Data processing method and device, storage medium and electronic equipment

Abstract

The invention discloses a data processing method and device, a storage medium and electronic equipment. The method relates to the technical field of RPA. The method comprises the steps that first data information of a to-be-processed risk event is captured from a risk system of a financial institution through robot process automation; creating a risk event data table based on the first data information and information of a target object corresponding to the risk event; and sending a target message to the target object based on the risk event data table to indicate the target object to process the risk event. Through the event processing method and device, the problem that the event processing efficiency is low due to the fact that various events in risk management and control need to be inquired manually and then personnel corresponding to the various events are notified to process in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the field of RPA technology, and specifically, to a data processing method and device, a storage medium, and an electronic device. Background Art

[0002] At present, the intelligent management system for operational risks in financial institutions involves many links, and the deadlines for each link are different, which leads to the system management post to query relevant risk monitoring data from multiple modules every day, check the data information and convey it to the corresponding assessors for supervision, which is very easy to form omissions. For risk events that are not closed-loop, managers are required to promptly notify the risk assessors corresponding to each event within the specified time, reminding them to complete the correction of risk events on time. If managers are negligent, risk events will not be handled in time, affecting risk event handling. In addition, managers need to check and issue notifications every day, which is time-consuming and laborious. For events that need to be identified, the current interface information display is relatively complicated. It takes multiple clicks to view the main event number, customer name, customer number, account opening date, card number, account number and other related information, which is relatively cumbersome. In addition, the information obtained is relatively single, which is not conducive to the identification personnel to make user risk judgments and thus identify the event.

[0003] Currently, no effective solution has been proposed to address the problem that related technologies require manual methods to query various events in risk management and control, and then notify the corresponding personnel of each event to handle it, resulting in low efficiency in event handling. Summary of the invention

[0004] The main purpose of this application is to provide a data processing method and device, a storage medium and an electronic device to solve the problem that the relevant technology requires manual query of various events in risk management and control, and then notifies the corresponding personnel of each event to handle it, resulting in low efficiency in event processing.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a data processing method is provided. The method comprises: capturing first data information of a risk event to be processed from a risk system of a financial institution through robotic process automation; creating a risk event data table based on the first data information and information of a target object corresponding to the risk event; and sending a target message to the target object based on the risk event data table to instruct the target object to process the risk event.

[0006] Furthermore, capturing first data information of risk events to be processed from the risk system of a financial institution through robotic process automation includes: sending a login request to the risk system through robotic process automation, wherein after receiving the login request, the risk system jumps to a login interface; inputting the robotic process automation identity information on the login interface, wherein if the robotic process automation identity information is verified, jumping to a risk event recording interface; and capturing data in the risk event recording interface to obtain the first data information of the risk event.

[0007] Furthermore, before capturing the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation, the method also includes: determining identification information of the first data information of the risk event to be processed; determining location information of the risk event to be processed in the risk system; configuring the robotic process automation based on the identification information and the location information to obtain the first data information of the risk event through the robotic process automation.

[0008] Furthermore, based on the first data information and the information of the target object corresponding to the risk event, creating a risk event data table includes: identifying the first data information to obtain the type corresponding to the risk event; determining the target message corresponding to the risk event based on the type corresponding to the risk event; obtaining the information of the target object corresponding to the risk event from the risk system; and creating the risk event data table based on the first data information, the information of the target object and the target message.

[0009] Furthermore, after sending a target message to the target object based on the risk event data table to instruct the target object to handle the risk event, the method also includes: capturing second data information of the target event to be evaluated from the customer system of the financial institution through robotic process automation; determining the identity information of the user corresponding to the target event, and obtaining the user's financial information and credit information based on the identity information; and evaluating the risk of the target event based on the second data information of the target event, the financial information and the credit information to obtain an evaluation result.

