Transaction risk detection method, device, equipment, medium and program product

Abstract

The invention provides a transaction risk detection method which can be applied to the technical field of computers or the field of financial science and technology. The transaction risk detection method comprises the steps that in response to a transaction processing task received in a thread pool, the transaction processing task is analyzed to obtain transaction parameters, and the transaction processing task is generated according to a transaction processing request; according to the transaction parameters, determining an expected increment risk index value generated by processing the transaction processing request; using the expected increment risk index value to update an existing risk index value related to the transaction processing request to obtain an updated risk index value; and detecting the updated risk index value based on a predetermined risk threshold to obtain a risk detection result of the transaction processing request. The invention further provides a transaction risk detection device and equipment, a storage medium and a program product.

Description

Technical Field

[0001] This application relates to the field of computer technology or financial technology, and more specifically to a method, apparatus, device, medium and program product for detecting transaction risks. Background Technology

[0002] In related technologies, when a trading system performs risk detection based on user-level transaction data, it needs to perform step-by-step calculations on multi-dimensional transaction information from a large number of users. This computational complexity results in low processing efficiency for the trading system, making it impossible to determine transaction risks in a timely manner and leading to low security for the trading system. Summary of the Invention

[0003] In view of the above problems, this application provides a method, apparatus, equipment, medium and program product for detecting transaction risks.

[0004] One aspect of this application provides a transaction risk detection method, comprising: in response to receiving a transaction processing task in a thread pool, parsing the transaction processing task to obtain transaction parameters, wherein the transaction processing task is generated based on a transaction processing request; determining, based on the transaction parameters, the expected incremental risk indicator value generated by processing the transaction processing request; updating existing risk indicator values ​​related to the transaction processing request using the expected incremental risk indicator value to obtain an updated risk indicator value; and detecting the updated risk indicator value based on a predetermined risk threshold to obtain a risk detection result for the transaction processing request.

[0005] According to an embodiment of this application, the transaction parameters include the transaction product; the risk detection result of the transaction processing request is obtained by detecting the updated risk indicator value based on a predetermined risk threshold, including: calling multiple predetermined risk thresholds related to the transaction product according to the identifier of the transaction product, wherein the predetermined risk thresholds are configured with an effective period; determining a target predetermined risk threshold from the multiple predetermined risk thresholds according to the relationship between the timestamp of the transaction processing request and the effective period; and detecting the updated risk indicator value using the target predetermined risk threshold to obtain the risk detection result of the transaction processing request.

[0006] According to an embodiment of this application, the transaction parameters further include transaction triggering node information that triggers the transaction processing request, and the risk detection result of the transaction processing request includes risk warning information; the risk detection result of the transaction processing request is obtained by detecting the updated risk indicator value using a target predetermined risk threshold, including: determining the risk level information corresponding to the transaction processing request based on the relationship between the updated risk indicator value and the target predetermined risk threshold; obtaining the generation method for generating the risk warning information based on the risk level information and the transaction triggering node information; calling the information template of the risk warning information according to the identifier of the generation method; and filling the information template with the risk level information to obtain the risk warning information.

[0007] According to an embodiment of this application, the target predetermined risk threshold includes a first risk threshold and a second risk threshold greater than the first risk threshold; the risk level information corresponding to the transaction processing request is determined based on the relationship between the updated risk indicator value and the target predetermined risk threshold, including: determining the transaction processing request as a warning risk level when the updated risk indicator value is greater than the first risk threshold and less than the second risk threshold; and determining the transaction processing request as an alarm risk level when the updated risk indicator value is greater than or equal to the second risk threshold.

[0008] According to an embodiment of this application, the transaction parameters further include transaction objects; based on the transaction parameters, determining the expected incremental risk indicator value generated by processing the transaction processing request includes: determining the transaction product associated with the transaction object; based on the transaction data of the transaction product, determining the object dimension risk indicator value on a per-transaction-object basis; and superimposing the object dimension risk indicator values ​​of the transaction objects to obtain the expected incremental risk indicator value of the transaction object group, wherein the transaction object group consists of transaction objects.

