Banking regulatory securities data method and apparatus based on a rules engine

Abstract

The application relates to a bank supervision securities data method and device based on a rule engine, a computer device, a storage medium and a computer program product. The method comprises the following steps: collecting event data in real time; the event data comprises bank-side transaction data and securities company-side transaction data; event construction is carried out based on the event data, a business event corresponding to the event data is acquired; a corresponding supervision rule is acquired from a preset rule engine library based on the event type; the supervision rule comprises a transaction detail sub-checking rule, a transaction detail total-checking rule and a securities company account occurrence amount checking rule; an execution result is acquired by executing the supervision rule; and a detection result is acquired based on the execution result and an expected result in the supervision rule. By adopting the method, fund data risks or error logic can be detected in high real time, and risk early warning can be performed in time.

Description

Technical Field

[0001] This application relates to the field of information security technology, and in particular to a method, apparatus, computer equipment, storage medium, and computer program product for bank supervision and securities data based on a rules engine. Background Technology

[0002] Following the comprehensive regulation of securities fund custody services, banks, as authorized institutions of regulatory agencies, have assumed some regulatory responsibilities. They oversee funds in securities firms' aggregated accounts held within the banking system to prevent financial risk events such as misappropriation or pledging of client funds without authorization, thus ensuring the safety of client funds. Against this backdrop, a bank-securities fund custody monitoring system has emerged. When a fund risk event is detected, it sends alerts to bank staff, securities firm staff, and regulatory agencies, allowing technical and operational personnel to collaborate on the response.

[0003] As competition intensifies in the banking sector, providing efficient, reliable, and flexible business services to customers is becoming increasingly important. To address these challenges, banks need to provide business monitoring systems that allow for the selection of monitoring rules based on business needs. Upon detecting a financial risk event, the system should issue an alert and transfer the anomaly to relevant personnel for handling. Currently, the goal is to promptly identify potential financial risk events for customers, minimize financial risks, improve customer satisfaction, and enhance regulatory capabilities. Therefore, how to detect financial data risks or logical errors in a high-real-time manner and issue timely risk warnings has become a pressing issue that needs to be addressed. Summary of the Invention

[0004] Therefore, it is necessary to provide a rule engine-based method, device, computer equipment, computer-readable storage medium, and computer program product for bank supervision and securities data that can detect financial data risks or erroneous logic in real time, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a method for collecting bank regulatory securities data based on a rules engine. The method includes:

[0006] Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data;

[0007] Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0008] Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules;

[0009] The execution of the supervision rules is performed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained.

[0010] In one embodiment, obtaining the execution result by executing the supervision rule includes:

[0011] The event data is cleaned to filter out invalid data.

[0012] The monitoring rules are executed on the cleaned event data to obtain the execution results.

[0013] In one embodiment, obtaining the detection result based on the execution result and the expected result in the supervision rule includes:

[0014] The execution result is compared with the expected result in the supervision rule to obtain the detection result.

[0015] In one embodiment, after comparing the execution result with the expected result in the supervision rule to obtain the detection result, the method further includes:

[0016] The detection results are stored in the database, and an operation log is generated simultaneously.

[0017] In one embodiment, after storing the detection results in the database and generating a record operation log, the method further includes:

[0018] If the execution result is inconsistent with the expected result in the supervision rule, the detection result will be sent to the management personnel via SMS and / or email alarm.

[0019] In one embodiment, comparing the execution result with the expected result in the supervision rule to obtain the detection result includes:

[0020] The execution result is compared with the expected result in the supervision rule. If they match, the detection result is that no risk was found; if they do not match, the detection result is that a risk was found.

[0021] Secondly, this application also provides a bank regulatory securities data device based on a rules engine. The device includes:

[0022] The data acquisition module is used to collect and acquire event data in real time; the event data includes bank-side transaction data and securities firm-side transaction data.

[0023] The time acquisition module is used to construct events based on the event data and acquire the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0024] The rule acquisition module is used to acquire the corresponding supervision rules from a preset rule engine library based on the event type; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules.