[0010] Furthermore, based on the second data information of the target event, the financial information and the credit information, the risk of the target event is evaluated, and the evaluation result obtained includes: extracting features of the second data information, the financial information and the credit information through a recurrent neural network to obtain a target feature vector; predicting risk based on the target feature vector through the recurrent neural network to obtain a predicted risk value; and obtaining the evaluation result based on the predicted risk value.

[0011] Furthermore, after evaluating the risk of the target event based on the second data information of the target event, the financial information and the credit information to obtain the evaluation result, the method also includes: if the evaluation result characterizes that the target event is a risk event, writing the second data information of the target event into the risk system to notify the object corresponding to the target event to process the target event.

[0012] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a data processing device is provided. The device comprises: a first capture unit, used to capture first data information of a risk event to be processed from a risk system of a financial institution through robotic process automation; a creation unit, used to create a risk event data table based on the first data information and information of a target object corresponding to the risk event; and a sending unit, used to send a target message to the target object based on the risk event data table to instruct the target object to process the risk event.

[0013] Furthermore, the first capture unit includes: a sending module, used to send a login request to the risk system through robotic process automation, wherein the risk system jumps to a login interface after receiving the login request; an input module, used to input the robotic process automation identity information on the login interface, wherein if the robotic process automation identity information is verified, it jumps to a risk event recording interface; a capture module, used to capture data in the risk event recording interface to obtain the first data information of the risk event.

[0014] Furthermore, the device also includes: a first determination unit, used to determine the identification information of the first data information of the risk event to be processed before capturing the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation; a second determination unit, used to determine the location information of the risk event to be processed in the risk system; and a configuration unit, used to configure the robotic process automation based on the identification information and the location information, so as to obtain the first data information of the risk event through the robotic process automation.

[0015] Furthermore, the creation unit includes: an identification module, used to identify the first data information to obtain the type corresponding to the risk event; a determination module, used to determine the target message corresponding to the risk event based on the type corresponding to the risk event; an acquisition module, used to obtain the information of the target object corresponding to the risk event from the risk system; and a creation module, used to create the risk event data table based on the first data information, the information of the target object and the target message.

[0016] Furthermore, the device also includes: a second capture unit, which is used to capture second data information of the target event to be evaluated from the customer system of the financial institution through robotic process automation after sending a target message to the target object based on the risk event data table to instruct the target object to handle the risk event; a third determination unit, which is used to determine the identity information of the user corresponding to the target event, and obtain the user's financial information and credit information based on the identity information; an evaluation unit, which is used to evaluate the risk of the target event based on the second data information of the target event, the financial information and the credit information, and obtain an evaluation result.

[0017] Furthermore, the evaluation unit includes: an extraction module, used to perform feature extraction on the second data information, the financial information and the credit information through a recurrent neural network to obtain a target feature vector; a prediction module, used to perform risk prediction based on the target feature vector through the recurrent neural network to obtain a predicted risk value; and a processing module, used to obtain the evaluation result based on the predicted risk value.

[0018] Furthermore, the device also includes: a writing unit, which is used to evaluate the risk of the target event based on the second data information of the target event, the financial information and the credit information, and after obtaining the evaluation result, if the evaluation result characterizes that the target event is a risk event, write the second data information of the target event into the risk system to notify the object corresponding to the target event to process the target event.

[0019] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a computer-readable storage medium is also provided, wherein the computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the steps of any one of the above-mentioned method embodiments.

[0020] In order to achieve the above-mentioned purpose, according to another aspect of the present application, there is further provided an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above-mentioned method embodiments.

