompt information to the client. According to the method and the system, potential easily-swallowed card clients can be identified in advance through the biological characteristic information of the clients and the operation frequency during transaction service handling, the card-swallowing risk prompt information is sent out, the clients are helped to know the card-swallowing risk in advance, and the card-swallowing event is prevented from happening.
Optionally, based on the method shown in fig. 1, as shown in fig. 3, a schematic flow chart of another implementation manner of the artificial intelligence based anti-blocking method provided in the embodiment of the present disclosure may further include, after step S400:
s500, under the condition that the ATM device buckles the bank card of the customer, if the biological characteristic information input by the customer is obtained within the preset card swallowing self-service retrieving time range, the buckled bank card is returned to the customer.
The preset card-retaining self-service retrieval time range can be set according to actual requirements. The embodiment of the disclosure can start timing after the ATM equipment buckles the bank card, and the customer can take back the card through the biological characteristic information within the preset card-swallowing self-help taking-back time range. After exceeding the preset self-service card-retaining time range, the customer can only retain the bank card by conventional means.
It can be understood that, in the embodiment of the present disclosure, the biometric information input by the client this time may be compared with the biometric information obtained in step S100 for identification, and after the identification is passed, the buckled bank card is returned to the client.
The disclosed embodiment provides a remedy means after the card is buckled, and the card retrieving function is realized by providing the biological characteristic information, so that the card can be retrieved by the biological characteristic information within a period of time after the card is swallowed by the ATM equipment.
Alternatively, the ATM device may be provided with a card buffer. The ATM equipment can place the bank card in the card buffer area in a preset card swallowing self-service fetching time range so as to be distinguished from a conventional card swallowing and placing area of the ATM equipment, and a customer can conveniently and quickly fetch the card through the biological characteristic information within a period of time after the card is swallowed by the ATM equipment.
Although the operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
Corresponding to the above method embodiment, an embodiment of the present disclosure further provides an artificial intelligence-based card swallowing prevention device, which is applied to an ATM device, and as shown in fig. 4, a schematic structural diagram of the artificial intelligence-based card swallowing prevention device provided in the embodiment of the present disclosure may include: a biometric information acquisition unit 100, an operation duration acquisition unit 200, an easy-to-swallow card client determination unit 300 and a card-swallow risk prompt unit 400.
The biometric information collecting unit 100 is used for collecting the biometric information of the client transacting transaction business on the ATM equipment.
An operation duration obtaining unit 200 is used for obtaining the operation duration of each step of transaction service transacted by a client on the ATM equipment.
The easy-to-swallow card client determining unit 300 is used for determining whether the client belongs to the easy-to-swallow card group or not by utilizing the biological characteristic information and the operation duration, and if so, triggering the card-swallowing risk prompting unit 400.
And a card-swallowing risk prompting unit 400, configured to send preset card-swallowing risk prompting information to the client.
Optionally, the artificial intelligence-based card swallowing prevention device may further include: and a bank card returning unit.
And the bank card returning unit is used for returning the buckled bank card to the customer if the biometric information input by the customer is obtained within the self-service withdrawing time range of the preset card swallowing under the condition that the ATM equipment buckles the bank card of the customer after the preset card swallowing risk prompting information is sent to the customer by the card swallowing risk prompting unit 400.
Optionally, the easy-swallow card client determining unit 300 includes: the device comprises a first obtaining subunit, a second obtaining subunit and an easily-swallowed card group determining subunit.
And the first obtaining subunit is used for inputting the biological characteristic information into a pre-trained age prediction model and obtaining the age group which is output by the age prediction model and corresponds to the biological characteristic information.
And the second obtaining subunit is used for calculating the operation duration of each step to obtain the average operation duration of each step when the client transacts the transaction service.
And the easy-to-swallow card group determining subunit is used for determining that the client belongs to the easy-to-swallow card group under the condition that the age group is a preset old people group or the average operation time length is greater than a preset time length threshold value.
Optionally, the biometric information includes face information and fingerprint information.