[0009] According to an embodiment of this application, the transaction data includes incremental scale data of the transaction product and transaction risk coefficient; based on the transaction data of the transaction product, the object dimension risk indicator value is determined on a per-transaction basis, including: for each transaction product, processing the existing scale data of the transaction product using the incremental scale data of the transaction product to obtain the target scale data of the transaction product; generating sub-risk indicator values ​​of the transaction product based on the target scale data and the transaction risk coefficient; and superimposing the sub-risk indicator values ​​of each transaction product of the transaction object to obtain the object dimension risk indicator value.

[0010] Another aspect of this application provides a transaction risk detection device, comprising: a parsing module, configured to parse a transaction processing task received from a thread pool to obtain transaction parameters, wherein the transaction processing task is generated based on a transaction processing request; a determining module, configured to determine the expected incremental risk indicator value generated by processing the transaction processing request based on the transaction parameters; an updating module, configured to update the existing risk indicator value related to the transaction processing request using the expected incremental risk indicator value to obtain an updated risk indicator value; and a detection module, configured to detect the updated risk indicator value based on a predetermined risk threshold to generate a risk detection result for the transaction processing request.

[0011] Another aspect of this application provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above-described transaction risk detection method.

[0012] Another aspect of this application provides a computer-readable storage medium having a computer program or instructions stored thereon, characterized in that the computer program or instructions, when executed by a processor, implement the steps of the above-described transaction risk detection method.

[0013] Another aspect of this application provides a computer program product, including a computer program or instructions, characterized in that the computer program or instructions, when executed by a processor, implement the steps of the above-described transaction risk detection method.

[0014] According to the embodiments of this application, by parsing each transaction processing task in the thread pool and calculating the expected incremental risk indicator value in real time based on the parsed transaction parameters, the complex calculation task is broken down into simple calculation tasks for each transaction processing task, improving the processing efficiency of the trading system. The expected incremental risk indicator value is then superimposed on the existing risk indicator value to obtain an updated risk indicator value, calculating the real-time risk indicator value corresponding to the transaction processing task. Finally, based on a predetermined risk threshold and the updated risk indicator value, the risk detection result of the transaction processing request is output in real time. Thus, the corresponding risk indicator value is calculated in real time for each transaction processing task, enabling timely control of each transaction processing task and improving the security of the trading system. Attached Figure Description

[0015] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0016] Figure 1 This illustration schematically depicts an application scenario of the transaction risk detection method and apparatus according to embodiments of this application.

[0017] Figure 2 A flowchart illustrating a transaction risk detection method according to an embodiment of this application is shown schematically.

[0018] Figure 3 A schematic diagram illustrating the risk detection results according to an embodiment of this application is shown.

[0019] Figure 4 A flowchart illustrating a transaction risk detection method according to another embodiment of this application is shown schematically;

[0020] Figure 5 This schematic diagram illustrates the structural block diagram of a transaction risk detection device according to an embodiment of this application;

[0021] Figure 6 A block diagram schematically illustrates an electronic device suitable for implementing a transaction risk detection method according to an embodiment of this application. Detailed Implementation

[0022] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0023] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0024] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0025] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0026] It should be noted that the transaction risk detection method and device of this application can be used in the field of computer technology or financial technology, or in any field other than computer technology or financial technology. This application does not limit the application field of the transaction risk detection method and device.

[0027] In the technical solution of this application, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0028] In scenarios involving automated decision-making using personal information, the methods, devices, and systems provided in this application all offer users corresponding entry points for choosing to agree to or reject the automated decision-making results. If the user chooses to reject, the process proceeds to the expert decision-making stage. Here, "automated decision-making" refers to the activity of automatically analyzing and evaluating an individual's behavioral habits, interests, or economic, health, and credit status through computer programs, and then making a decision. Here, "expert decision-making" refers to the activity of making decisions by personnel who specialize in a particular field, possess specialized experience, knowledge, and skills, and have reached a certain level of professional expertise.