[0021] In the embodiment of the present application, the first data information of the risk event to be processed is captured from the risk system of the financial institution through robotic process automation; based on the first data information and the information of the target object corresponding to the risk event, a risk event data table is created; based on the risk event data table, a target message is sent to the target object to instruct the target object to handle the risk event, which solves the technical problem that the relevant technology needs to manually query various events in risk management and control, and then notify the personnel corresponding to various events to handle them, resulting in relatively low efficiency in event processing. In this solution, the unclosed-loop risk events that are to be corrected, unfeeded back, and unrectified, as well as the target objects corresponding to the events, are captured through robotic process automation, and a risk event data table is constructed based on the information of the target object and the risk event, and a target message is automatically sent based on the risk event data table to prompt the target object to handle the risk event, thereby reducing the workload of manual supervision and preventing the occurrence of risks in a timely manner, thereby achieving the effect of improving the efficiency of event processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0023] Figure 1 It is a hardware structure block diagram of a computer terminal for implementing a data processing method provided in an embodiment of the present application;

[0024] Figure 2 The data processing method according to the embodiment of the present application is as follows: Figure 1 ;

[0025] Figure 3 The data processing method according to the embodiment of the present application is as follows: Figure 2 ;

[0026] Figure 4 The data processing method according to the embodiment of the present application is as follows: Figure 3 ;

[0027] Figure 5 is a schematic diagram of a data processing device provided according to an embodiment of the present application;

[0028] Figure 6 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] It should be noted that the collected information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this application are information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with relevant laws, regulations and standards, necessary confidentiality measures are taken, and public order and good customs are not violated, and corresponding operation entrances are provided for users to choose to authorize or refuse. For example, an interface is set up between this system and relevant users or institutions to provide users with corresponding operation entrances for users to choose to agree or refuse the results of automated decision-making; if the user chooses to refuse, the expert decision-making process will be entered.

[0032] Example 1

[0033] According to an embodiment of the present application, a method embodiment of data processing is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 FIG. 1 shows a hardware structure block diagram of a computer terminal (or mobile device) for implementing a data processing method. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0035] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0036] The memory 104 can be used to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the data processing method in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizing the above-mentioned data processing method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0037] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0038] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0039] Under the above operating environment, this application provides Figure 2 The data processing method shown. Figure 2 The data processing method according to the first embodiment of the present invention is as follows: Figure 1 .

[0040] Step S201: capturing first data information of a risk event to be processed from a risk system of a financial institution through robotic process automation.

[0041] Optionally, use Robotic Process Automation (RPA) to log in to the risk system of the financial institution, and then capture the first data information of the risk event to be processed from the risk system of the financial institution. For example, capture risk events such as "pending correction", "no feedback", "no rectification" from the risk system of the financial institution. The risk event may refer to a risk event in which the debtor or counterparty fails to perform the obligations stipulated in the contract or the credit quality changes, resulting in loan default, or a risk event caused by an imperfect or problematic internal procedure. It should be noted that the first data information may include the event details of the risk event, and may also include an identifier of the risk event, such as "pending correction", "no feedback", "no rectification", etc.

[0042] Step S202: Create a risk event data table based on the first data information and information of the target object corresponding to the risk event.

[0043] Optionally, RPA creates a risk event data table through the first data information and the information of the target object corresponding to the risk event, that is, the first data information corresponding to the risk event is integrated with the corresponding processing personnel (that is, the information of the above-mentioned target object) to obtain the above-mentioned risk event data table. It should be noted that the risk event data table can also be matched with information such as the processing personnel's work email address.

[0044] Step S203: Send a target message to a target object based on the risk event data table to instruct the target object to process the risk event.

[0045] Optionally, RPA automatically triggers a target message to the processing personnel based on the risk event data table to instruct the processing personnel to handle the risk event. For example, RPA automatically sends an email to remind relevant personnel.

[0046] To summarize, robotic process automation is used to capture uncorrected, unresponsive, unrectified, unclosed-loop risk events, as well as information such as the target objects corresponding to the events. A risk event data table is constructed based on the target object’s information and risk events. The target message is automatically sent based on the risk event data table to prompt the target object to handle the risk event, thereby reducing the workload of manual supervision and preventing the occurrence of risks in a timely manner, thereby achieving the effect of improving the efficiency of event handling.