[0025] The rule execution module is used to execute the supervision rule to obtain the execution result, and obtain the detection result based on the execution result and the expected result in the supervision rule.

[0026] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0027] Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data;

[0028] Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0029] Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules;

[0030] The execution of the supervision rules is performed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained.

[0031] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0032] Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data;

[0033] Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0034] Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules;

[0035] The execution of the supervision rules is performed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained.

[0036] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0037] Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data;

[0038] Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0039] Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules;

[0040] The execution of the supervision rules is performed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained.

[0041] The aforementioned rule-engine-based banking and securities data supervision method, device, computer equipment, storage medium, and computer program product collect and acquire event data in real time, construct events based on the event data, obtain the corresponding business events, retrieve the corresponding supervision rules from the preset rule engine library based on the event type, execute the supervision rules to obtain the execution results, and obtain the detection results based on the execution results and the expected results in the supervision rules. This achieves highly real-time detection of financial data risks or erroneous logic and can provide timely risk warnings based on the detection results. Attached Figure Description

[0042] Figure 1 This is a diagram illustrating the application environment of a rule engine-based method for regulating securities data in banking, as shown in one embodiment.

[0043] Figure 2 This is a flowchart illustrating a rule engine-based method for regulating securities data in banking, as shown in one embodiment.

[0044] Figure 3 This is a schematic diagram illustrating the comparison between the execution result and the expected result in the supervision rule in one embodiment;

[0045] Figure 4 This is a structural block diagram of a rule engine-based bank regulatory securities data device in one embodiment.

[0046] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0048] The rule-engine-based method for managing securities data in banking supervision provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. For example, server 104 collects event data in real time; the event data includes bank-side transaction data and brokerage-side transaction data; based on the event data, events are constructed to obtain the corresponding business events; the event types of the business events include transfer events, account balance events, account transaction amount events, and account detail verification events; based on the event type, corresponding supervision rules are obtained from a preset rule engine library; the supervision rules include transaction detail reconciliation rules, transaction detail total reconciliation rules, and brokerage account transaction amount reconciliation rules; the supervision rules are executed to obtain execution results, and based on the execution results and the expected results in the supervision rules, detection results are obtained.

[0049] The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle systems. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0050] In one embodiment, such as Figure 2 As shown, a rule engine-based method for bank regulatory securities data is provided, which can be applied to... Figure 1 Taking the server in the example, the following steps are included:

[0051] Step 202: Collect and acquire event data in real time; the event data includes bank-side transaction data and securities firm-side transaction data.

[0052] Specifically, event data is collected in real time; this event data includes transaction data from both the bank and securities firms. Real-time collection of event data can be achieved through a pre-set data collection server. The event data primarily includes business event data such as bank-side and securities firm-side transaction data, with bank-side transaction data encompassing data from the bank's securities fund custody system and bank account settlement system.

[0053] Step 204: Construct events based on the event data and obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events.

[0054] Specifically, events are constructed based on event data to obtain the corresponding business events. Events of different event types are constructed according to the event data. The event types include transfer events, account balance events, account transaction events, and account detail reconciliation events. The transfer and account transaction events are constructed as follows: A transfer event refers to each customer's deposit or withdrawal transaction under the third-party custody agreement. The system automatically identifies the customer's transfer behavior and collects the elements of the transfer event, including the agreement number, debit account, credit account, transfer amount, transfer serial number, and brokerage ID. An account transaction event refers to the customer's transaction amount under the third-party custody agreement within a reconciliation period. The system automatically collects customer transfer behavior and event elements, including the agreement number, transfer-in / transfer-out identifier, transfer amount, and brokerage ID. Before the end-of-day reconciliation, the system summarizes and nets the transaction amount according to the agreement dimension to obtain the account transaction event data for each agreement.

[0055] Step 206: Obtain the corresponding supervision rules from the preset rule engine library based on the event type; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules.