[0029] Currently, the main methods for detecting trading risks in bond and other trading products include static limit risk detection and dynamic limit risk detection. Static limit risk monitoring is based on predetermined risk indicators (i.e., trading limits) set by the trader's authority or counterparty, such as the maximum single transaction amount (e.g., ≤100 million yuan per transaction) and daily / monthly cumulative transaction limits (e.g., ≤5 billion yuan per day). For a single bond, this could mean the cumulative amount does not exceed 20% of the issuance amount. However, this static limit risk detection method is not sensitive enough in terms of risk control. Dynamic limit risk detection can be based on real-time exposure limits, calculating the current net exposure limit of the trading portfolio or trader in real time. Intraday exposure limits refer to the maximum unhedged market risk exposure that a trader or trading portfolio is allowed to bear within a trading day. Exposure limits are usually set in the form of notional principal amount or value at risk. However, this dynamic limit risk detection method has the following problems: real-time exposure limits only focus on absolute position size risk, lacking the ability to limit potential intraday losses from the perspective of specific interest rate risk sensitivity, and are difficult to support risk assessment across different product portfolios and are insensitive to risk control in hedging scenarios. Current trading systems export all traded data after market close and perform operations such as data reconciliation, position restoration, and calculation of trading risk indicators. Finally, they aggregate and generate the day's trading risk indicator values ​​overnight as the trading risk detection result. However, the trading risk detection results obtained in this way are delayed, resulting in untimely risk management and making it difficult to guarantee the security of transactions.

[0030] In view of this, and addressing the shortcomings of current static and dynamic limit risk detection methods—namely, their lack of risk sensitivity, difficulty in supporting cross-product portfolio risk assessment, and inability to guarantee transaction security—this application provides a transaction risk detection method to resolve scenarios where cross-product risk comparison fails and hedging efficiency is distorted, thereby improving transaction security. Specifically, the method includes: responding to a transaction processing task received in a thread pool; parsing the transaction processing task to obtain transaction parameters, wherein the transaction processing task is generated based on a transaction processing request; determining the expected incremental risk indicator value generated by processing the transaction processing request based on the transaction parameters; updating existing risk indicator values ​​related to the transaction processing request using the expected incremental risk indicator value to obtain an updated risk indicator value; and detecting the updated risk indicator value based on a predetermined risk threshold to obtain the risk detection result of the transaction processing request.

[0031] Figure 1 The illustration shows an application scenario of the transaction risk detection method and apparatus according to embodiments of this application.

[0032] like Figure 1 As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0033] Users can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0034] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0035] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0036] It should be noted that the transaction risk detection method provided in this application embodiment can generally be executed by server 105. Correspondingly, the transaction risk detection device provided in this application embodiment can generally be located in server 105. The transaction risk detection method provided in this application embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the transaction risk detection device provided in this application embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0037] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0038] The following will be based on Figure 1 The described scene, through Figures 2-3 The transaction risk detection method according to the embodiments of this application will be described in detail.

[0039] Figure 2 A flowchart illustrating a transaction risk detection method according to an embodiment of this application is shown.

[0040] like Figure 2 As shown, the transaction risk detection method in this embodiment includes operations S210 to S240.

[0041] In operation S210, in response to receiving a transaction processing task in the thread pool, the transaction processing task is parsed to obtain the transaction parameters.

[0042] The transaction processing task is generated based on the transaction processing request.

[0043] According to the embodiments of this application, the above-mentioned transaction processing task may be, for example, a purchase operation of bonds or bond derivatives by relevant personnel (e.g., a trader).

[0044] In operation S220, the expected incremental risk indicator value generated by processing the transaction processing request is determined based on the transaction parameters.

[0045] According to the embodiments of this application, the above-mentioned transaction parameters may include transaction amount, transaction product, duration of transaction product, etc.

[0046] According to the embodiments of this application, the aforementioned expected incremental risk indicator value can be the DV01 (Dollar Value of 01) value calculated for the transaction processing request. DV01 represents the amount by which the value of the bond portfolio changes when the yield changes by one basis point.

[0047] In operation S230, the existing risk indicator values ​​related to the transaction processing request are updated using the expected incremental risk indicator values ​​to obtain updated risk indicator values.