[0047] Optionally, in the data processing method provided in the embodiment of the present application, capturing the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation includes: sending a login request to the risk system through robotic process automation, wherein after the risk system receives the login request, it jumps to the login interface; inputting the robotic process automation identity information in the login interface, wherein if the robotic process automation identity information is verified, it jumps to the risk event recording interface; and capturing data in the risk event recording interface to obtain the first data information of the risk event.

[0048] In an optional embodiment, the first data information is obtained by the following steps: a login request is sent to the risk system through the robot process automation, and a response from the risk system is waited for. After receiving the login request, the risk system jumps to the login interface, and the RPA automatically enters the virtual digital employee information specified in the system (i.e., the robot process automation identity information) in the user name and password box. The risk system performs identity authentication, and when the robot process automation identity information is authenticated, jumps to the risk event recording interface.

[0049] Robotic process automation uses OCR technology to identify keywords in the risk event record interface, and then realizes data capture in the risk event record interface to obtain the first data information of the risk event. It should be noted that robotic process automation can filter risk events according to date and select the risk events that need to be processed currently.

[0050] Through robotic process automation, we can capture uncorrected, un-feedbacked, and un-rectified unclosed-loop risk events, thereby improving the efficiency of handling risk events.

[0051] Optionally, in the data processing method provided in the embodiment of the present application, before capturing the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation, the method also includes: determining identification information of the first data information of the risk event to be processed; determining location information of the risk event to be processed in the risk system; configuring the robotic process automation based on the identification information and the location information to obtain the first data information of the risk event through robotic process automation.

[0052] In an optional embodiment, the following steps are used to configure the robotic process automation: determine the identification information of the first data information of the risk event to be processed, for example, the field identification corresponding to the first data information in the risk system. Then determine the location information of the risk event to be processed in the risk system, and finally configure the robotic process automation according to the identification information and the location information to obtain the first data information of the risk event through the robotic process automation.

[0053] RPA can simulate manual operations, quickly capture and integrate data, reduce the time and error rate of manual entry, and improve the efficiency and accuracy of data collection.

[0054] Optionally, in the data processing method provided in the embodiment of the present application, creating a risk event data table based on the first data information and the information of the target object corresponding to the risk event includes: identifying the first data information to obtain the type corresponding to the risk event; determining the target message corresponding to the risk event based on the type corresponding to the risk event; obtaining the information of the target object corresponding to the risk event from the risk system; and creating a risk event data table based on the first data information, the information of the target object and the target message.

[0055] In an optional embodiment, the risk event data table is created by the following steps: the first data information is identified to obtain the type corresponding to the risk event, for example, to be corrected, not fed back, not rectified. According to the type corresponding to the risk event, the target message corresponding to the risk event is determined, for example, the target information to be corrected includes the details of the risk event and the content that needs to be changed. For example, the target information that has not been fed back includes the details of the risk event and the content that needs to be fed back.

[0056] Then, the information of the person handling the risk event (i.e., the above-mentioned person handling the risk event) is obtained from the risk system through robotic process automation. Finally, the risk event data table is created using the first data information, the target object information, and the target message. For example, a risk event table corresponding to "pending correction", "no feedback", and "no rectification" can be created, and the corresponding relevant information identified can be filled into the table in turn.

[0057] By creating a risk event data table, the efficiency of subsequently sending target messages to processing personnel is improved, thereby achieving the effect of improving the efficiency of risk event processing.

[0058] Optionally, in the data processing method provided in the embodiment of the present application, after sending a target message to the target object based on the risk event data table to instruct the target object to process the risk event, the method also includes: capturing second data information of the target event to be evaluated from the customer system of the financial institution through robotic process automation; determining the identity information of the user corresponding to the target event, and obtaining the user's financial information and credit information based on the identity information; evaluating the risk of the target event based on the second data information, financial information and credit information of the target event to obtain an evaluation result.