[0056] Specifically, based on the event type, corresponding supervisory rules are retrieved from a pre-defined rule engine library. These supervisory rules include transaction detail reconciliation rules, total transaction detail reconciliation rules, and brokerage account transaction amount reconciliation rules. Event types are divided into major and minor categories. Major categories include detail categories and amount categories. The detail category includes subcategories such as transfer details and opening / closing agreement details. The amount category includes subcategories such as account transaction amount and account balance. The supervisory rules include transaction detail reconciliation rules. These rules require a transaction-by-transaction reconciliation between the bank and brokerage sides to identify customer transfer errors. Specifically, there are three scenarios: First, the same transaction detail exists on both the bank and brokerage sides. A second reconciliation of the transaction detail elements is required. If the elements match, it is considered a consistent transaction; otherwise, it is considered an error detail. Second, the bank has the transaction detail, but the brokerage does not. This is considered an error detail. Third, the bank does not have the transaction detail, but the brokerage does. This is considered an error detail. The transaction details summary verification rules summarize the transaction amounts of the brokerage firm's end-of-day pending reconciliation details and check the consistency between the summarized amounts on the bank side and the brokerage firm side. The brokerage firm account transaction amount verification rules verify the consistency between the daily changes in the brokerage firm's bank account and the agreed changes in all its clients' accounts, checking whether the actual changes in bank account funds are consistent with the agreed changes in client funds.

[0057] Step 208: Execute the supervision rule to obtain the execution result, and obtain the detection result based on the execution result and the expected result in the supervision rule.

[0058] Specifically, to obtain the execution results by executing the supervision rules, rule filtering needs to be run first to clean up invalid data and avoid affecting the supervision results. Finally, the supervision rules are run. The execution of the supervision rules involves comparing the execution results with the expected results in the supervision rules to obtain the detection results.

[0059] In the aforementioned rule engine-based method for bank supervision and securities data, event data is collected in real time, events are constructed based on the event data, business events corresponding to the event data are obtained, corresponding supervision rules are obtained from the preset rule engine library based on the event type, and finally the supervision rules are executed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained. This achieves high real-time detection of financial data risks or erroneous logic, and can provide timely risk warnings based on the detection results.

[0060] In one embodiment, obtaining the execution result by executing the supervision rule includes:

[0061] The event data is cleaned to filter out invalid data.

[0062] The monitoring rules are executed on the cleaned event data to obtain the execution results.

[0063] Specifically, when executing the monitoring rules and obtaining the execution results, the event data is first cleaned to filter out invalid data and avoid affecting the monitoring results. The filtered event data is then obtained, the monitoring rules are executed, and the execution results are obtained. The monitoring rules include transaction detail reconciliation rules, transaction detail total reconciliation rules, and brokerage account transaction amount reconciliation rules. Event types are divided into major and minor categories. Major categories include detail categories and amount categories. Detail categories include subcategories such as transfer details and opening / closing agreement details, while amount categories include subcategories such as account transaction amount and account balance. The monitoring rules include the transaction detail reconciliation rules, which require verifying each customer transfer transaction detail on both the bank and brokerage sides to identify customer transfer errors. Specifically, there are three scenarios: First, the same transaction details exist on both the bank's and the brokerage's sides. A second verification of the transaction details is required; if the details match, it's considered a consistent transaction; otherwise, it's considered an error. Second, the bank has the transaction details, but the brokerage does not; this is considered an error. Third, the bank has no transaction details, but the brokerage does; this is also considered an error. The transaction details summary verification rule summarizes the total amount of transactions pending reconciliation at the brokerage's end of the day and checks the consistency between the summarized amounts on the bank and brokerage sides. The brokerage account transaction amount verification rule verifies the consistency between the brokerage's daily bank account changes and the agreed-upon changes for all clients under its name, checking whether the actual bank account fund changes match the agreed-upon client fund changes.

[0064] In this embodiment, the event data is cleaned to filter out invalid data; monitoring rules are executed on the cleaned event data to obtain the execution results; it can flexibly and conveniently access various business rules, and quickly access the monitoring platform through script rules, thereby improving the accuracy of obtaining execution results by executing monitoring rules.