[0048] In operation S240, the updated risk indicator value is detected based on a predetermined risk threshold to obtain the risk detection result of the transaction processing request.

[0049] According to the embodiments of this application, the aforementioned predetermined risk threshold may be the DV01 limit value, where the DV01 limit refers to the maximum duration value risk that a trader or trading portfolio is allowed to bear.

[0050] In some embodiments, the predetermined risk threshold can be set by users based on custom product portfolios (e.g., a combination of bonds and derivatives) and user groups. Warning and alert values ​​can be set; for example, a first risk threshold can be set as the warning value, and a second risk threshold greater than the first risk threshold can be set as the alert value. In some embodiments, the predetermined risk threshold can also have its effective and ineffective time intervals, transaction triggering nodes (e.g., transaction trial calculation, transaction execution, transaction approval, timed monitoring, etc.), and notification methods set, enabling diverse settings for the predetermined risk threshold. The process of setting the predetermined risk threshold can be shown in Table 1.

[0051] Table 1

[0052]

[0053] Preset risk thresholds can be set as shown in Table 1. The limit name can be the name of the preset risk threshold. The account type can be the account type of the trading object related to the trading product, such as an individual or a company. Business type 1 is, for example, a major business category, such as financial services or credit card services; business type 2 is, for example, a minor business category, such as personal time deposits. Trading products can be, for example, bonds. A trading product portfolio can be, for example, a combination of various bonds. The over-limit alert role is, for example, the entity that needs to be alerted when risk is detected, such as the relevant trader or operations personnel.

[0054] For example, consider a transaction processing task where counterparty 1 purchases 10,000 yuan of Bond A. Bond A has a duration of 5 years, and the corresponding expected incremental risk indicator value is 5. If counterparty 1 originally held 5 million yuan of Bond A, with an existing risk indicator value of 2500, then the existing risk indicator value of 2500 is updated using the expected incremental risk indicator value of 5, resulting in an updated risk indicator value of 2505. If the predetermined risk threshold is 3000, then the risk detection result of this transaction processing task is safe, and no warning will be triggered.

[0055] According to the embodiments of this application, when multiple transaction processing tasks occur simultaneously in the thread pool, the expected incremental risk corresponding to each transaction processing task can be calculated in parallel, and the existing risk indicator value can be updated based on all expected incremental risks to obtain the updated risk indicator value.

[0056] According to the embodiments of this application, by parsing each transaction processing task in the thread pool and calculating the expected incremental risk indicator value in real time based on the parsed transaction parameters, the complex calculation task is broken down into simple calculation tasks for each transaction processing task, improving the processing efficiency of the trading system. The expected incremental risk indicator value is then superimposed on the existing risk indicator value to obtain an updated risk indicator value, calculating the real-time risk indicator value corresponding to the transaction processing task. Finally, based on a predetermined risk threshold and the updated risk indicator value, the risk detection result of the transaction processing request is output in real time. Thus, the corresponding risk indicator value is calculated in real time for each transaction processing task, enabling timely control of each transaction processing task and improving the security of the trading system.

[0057] According to an embodiment of this application, the above-mentioned transaction parameters include the transaction product; the risk detection result of the transaction processing request is obtained by detecting the updated risk indicator value based on a predetermined risk threshold, including: calling multiple predetermined risk thresholds related to the transaction product according to the identifier of the transaction product, wherein the predetermined risk thresholds are configured with an effective period; determining a target predetermined risk threshold from the multiple predetermined risk thresholds according to the relationship between the timestamp of the transaction processing request and the effective period; and detecting the updated risk indicator value using the target predetermined risk threshold to obtain the risk detection result of the transaction processing request.

[0058] For example, for trading product A (duration of 5 years), the trading product identifier is: A, and the corresponding pre-defined risk thresholds for the effective period are: 9:00~12:00: 2200; 12:00~14:30: 2000. If the timestamp of the transaction processing request is 11:00, then the target pre-defined risk threshold is 2200. If the transaction processing request is to buy 5 million of trading product A, the corresponding updated risk threshold is 2500. Since it is greater than 2200, the risk detection result can be considered unsafe, and a warning will be issued to the relevant user (e.g., a trader).