[0059] In an optional embodiment, the second data information of the target event to be evaluated is captured from the customer system of the financial institution through robotic process automation. It should be noted that the target event is an event to be identified, that is, an event that needs to be evaluated to determine whether it has risks. For example, it can be an event in which a user applies for a loan, and the second data information may include specific loan business data. Then, the identity information of the user corresponding to the target event (for example, the identity information of the user who applies for a loan) is captured through robotic process automation. Based on the identity information, the user's financial information and credit information are captured from the data lake of the financial system through robotic process automation, and a result data table can be formed based on the second data information, financial information and credit information of the target event. Finally, based on the second data information, financial information and credit information of the target event, the risk of the target event is evaluated to obtain an evaluation result.

[0060] By using RPA technology, relevant data of the events to be identified are automatically obtained, which improves the processing efficiency of the events to be identified.

[0061] Optionally, in the data processing method provided in the embodiment of the present application, the risk of the target event is evaluated based on the second data information, financial information and credit information of the target event, and the evaluation result includes: extracting features of the second data information, financial information and credit information through a recurrent neural network to obtain a target feature vector; predicting the risk based on the target feature vector through a recurrent neural network to obtain a predicted risk value; and obtaining the evaluation result based on the predicted risk value.

[0062] In an optional embodiment, the risk of the target event can be evaluated by the following steps: Deep learning technology can be used in advance, using the customer's asset situation and credit score as historical data, and using a recurrent neural network to train the customer's credit index data to obtain a prediction model (i.e., the above-mentioned recurrent neural network). The recurrent neural network is more dependent on the network state at the previous moment, and at each moment it is associated with the network state at the previous moment (generally the input vector convolution state vector). The output and the state at the next moment are obtained through the internal structure of the recurrent neural network, and the best training result is obtained by repeated training. The best training result is obtained by continuous iteration of historical data.

[0063] After obtaining the above prediction model, the second data information, the fund information and the credit information are input into the prediction model to predict the risk of the target event, obtain the predicted risk value, and finally obtain the evaluation result according to the predicted risk value. For example, if the predicted risk value exceeds a threshold value (e.g., 0.6), it is determined that the target event is risky.

[0064] Risk assessment is performed through recurrent neural networks, which improves the accuracy of risk assessment.

[0065] Optionally, in the data processing method provided in the embodiment of the present application, after evaluating the risk of the target event based on the second data information, financial information and credit information of the target event and obtaining the evaluation result, the method also includes: if the evaluation result characterizes that the target event is a risk event, writing the second data information of the target event into the risk system to notify the object corresponding to the target event to process the target event.

[0066] In an optional embodiment, if the evaluation result characterizes the target event as a risk event, the second data information of the target event is written into the risk system to notify the processing personnel corresponding to the target event (ie the above-mentioned object) to process the target event.

[0067] In an optional embodiment, the Figure 3 The flowchart shown implements the processing of unclosed-loop risk events: RPA opens the risk system, filters the date, selects the "pending correction", "no feedback", and "unrectified" options, and determines whether there are risk events to be processed. If so, the data of these risk events and the information of the corresponding processing personnel are captured, and RPA is used to automatically send emails to remind relevant personnel to handle risk events.

[0068] In an optional embodiment, the Figure 4The flowchart shown implements the processing of pending events: RPA opens the customer system, filters the date, and selects the "pending" and "pending reply" options to determine whether there are pending events to be processed. If so, the data of these risk events is captured and combined with the asset information and credit status related to the customer information in the data lake to form a list of pending events. The list of pending events is evaluated for risk through the predictive model to obtain the evaluation results.