[0065] In one embodiment, obtaining the detection result based on the execution result and the expected result in the supervision rule includes:

[0066] The execution result is compared with the expected result in the supervision rule to obtain the detection result.

[0067] Specifically, Figure 3 This is a schematic diagram illustrating the comparison between the execution result and the expected result in the supervision rule in one embodiment, as shown below. Figure 3 As shown, when obtaining the detection result, the execution result is compared with the expected result in the supervision rule based on the execution result and the expected result in the supervision rule. The detection result includes whether the comparison is consistent or inconsistent. If the comparison is consistent, there is no risk; if the comparison is inconsistent, there is a risk.

[0068] In this embodiment, the execution result is compared with the expected result in the supervision rule to obtain the detection result. It can flexibly and conveniently access various business rules, quickly access the supervision platform through script rules, and improve the efficiency of verification through real-time detection and monitoring of the supervision rule online.

[0069] In one embodiment, after comparing the execution result with the expected result in the supervision rule to obtain the detection result, the method further includes:

[0070] The detection results are stored in the database, and an operation log is generated simultaneously.

[0071] Specifically, the execution result is compared with the expected result in the supervision rules. After obtaining the detection result, it is also necessary to store the detection result in a file and a database, and record the operation log to achieve persistent storage of the event detection result.

[0072] In this embodiment, after obtaining the detection results through comparison, the detection results are stored in the database, and an operation log is generated to achieve persistent storage of the detection results, which is beneficial for comprehensive analysis of the detection results.

[0073] In one embodiment, after storing the detection results in the database and generating a record operation log, the method further includes:

[0074] If the execution result is inconsistent with the expected result in the supervision rule, the detection result will be sent to the management personnel via SMS and / or email alarm.

[0075] Specifically, the detection results are stored in the database, and an operation log is generated. When the execution result is inconsistent with the expected result in the supervision rules, it proves that a risk has occurred. In order to deal with the risk, the detection results are sent to the management personnel via SMS and / or email alerts so that the management personnel can deal with the risk event in a timely manner.

[0076] In this embodiment, when the execution result is inconsistent with the expected result in the supervision rules, the detection result is sent to the management personnel via SMS alarm and / or email alarm, which realizes the notification of management personnel based on the detection result, which is conducive to the management personnel to handle risk events in a timely manner.

[0077] In one embodiment, comparing the execution result with the expected result in the supervision rule to obtain the detection result includes:

[0078] The execution result is compared with the expected result in the supervision rule. If they match, the detection result is that no risk was found; if they do not match, the detection result is that a risk was found.

[0079] Specifically, the execution result is compared with the expected result in the supervision rules. When obtaining the detection result, it is determined whether the execution result is consistent with the expected result in the supervision rules. If the execution result is consistent with the expected result in the supervision rules, it proves that no risk event was found in the detection result; if the execution result is inconsistent with the expected result in the supervision rules, it proves that a risk event exists in the detection result. In this case, the detection result needs to be sent to the management personnel via SMS alert and / or email alert so that the management personnel can handle the risk event in a timely manner.

[0080] In this embodiment, the execution result is compared with the expected result in the supervision rule. If the execution result is consistent with the expected result in the supervision rule, the detection result is that no risk was found; if the execution result is inconsistent with the expected result in the supervision rule, the detection result is that a risk was found. This achieves accurate judgment of the detection result and improves the efficiency and accuracy of risk detection.

[0081] This application enables high-real-time detection of financial data risks or logical errors, allowing for immediate discovery and notification of relevant personnel for risk event handling. It also allows for flexible and convenient integration with various business rules, enabling rapid access to the supervision platform via script rules. Real-time detection and monitoring through the online supervision rules facilitates verification, improving efficiency. The rule-engine-based bank supervision securities data method in this application employs rules and standardized business rules to meet the high-timeliness and high-reliability requirements of securities custody fund supervision. The goal is to formulate a standardized business supervision rule for each regulatory requirement through a series of business rules. It can collect data information in real time, perform data detection according to regulatory rules, and efficiently and reliably detect securities custody fund risk events.