[0059] For example, for trading product A (duration of 5 years), the trading product is identified as A, and the corresponding pre-defined risk thresholds for the effective period are as follows: Day D of Month M, Year Y ~ Day D+1 of Month M, Year Y: 2200; Day D+2 of Month M, Year Y ~ Day D+3 of Month M, Year Y: 2000. If the timestamp of the transaction processing request is Day D of Month M, Year Y, then the target pre-defined risk threshold is 2200. If the transaction processing request is to buy 5 million of trading product A, the corresponding updated risk threshold is 2500. Since it is greater than 2200, the risk detection result can be considered unsafe, and a warning will be issued to the relevant user (e.g., a trader).

[0060] According to the embodiments of this application, by setting predetermined risk thresholds corresponding to multiple effective time periods for transaction products, the system will automatically determine the target predetermined risk threshold from the predetermined risk thresholds based on the relationship between the timestamp of the transaction processing request and the effective time period, thereby improving the accuracy of transaction risk detection.

[0061] According to an embodiment of this application, the aforementioned transaction parameters further include transaction triggering node information that triggers the transaction processing request, and the risk detection result of the transaction processing request includes risk warning information; the risk detection result of the transaction processing request is obtained by detecting the updated risk indicator value using a target predetermined risk threshold, including: determining the risk level information corresponding to the transaction processing request based on the relationship between the updated risk indicator value and the target predetermined risk threshold; obtaining the generation method for generating risk warning information based on the risk level information and the transaction triggering node information; calling the information template of the risk warning information according to the identifier of the generation method; and filling the information template with the risk level information to obtain the risk warning information.

[0062] According to the embodiments of this application, the aforementioned transaction triggering node information may include, for example, a transaction trial calculation node, a transaction execution node, a transaction approval node, and a timed monitoring node. Different transaction triggering nodes can correspond to different risk warning methods. For example, if a risk alarm is triggered at the transaction trial calculation node, relevant staff (such as traders or maintenance personnel) can be notified via pop-up windows or emails. If a risk alarm is triggered at the transaction execution node, relevant staff can be notified via SMS. If a risk alarm is triggered at the transaction approval node, relevant staff can be notified via SMS or emails. If a risk alarm is triggered at the timed monitoring node, relevant staff can be notified via emails.

[0063] According to the embodiments of this application, by setting different risk warning modes at different transaction triggering nodes, differentiated risk level warnings can be achieved, which also helps relevant personnel determine the risk level of the current transaction based on the warning method, thereby improving the efficiency of transaction risk handling.

[0064] According to the embodiments of this application, the aforementioned target predetermined risk threshold includes a first risk threshold and a second risk threshold greater than the first risk threshold; the risk level information corresponding to the transaction processing request is determined based on the relationship between the updated risk indicator value and the target predetermined risk threshold, including: determining the transaction processing request as a warning risk level when the updated risk indicator value is greater than the first risk threshold and less than the second risk threshold; and determining the transaction processing request as an alarm risk level when the updated risk indicator value is greater than or equal to the second risk threshold.

[0065] For example, if the first risk threshold is set to 2000 and the second risk threshold is set to 2500, then for a case where the updated risk indicator value is 2200, the transaction processing request can be determined to be at the warning risk level.

[0066] According to the embodiments of this application, after determining that a transaction processing request is at a warning risk level, the system will automatically send an alert to relevant personnel to remind them that the risk is approaching the limit and requires attention. The alert may include relevant information such as the limit name, account type, business category, business subcategory, financial product, investment portfolio, DV01 currency, DV01 limit value, DV01 warning value, limit effective range, calculation trigger method, and the role for exceeding the limit reminder.

[0067] Once a transaction processing request is determined to be at an alarm risk level, relevant staff will be notified so that traders can take action to reduce the risk or terminate the current transaction processing task directly, such as by closing out positions or hedging.