[0069] The data processing method provided in the embodiment of the present application uses robotic process automation to capture the first data information of the risk event to be processed from the risk system of the financial institution; based on the first data information and the information of the target object corresponding to the risk event, a risk event data table is created; based on the risk event data table, a target message is sent to the target object to instruct the target object to process the risk event, which solves the technical problem that the relevant technology needs to manually query various events in risk management and control, and then notify the personnel corresponding to various events to process, resulting in low efficiency in event processing. In this solution, robotic process automation is used to capture the unclosed-loop risk events that are to be corrected, not fed back, and not rectified, as well as the target objects corresponding to the events, and a risk event data table is constructed based on the information of the target object and the risk event, and a target message is automatically sent based on the risk event data table to prompt the target object to process the risk event, thereby reducing the workload of manual supervision and preventing the occurrence of risks in a timely manner, thereby achieving the effect of improving the efficiency of event processing.

[0070] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0071] Example 2

[0072] The embodiment of the present application also provides a data processing device. It should be noted that the data processing device of the embodiment of the present application can be used to execute the data processing method provided by the embodiment of the present application. The data processing device provided by the embodiment of the present application is introduced below.

[0073] According to an embodiment of the present application, a device for implementing the above data processing method is also provided, such as Figure 5 As shown, the device includes: a first grabbing unit 501, a creating unit 502 and a sending unit 503.

[0074] A first capture unit 501 is used to capture first data information of a risk event to be processed from a risk system of a financial institution through robotic process automation;

[0075] A creation unit 502 is used to create a risk event data table based on the first data information and information of a target object corresponding to the risk event;

[0076] The sending unit 503 is used to send a target message to a target object based on the risk event data table to instruct the target object to process the risk event.

[0077] The data processing device provided in the embodiment of the present application captures the first data information of the risk event to be processed from the risk system of the financial institution through the first capture unit 501 through the robot process automation; the creation unit 502 creates a risk event data table based on the first data information and the information of the target object corresponding to the risk event; the sending unit 503 sends a target message to the target object based on the risk event data table to instruct the target object to process the risk event, which solves the technical problem that the relevant technology needs to manually query various events in risk management and control, and then notify the personnel corresponding to various events to process, resulting in low efficiency in event processing. In this scheme, the robot process automation is used to capture the unclosed-loop risk events that are to be corrected, not fed back, and not rectified, as well as the target object corresponding to the event, and the risk event data table is constructed according to the information of the target object and the risk event, and the target message is automatically sent according to the risk event data table to prompt the target object to process the risk event, thereby reducing the workload of manual supervision and preventing the occurrence of risks in a timely manner, thereby achieving the effect of improving the efficiency of event processing.

[0078] Optionally, in the data processing device provided in the embodiment of the present application, the first capture unit includes: a sending module, used to send a login request to the risk system through robot process automation, wherein the risk system jumps to the login interface after receiving the login request; an input module, used to input the robot process automation identity information in the login interface, wherein when the robot process automation identity information is verified, it jumps to the risk event recording interface; a capture module, used to capture data in the risk event recording interface to obtain the first data information of the risk event.

[0079] Optionally, in the data processing device provided in the embodiment of the present application, the device also includes: a first determination unit, used to determine the identification information of the first data information of the risk event to be processed before capturing the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation; a second determination unit, used to determine the location information of the risk event to be processed in the risk system; and a configuration unit, used to configure the robotic process automation based on the identification information and the location information, so as to obtain the first data information of the risk event through robotic process automation.

[0080] Optionally, in the data processing device provided in the embodiment of the present application, the creation unit includes: an identification module, used to identify the first data information to obtain the type corresponding to the risk event; a determination module, used to determine the target message corresponding to the risk event based on the type corresponding to the risk event; an acquisition module, used to obtain the information of the target object corresponding to the risk event from the risk system; and a creation module, used to create a risk event data table based on the first data information, the information of the target object and the target message.

[0081] Optionally, in the data processing device provided in the embodiment of the present application, the device also includes: a second capture unit, which is used to capture the second data information of the target event to be evaluated from the customer system of the financial institution through robotic process automation after sending a target message to the target object based on the risk event data table to instruct the target object to handle the risk event; a third determination unit, which is used to determine the identity information of the user corresponding to the target event, and obtain the user's financial information and credit information based on the identity information; an evaluation unit, which is used to evaluate the risk of the target event based on the second data information, financial information and credit information of the target event to obtain an evaluation result.