[0082] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0083] Based on the same inventive concept, this application also provides a rule-engine-based bank regulatory securities data device for implementing the rule-engine-based bank regulatory securities data method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations of one or more rule-engine-based bank regulatory securities data device embodiments provided below can be found in the limitations of the rule-engine-based bank regulatory securities data method described above, and will not be repeated here.

[0084] In one embodiment, such as Figure 4 As shown, a bank regulatory securities data device based on a rule engine is provided, including: a data acquisition module 401, a time acquisition module 402, a rule acquisition module 403, and a rule execution module 404, wherein:

[0085] Data acquisition module 401 is used to collect and acquire event data in real time; the event data includes bank-side transaction data and securities firm-side transaction data;

[0086] The time acquisition module 402 is used to construct events based on the event data and acquire the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0087] The rule acquisition module 403 is used to acquire the corresponding supervision rules from a preset rule engine library based on the event type; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules.

[0088] The rule execution module 404 is used to execute the supervision rule to obtain the execution result, and obtain the detection result based on the execution result and the expected result in the supervision rule.

[0089] In one embodiment, the rule execution module 404 is specifically used to: perform data cleaning on the event data to filter out invalid data in the event data; execute the supervision rule on the data-cleaned event data, and obtain the execution result.

[0090] In this embodiment, the supervision rules are filtered to obtain the filtered supervision rules, which are then executed to obtain the execution results. This achieves the filtering of supervision rules, enabling flexible and convenient access to various business rules. By using script rules, the supervision platform can be quickly accessed, improving the accuracy of obtaining execution results from the execution of supervision rules.

[0091] In one embodiment, the rule execution module 404 is further configured to: compare the execution result with the expected result in the supervision rule to obtain the detection result.

[0092] In this embodiment, the execution result is compared with the expected result in the supervision rule to obtain the detection result. It can flexibly and conveniently access various business rules, quickly access the supervision platform through script rules, and improve the efficiency of verification through real-time detection and monitoring of the supervision rule online.

[0093] In one embodiment, the rule execution module 404 is further configured to: save the detection results in a database and generate a record operation log.

[0094] In this embodiment, after obtaining the detection results through comparison, the detection results are stored in the database, and an operation log is generated to achieve persistent storage of the detection results, which is beneficial for comprehensive analysis of the detection results.

[0095] In one embodiment, the rule execution module 404 is further configured to: if the execution result is inconsistent with the expected result in the supervision rule, send the detection result to the management personnel via SMS alarm and / or email alarm.

[0096] In this embodiment, when the execution result is inconsistent with the expected result in the supervision rules, the detection result is sent to the management personnel via SMS alarm and / or email alarm, which realizes the notification of management personnel based on the detection result, which is conducive to the management personnel to handle risk events in a timely manner.

[0097] In one embodiment, the rule execution module 404 is further configured to: compare the execution result with the expected result in the supervision rule; if they are consistent, the detection result is no risk found; if they are inconsistent, the detection result is a risk found.

[0098] In this embodiment, the execution result is compared with the expected result in the supervision rule. If the execution result is consistent with the expected result in the supervision rule, the detection result is that no risk was found; if the execution result is inconsistent with the expected result in the supervision rule, the detection result is that a risk was found. This achieves accurate judgment of the detection result and improves the efficiency and accuracy of risk detection.

[0099] The aforementioned rule engine-based banking and securities data device collects event data in real time, constructs events based on the event data, obtains the corresponding business events, retrieves the corresponding supervision rules from the preset rule engine library based on the event type, executes the supervision rules to obtain the execution results, and obtains the detection results based on the execution results and the expected results in the supervision rules. This achieves high real-time detection of financial data risks or erroneous logic and can provide timely risk warnings based on the detection results.

[0100] The modules in the aforementioned rule-based banking and securities data device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can invoke and execute the corresponding operations of each module.

[0101] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a rule-engine-based method for managing securities data in banking supervision.