[0068] According to an embodiment of this application, the aforementioned information template could be, for example, "Please note that the current DV01 is XX, the warning value is XX, the warning has been exceeded by XX%, the limit is XX, and the limit has not been exceeded." Further, by filling in the XX in the aforementioned information template according to risk level information, the risk warning information could be, for example, "Please note that the current DV01 is 2200, the warning value is 2000, the warning has been exceeded by 10%, the limit is 2500, and the limit has not been exceeded."

[0069] According to the embodiments of this application, the risk range is divided into three levels: normal, warning, and alarm, by using a first risk threshold and a second risk threshold. This can avoid extreme misjudgments caused by a single threshold and can promptly remind relevant personnel before the risk level is upgraded, thereby avoiding greater losses.

[0070] According to an embodiment of this application, the above-mentioned transaction parameters also include transaction objects; determining the expected incremental risk index value generated by processing the transaction processing request based on the transaction parameters includes: determining the transaction product associated with the transaction object; determining the object dimension risk index value on a per-transaction basis based on the transaction data of the transaction product; and superimposing the object dimension risk index values ​​of the transaction objects to obtain the expected incremental risk index value of the transaction object group, wherein the transaction object group is composed of transaction objects.

[0071] According to the embodiments of this application, the aforementioned trading objects can purchase multiple trading products. For example, the trading object group includes trading object 1 and trading object 2. Trading object 1 purchases trading product A and trading product B. Therefore, the object-dimensional risk indicator value of trading object 1 needs to be calculated based on the sub-risk indicator values ​​corresponding to trading product A and trading product B respectively. Assuming the sub-risk indicator value for trading product A is 2 million and the sub-risk indicator value for trading product B is 3 million, then the object-dimensional risk indicator value for trading object 1 is 5 million. Trading object 2 only purchases trading product A, with a corresponding sub-risk indicator value of 1 million. Therefore, the object-dimensional risk indicator value for trading object 2 is 1 million, and thus the expected incremental risk indicator value for the trading object group is calculated to be 6 million.

[0072] According to the embodiments of this application, the aforementioned transaction data includes incremental scale data of the transaction products and transaction risk coefficients; based on the transaction data of the transaction products, determining the object-dimensional risk indicator value on a per-transactional-object basis includes: for each transaction product, processing the existing scale data of the transaction product using the incremental scale data of the transaction product to obtain the target scale data of the transaction product; generating sub-risk indicator values ​​of the transaction product based on the target scale data and the transaction risk coefficients; and superimposing the sub-risk indicator values ​​of each transaction product of the transaction object to obtain the object-dimensional risk indicator value.

[0073] According to the embodiments of this application, the aforementioned incremental scale data may be, for example, the position (i.e., the amount of funds) of the trading product, and the aforementioned trading risk coefficient may be, for example, the duration of the trading product. Duration is the time to maturity of the present value weighted average of the present value of bond cash flows, which reflects the sensitivity of bond prices to interest rate changes.

[0074] In some embodiments, the process of generating sub-risk index values ​​for trading products based on target size data and trading risk coefficients can be as shown in formula (1).

[0075] The sub-risk indicator value of the trading product = the target size data of the trading product × the duration of the trading product × 0.0001 (1)

[0076] Among them, the target size data of the trading product can be the position of the trading product, and the trading risk coefficient can be the product of the duration of the trading product and 0.0001.

[0077] For example, for trading product A, the incremental size of the transaction processing request is 1 million. If the existing size of trading product A is 2 million, then the target size of trading product A is 3 million. If the transaction risk coefficient of trading product A is 19 years, then the sub-risk index value of the trading product is 3 million × 19 × 0.0001 = 5700.

[0078] According to the embodiments of this application, target-scale data is obtained by processing existing-scale data with incremental-scale data, and then sub-risk indicator values ​​for the trading product are derived. This allows for the real-time calculation of the impact of a single transaction processing task on the target-scale data as a sub-risk indicator value. These sub-risk indicator values ​​are then superimposed according to the trading object dimension to obtain the object-level risk indicator value. This achieves dynamic updating of the trading object-level risk indicator value, improving the timeliness and accuracy of risk management. Furthermore, the process considers duration, an interest rate risk dimension, enhancing the accuracy of risk detection.