[0082] Optionally, in the data processing device provided in the embodiment of the present application, the evaluation unit includes: an extraction module, used to perform feature extraction on the second data information, financial information and credit information through a recurrent neural network to obtain a target feature vector; a prediction module, used to perform risk prediction based on the target feature vector through a recurrent neural network to obtain a predicted risk value; and a processing module, used to obtain an evaluation result based on the predicted risk value.

[0083] Optionally, in the data processing device provided in the embodiment of the present application, the device also includes: a writing unit, which is used to evaluate the risk of the target event based on the second data information, financial information and credit information of the target event, and after obtaining the evaluation result, if the evaluation result characterizes that the target event is a risk event, write the second data information of the target event into the risk system to notify the object corresponding to the target event to process the target event.

[0084] It should be noted that the first capture unit 501, the creation unit 502 and the sending unit 503 correspond to steps S201 to S203 in the first embodiment, and the three units and the corresponding steps implement the same examples and application scenarios, but are not limited to the contents disclosed in the first embodiment. It should be noted that the modules or units may be hardware components or software components stored in a memory (e.g., the memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n), and the modules may also be part of the device and run in the computer terminal 10 provided in the first embodiment.

[0085] Example 3

[0086] An embodiment of the present application may provide an electronic device, Figure 6 is a structural block diagram of an electronic device according to an embodiment of the present application. Figure 6 As shown, the electronic device may include: one or more ( Figure 6 (only one is shown) processor 602, memory 604, storage controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0087] Among them, the memory can be used to store software programs and modules, such as program instructions / modules corresponding to the methods and devices in the embodiments of the present application, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the above-mentioned method. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0088] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: capture the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation; create a risk event data table based on the first data information and the information of the target object corresponding to the risk event; send a target message to the target object based on the risk event data table to instruct the target object to process the risk event.

[0089] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: capturing the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation, including: sending a login request to the risk system through robotic process automation, wherein the risk system jumps to the login interface after receiving the login request; entering the robotic process automation identity information in the login interface, wherein if the robotic process automation identity information is verified, jumping to the risk event recording interface; capturing data in the risk event recording interface to obtain the first data information of the risk event.

[0090] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: before capturing the first data information of the risk event to be processed from the risk system of the financial institution through robotic process automation, the method also includes: determining the identification information of the first data information of the risk event to be processed; determining the location information of the risk event to be processed in the risk system; configuring the robotic process automation based on the identification information and the location information to obtain the first data information of the risk event through robotic process automation.

[0091] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: based on the first data information and the information of the target object corresponding to the risk event, create a risk event data table including: identifying the first data information to obtain the type corresponding to the risk event; determining the target message corresponding to the risk event based on the type corresponding to the risk event; obtaining the information of the target object corresponding to the risk event from the risk system; and creating a risk event data table based on the first data information, the information of the target object and the target message.

[0092] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: after sending the target message to the target object based on the risk event data table to instruct the target object to handle the risk event, the method also includes: capturing the second data information of the target event to be evaluated from the customer system of the financial institution through robotic process automation; determining the identity information of the user corresponding to the target event, and obtaining the user's financial information and credit information based on the identity information; based on the second data information, financial information and credit information of the target event, evaluating the risk of the target event to obtain an evaluation result.

[0093] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: based on the second data information, financial information and credit information of the target event, the risk of the target event is evaluated, and the evaluation result includes: extracting features of the second data information, financial information and credit information through a recurrent neural network to obtain a target feature vector; predicting the risk based on the target feature vector through a recurrent neural network to obtain a predicted risk value; and obtaining the evaluation result based on the predicted risk value.