[0102] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0103] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0104] Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data;

[0105] Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0106] Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules;

[0107] The execution of the supervision rules is performed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained.

[0108] In one embodiment, when the processor executes the computer program, it further performs the following steps: data cleaning of the event data to filter out invalid data in the event data; and executing the supervision rule on the data-cleaned event data to obtain the execution result.

[0109] In one embodiment, when the processor executes the computer program, it further performs the following steps: comparing the execution result with the expected result in the supervision rule to obtain the detection result.

[0110] In one embodiment, when the processor executes the computer program, it also performs the following steps: storing the detection results in a database and generating a record operation log.

[0111] In one embodiment, when the processor executes the computer program, it further performs the following steps: if the execution result is inconsistent with the expected result in the supervision rule, the detection result is sent to the management personnel via SMS alarm and / or email alarm.

[0112] In one embodiment, when the processor executes the computer program, it further performs the following steps: comparing the execution result with the expected result in the supervision rule; if they match, the detection result is no risk found; if they do not match, the detection result is a risk found.

[0113] The aforementioned computer equipment collects and acquires event data in real time, constructs events based on the event data, obtains the business events corresponding to the event data, retrieves the corresponding supervision rules from the preset rule engine library based on the event type, finally executes the supervision rules to obtain the execution results, and obtains the detection results based on the execution results and the expected results in the supervision rules. This achieves high real-time detection of financial data risks or erroneous logic, and can provide timely risk warnings based on the detection results.

[0114] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0115] Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data;

[0116] Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0117] Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules;

[0118] The execution of the supervision rules is performed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained.

[0119] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: data cleaning of the event data to filter out invalid data in the event data; and executing the supervision rule on the data-cleaned event data to obtain the execution result.

[0120] In one embodiment, when the computer program is executed by a processor, it further performs the following steps: comparing the execution result with the expected result in the supervision rule to obtain a detection result.

[0121] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: storing the detection results in a database and generating a record operation log.

[0122] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: if the execution result is inconsistent with the expected result in the supervision rule, the detection result is sent to the management personnel via SMS alarm and / or email alarm.

[0123] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: comparing the execution result with the expected result in the supervision rule; if they match, the detection result is no risk found; if they do not match, the detection result is a risk found.

[0124] The aforementioned storage medium collects event data in real time, constructs events based on the event data, obtains the corresponding business events, retrieves the corresponding supervision rules from the preset rule engine library based on the event type, executes the supervision rules to obtain the execution results, and obtains the detection results based on the execution results and the expected results in the supervision rules. This achieves high real-time detection of financial data risks or erroneous logic, and can provide timely risk warnings based on the detection results.

[0125] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0126] Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data;

[0127] Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events;

[0128] Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules;

[0129] The execution of the supervision rules is performed to obtain the execution results. Based on the execution results and the expected results in the supervision rules, the detection results are obtained.

[0130] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: data cleaning of the event data to filter out invalid data in the event data; and executing the supervision rule on the data-cleaned event data to obtain the execution result.

[0131] In one embodiment, when the computer program is executed by a processor, it further performs the following steps: comparing the execution result with the expected result in the supervision rule to obtain a detection result.

[0132] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: storing the detection results in a database and generating a record operation log.

[0133] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: if the execution result is inconsistent with the expected result in the supervision rule, the detection result is sent to the management personnel via SMS alarm and / or email alarm.

[0134] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: comparing the execution result with the expected result in the supervision rule; if they match, the detection result is no risk found; if they do not match, the detection result is a risk found.

[0135] The aforementioned computer program product collects event data in real time, constructs events based on the event data, obtains the business events corresponding to the event data, retrieves the corresponding supervision rules from the preset rule engine library based on the event type, finally executes the supervision rules to obtain the execution results, and obtains the detection results based on the execution results and the expected results in the supervision rules. This achieves high real-time detection of financial data risks or erroneous logic, and can provide timely risk warnings based on the detection results.