The anti-card swallowing device based on the artificial intelligence can be applied to the field of the artificial intelligence or the field of finance, is applied to ATM equipment, and can acquire biological characteristic information of a client transacting business on the ATM equipment; obtaining the operation duration of each step of transacting business on ATM equipment by a client; and determining whether the client belongs to a group easy to swallow the card or not by utilizing the biological characteristic information and the operation duration, and if so, sending preset card-swallowing risk prompt information to the client. According to the method and the system, potential easily-swallowed card clients can be identified in advance through the biological characteristic information of the clients and the operation frequency during transaction service handling, and the card-swallowing risk prompt information is sent out to help the clients to know the card-swallowing risk in advance and prevent the card-swallowing event.
With regard to the apparatus in the above-described embodiment, the specific manner in which each unit performs the operation has been described in detail in the embodiment related to the method, and will not be described in detail here.
The card swallowing prevention device based on artificial intelligence comprises a processor and a memory, wherein the biological characteristic information acquisition unit 100, the operation duration acquisition unit 200, the easy-to-swallow card client determination unit 300, the card swallowing risk prompt unit 400 and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more than one, potential easily-swallowed card customers can be identified in advance by adjusting kernel parameters according to the biological characteristic information of the customers and the operation frequency during transaction service handling, card-swallowing risk prompt information is sent out, the customers are helped to know the card-swallowing risk in advance, and the card-swallowing event is prevented from happening.
The disclosed embodiments provide a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the artificial intelligence based anti-swallow card method.
The embodiment of the disclosure provides a processor, which is configured to execute a program, where the program executes the artificial intelligence based anti-swallow card method during the running.
As shown in fig. 5, an ATM apparatus 1000 is provided in accordance with an embodiment of the present disclosure, the ATM apparatus 1000 includes at least one processor 1001, and at least one memory 1002, bus 1003 coupled to the processor 1001; the processor 1001 and the memory 1002 complete communication with each other through the bus 1003; the processor 1001 is configured to call the program instructions in the memory 1002 to execute the artificial intelligence based anti-swallow card method. The ATM device herein may be a server, PC, PAD, handset, etc.
The present disclosure also provides a computer program product adapted to perform a program for initializing the following method steps when executed on an ATM apparatus:
an anti-card swallowing method based on artificial intelligence is applied to ATM equipment, and comprises the following steps:
collecting the biological characteristic information of a client transacting transaction business on ATM equipment;
obtaining the operation duration of each step of transacting business on ATM equipment by a client;
and determining whether the client belongs to a group easy to swallow the card or not by utilizing the biological characteristic information and the operation duration, and if so, sending preset card-swallowing risk prompt information to the client.
Optionally, after sending the preset card-swallowing risk prompt message to the client, the method further includes:
under the condition that the ATM equipment buckles the bank card of the customer, if the biological characteristic information input by the customer is obtained within the preset card swallowing self-service retrieving time range, the buckled bank card is returned to the customer.
Optionally, determining whether the client belongs to the swallowable card group by using the biometric information and the operation duration includes:
inputting the biological characteristic information into a pre-trained age prediction model to obtain an age group which is output by the age prediction model and corresponds to the biological characteristic information;
calculating the operation duration of each step to obtain the average operation duration of each step of transacting business by a client;
and under the condition that the age group is a preset old people group or the average operation time length is greater than a preset time length threshold value, determining that the client belongs to the easily swallowed card group.
Optionally, the biometric information includes face information and fingerprint information.
It should be noted that the artificial intelligence based anti-card swallowing method and the related device provided by the disclosure can be used in the field of artificial intelligence or financial field. The above description is merely an example, and does not limit the application field of the artificial intelligence-based anti-jamming method and the related device provided by the present disclosure.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, ATM devices (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, an ATM apparatus includes one or more processors (CPUs), memory, and a bus. The ATM device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory in a computer readable medium, random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.
Computer-readable media, including both permanent and non-permanent, removable and non-removable media, may implement the information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
In the description of the present disclosure, it is to be understood that the directions or positional relationships indicated as referring to the terms "upper", "lower", "front", "rear", "left" and "right", etc., are based on the directions or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the positions or elements referred to must have specific directions, be constituted and operated in specific directions, and thus, are not to be construed as limitations of the present disclosure.