[0094] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: after evaluating the risk of the target event based on the second data information, financial information and credit information of the target event and obtaining the evaluation result, the method also includes: if the evaluation result characterizes that the target event is a risk event, writing the second data information of the target event into the risk system to notify the object corresponding to the target event to process the target event.

[0095] It can be understood by those skilled in the art that Figure 6 The structure shown is for illustration only, and the electronic device may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, MID), a PAD, or other terminal devices. Figure 6 The structure of the electronic device is not limited. Figure 6 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 6 Different configurations are shown.

[0096] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0097] Example 4

[0098] The embodiment of the present application further provides a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the data processing method provided in the first embodiment.

[0099] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0100] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing the program of the data processing method steps.

[0101] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0102] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0103] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0104] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple 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.

[0105] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0106] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0107] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A data processing method, characterized in that: include: Capture the first data information of risk events to be processed from the risk system of financial institutions through robotic process automation; Creating a risk event data table based on the first data information and information of the target object corresponding to the risk event; A target message is sent to the target object based on the risk event data table to instruct the target object to process the risk event.

2. The method according to claim 1, characterized in that The first data information of risk events to be processed is captured from the risk system of financial institutions through robotic process automation, including: Sending a login request to the risk system through robotic process automation, wherein after receiving the login request, the risk system jumps to a login interface; Input the RPA identity information on the login interface, wherein if the RPA identity information is verified, jump to the risk event recording interface; Data is captured in the risk event recording interface to obtain first data information of the risk event.

3. The method according to claim 1, characterized in that Before fetching first data information of a risk event to be processed from a risk system of a financial institution through robotic process automation, the method further includes: Determine identification information of first data information of a risk event to be processed; Determine the location information of the risk event to be processed in the risk system; The robotic process automation is configured according to the identification information and the location information to obtain first data information of the risk event through the robotic process automation.

4. The method according to claim 1, characterized in that: Creating a risk event data table based on the first data information and information of a target object corresponding to the risk event includes: Identify the first data information to obtain a type corresponding to the risk event; Determining a target message corresponding to the risk event according to the type corresponding to the risk event; Acquire information of the target object corresponding to the risk event from the risk system; The risk event data table is created according to the first data information, the information of the target object and the target message.

5. The method according to claim 1, characterized in that After sending a target message to the target object based on the risk event data table to instruct the target object to process the risk event, the method further includes: Capturing second data information of the target event to be evaluated from the customer system of the financial institution through robotic process automation; Determine the identity information of the user corresponding to the target event, and obtain the user's financial information and credit information based on the identity information; Based on the second data information of the target event, the fund information and the credit information, the risk of the target event is evaluated to obtain an evaluation result.

6. The method according to claim 5, characterized in that Based on the second data information of the target event, the fund information and the credit information, the risk of the target event is evaluated, and the evaluation result includes: Extracting features from the second data information, the fund information and the credit information through a recurrent neural network to obtain a target feature vector; Performing risk prediction based on the target feature vector by the recurrent neural network to obtain a predicted risk value; The assessment result is obtained according to the predicted risk value.

7. The method according to claim 5, characterized in that After evaluating the risk of the target event based on the second data information of the target event, the fund information and the credit information to obtain the evaluation result, the method further includes: If the evaluation result indicates that the target event is a risk event, the second data information of the target event is written into the risk system to notify the object corresponding to the target event to process the target event.

8. A data processing device, characterized in that: include: A first capture unit, used to capture first data information of a risk event to be processed from a risk system of a financial institution through robotic process automation; A creating unit, configured to create a risk event data table based on the first data information and information of a target object corresponding to the risk event; A sending unit is used to send a target message to the target object based on the risk event data table to instruct the target object to process the risk event.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the computer-readable storage medium is located is controlled to execute the data processing method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A memory storing an executable program; A processor, used to run the program, wherein the program executes the data processing method according to any one of claims 1 to 7 when running.

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