[0136] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0137] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0138] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0139] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for bank regulatory securities data based on a rules engine, characterized in that, The method includes: Real-time acquisition of event data; the event data includes bank-side transaction data and securities firm-side transaction data; Based on the event data, events are constructed to obtain the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events; Based on the event type, the corresponding supervision rules are obtained from the preset rule engine library; the supervision rules include transaction detail verification rules, transaction detail total verification rules, and brokerage account transaction amount verification rules; The execution of the supervision rules is performed to obtain the execution results, and the detection results are obtained based on the execution results and the expected results in the supervision rules. The execution of the supervision rule to obtain the execution result includes: The event data is cleaned to filter out invalid data. The monitoring rules are executed on the cleaned event data to obtain the execution results; The detailed transaction reconciliation rules are used to reconcile the details of customer transfer transactions between the bank and the brokerage firm on a transaction-by-transaction basis. If the same transaction details exist on the bank's side and the securities firm's side, the transaction details will be checked twice. If the details are consistent, it will be considered a consistent transaction; otherwise, it will be considered an error. If the bank has transaction details but the brokerage does not, it is recorded as an error detail. If the bank has no transaction details but the brokerage has transaction details, it should be recorded as an error. The transaction details total reconciliation rules are used to summarize the transaction details pending reconciliation at the end of the day for securities firms and to check the consistency of the summaries between the bank side and the securities firm side. The aforementioned brokerage account transaction verification rules are used to verify the consistency between the daily transaction amount changes in the brokerage's bank account and the transaction amounts changes agreed upon by all its clients.

2. The method according to claim 1, characterized in that, The process of obtaining the detection result based on the execution result and the expected result in the supervision rule includes: The execution result is compared with the expected result in the supervision rule to obtain the detection result.

3. The method according to claim 2, characterized in that, After comparing the execution result with the expected result in the supervision rule to obtain the detection result, the method further includes: The detection results are stored in the database, and an operation log is generated simultaneously.

4. The method according to claim 3, characterized in that, After storing the detection results in the database and generating an operation log, the process also includes: If the execution result is inconsistent with the expected result in the supervision rule, the detection result will be sent to the management personnel via SMS and / or email alarm.

5. The method according to claim 2, characterized in that, The step of comparing the execution result with the expected result in the supervision rule to obtain the detection result includes: The execution result is compared with the expected result in the supervision rule. If they match, the detection result is that no risk was found; if they do not match, the detection result is that a risk was found.

6. A bank regulatory securities data device based on a rules engine, characterized in that, The device includes: The data acquisition module is used to collect and acquire event data in real time; the event data includes bank-side transaction data and securities firm-side transaction data. The time acquisition module is used to construct events based on the event data and acquire the business events corresponding to the event data; the event types of the business events include transfer events, account balance events, account transaction events, and account detail reconciliation events; The rule acquisition module is used to retrieve corresponding supervision rules from a preset rule engine library based on the event type. These supervision rules include transaction detail reconciliation rules, total transaction detail reconciliation rules, and brokerage account transaction amount reconciliation rules. The transaction detail reconciliation rules are used to reconcile customer transfer transaction details between the bank and brokerage sides one by one. If the same transaction detail exists on both sides, the transaction detail elements are reconciled a second time; if the elements match, it is considered a consistent reconciliation; otherwise, it is considered an error detail. If the bank has a transaction detail but the brokerage side does not, it is considered an error detail. If the bank does not have a transaction detail but the brokerage side does, it is considered an error detail. The total transaction detail reconciliation rules are used to summarize the transaction amounts of the brokerage's end-of-day pending reconciliation transaction details and check the consistency of the summarized amounts on both the bank and brokerage sides. The brokerage account transaction amount reconciliation rules are used to verify the consistency between the daily change amount in the brokerage's bank account and the agreed change amount for all its clients. The rule execution module is used to execute the supervision rule, obtain the execution result, and obtain the detection result based on the execution result and the expected result in the supervision rule. The rule execution module is specifically used to perform data cleaning on the event data, filtering out invalid data in the event data; and to execute the supervision rule on the cleaned event data to obtain the execution result.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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