It is 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. It should also be noted that 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 a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The above are merely examples of the present disclosure, and are not intended to limit the present disclosure. Various modifications and variations of this disclosure will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the scope of the claims of the present disclosure.
Claims (10)
1. An artificial intelligence-based anti-swallow card method, which is applied to an ATM device, and comprises the following steps:
collecting biometric information of a customer transacting transaction services on the ATM device;
obtaining the operation duration of each step of transacting the transaction service on the ATM equipment by the client;
and determining whether the client belongs to a group easy to swallow the card or not by using the biological characteristic information and the operation duration, and if so, sending preset card-swallowing risk prompt information to the client.
2. The method of claim 1, wherein after sending a preset card-swallowing risk hint message to the client, the method further comprises:
and under the condition that the ATM equipment buckles the bank card of the customer, if the biological characteristic information input by the customer is obtained within a preset card swallowing self-service retrieving time range, returning the buckled bank card to the customer.
3. The method of claim 1, wherein said determining whether said customer belongs to a swallowable card group using said biometric information and said duration of operation comprises:
inputting the biological characteristic information into a pre-trained age prediction model to obtain an age group which is output by the age prediction model and corresponds to the biological characteristic information;
calculating the operation duration of each step to obtain the average operation duration of each step when the client transacts the transaction service;
and under the condition that the age group is a preset old people group or the average operation time is greater than a preset time threshold, determining that the client belongs to a swallowable card group.
4. The method of claim 1, wherein the biometric information comprises face information and fingerprint information.
5. An artificial intelligence-based card swallowing prevention device is applied to ATM equipment, and the device comprises: a biological characteristic information acquisition unit, an operation duration acquisition unit, an easy card-swallowing client determination unit and a card-swallowing risk prompt unit,
the biological characteristic information acquisition unit is used for acquiring biological characteristic information of a client transacting transaction business on the ATM equipment;
the operation duration obtaining unit is used for obtaining the operation duration of each step of transacting the transaction service on the ATM equipment by the client;
the easy-to-swallow card client determining unit is used for determining whether the client belongs to an easy-to-swallow card group or not by utilizing the biological characteristic information and the operation duration, and if so, triggering the card-swallowing risk prompting unit;
and the card-swallowing risk prompt unit is used for sending preset card-swallowing risk prompt information to the client.
6. The apparatus of claim 5, further comprising: the bank card is returned to the unit,
and the bank card returning unit is used for returning the buckled bank card to the customer if the biological characteristic information input by the customer is obtained within a preset card-swallowing self-service withdrawing time range under the condition that the ATM equipment buckles the bank card of the customer after the preset card-swallowing risk prompting unit sends preset card-swallowing risk prompting information to the customer.
7. The apparatus of claim 5, wherein the easy-swallow card client determination unit comprises: a first obtaining subunit, a second obtaining subunit and an easy-to-swallow card group determining subunit,
the first obtaining subunit is configured to input the biometric information into a pre-trained age prediction model, and obtain an age group corresponding to the biometric information and output by the age prediction model;
the second obtaining subunit is configured to calculate the operation duration of each step, and obtain an average operation duration of each step when the client handles the transaction service;
the easy-to-swallow card group determining subunit is configured to determine that the customer belongs to the easy-to-swallow card group when the age group is a preset elderly group or the average operation time length is greater than a preset time length threshold.
8. The apparatus of claim 5, wherein the biometric information comprises face information and fingerprint information.
9. A computer-readable storage medium on which a program is stored, which, when executed by a processor, implements the artificial intelligence based anti-swallow card method of any one of claims 1 to 4.
10. An ATM apparatus comprising at least one processor, and at least one memory connected to the processor, a bus; the processor and the memory complete mutual communication through the bus; the processor is configured to invoke program instructions in the memory to perform the artificial intelligence based anti-swallow card method of any one of claims 1 to 4.
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