[0079] Figure 3 A schematic diagram of risk detection results according to an embodiment of this application is shown.

[0080] like Figure 3 As shown, the risk detection results include a header title, investment portfolio, over-limit details, report date, report time, and report currency. It displays the warning and limit status of a specific trading portfolio on the DV01 limit, along with relevant information such as the report date, time, and report currency for review by relevant personnel. In some embodiments, it can generate results daily or even multiple times within a day. Figure 3 The risk assessment results shown detail the transaction risk assessment process for review by relevant personnel.

[0081] Figure 4 A flowchart illustrating a transaction risk detection method according to another embodiment of this application is shown.

[0082] like Figure 4 As shown, the transaction risk detection method in this embodiment includes operations S410 to S430.

[0083] In operation S410, a predetermined risk threshold is set.

[0084] The predetermined risk threshold can be set based on multiple dimensions, including user-defined product portfolios (such as a combination of bonds and bond derivatives), portfolio tree nodes, and user groups. The portfolio tree nodes can be a tree structure composed of hierarchical portfolios. The predetermined risk threshold can include a first risk threshold and a second risk threshold, with the first risk threshold accounting for 80% of the second risk threshold. The predetermined risk threshold can also be configured with effective and ineffective time intervals, transaction trigger nodes (such as transaction trial calculation, transaction execution, transaction approval, and scheduled monitoring), and notification methods. See Table 1 for details.

[0085] In operation S420, the expected incremental risk indicator value is calculated and compared with the predetermined risk threshold.

[0086] For example, when a transaction flows in, a transaction event-driven limit calculation is used. Each inflow of transaction generates a transaction processing task to calculate the expected incremental risk indicator value generated by the current transaction. The impact of all inflow transactions on the existing risk indicator value is calculated in parallel using a thread pool to achieve real-time DV01 monitoring (at the second level). The DV01 values ​​of different assets are compared with the predetermined risk threshold of operation S410, and the comparison results are recorded.

[0087] In some embodiments, the current intraday expected incremental risk indicator value (calculated per position) can be calculated for each trader / trading portfolio. The calculation process is as follows, taking the calculation of the expected incremental risk indicator value for bonds as an example.

[0088] Iterate through the bond-related parameters in Table 1, calculate and summarize the corresponding existing risk indicator values ​​based on the product type and portfolio of the current inflow transaction, and obtain the risk detection result of the current inflow transaction. For example, first, based on the transaction portfolio, transaction object group, and transaction object of the current inflow transaction, find all bonds and positions of the corresponding transaction group, and add the position of the current inflow transaction. For example, calculate the risk indicator value of the object dimension of each transaction object. For each bond of the transaction object, the sub-risk indicator value is: bond position × bond duration × 0.0001. Then, add the sub-risk indicator values ​​of each bond to obtain the risk indicator value of the object dimension of the transaction object. Add the risk indicator values ​​of the object dimension of each transaction object to obtain the expected incremental risk indicator value of the transaction object group.

[0089] The updated risk indicator value is obtained by adding the expected incremental risk indicator value to the existing risk indicator value and then comparing it with the predetermined risk threshold.

[0090] If the updated risk indicator value is ≤100% × the first risk threshold, it is considered a normal transaction. If 100% × the first risk threshold is ≤ the updated risk indicator value < 100% × the second risk threshold, it is considered a warning level transaction. A limit warning or over-limit email notification will be sent to the maintenance email notification provider. If the updated risk indicator value is >100% × the second risk threshold, it is considered an alarm level transaction. A limit warning or over-limit email will be sent to the maintenance email notification provider, and the current transaction will be terminated.

[0091] The calculation of the expected incremental risk index value for bond derivatives is the same as the above process. The expected incremental risk index value for each transaction under the trading portfolio and user dimension can be calculated separately. The expected incremental risk index values ​​of all transactions are added together to obtain the expected incremental risk index value of bond derivatives.

[0092] When operating S430, if the expected incremental risk indicator value exceeds the predetermined risk threshold, notify the relevant personnel.

[0093] If the expected incremental risk indicator value exceeds the predetermined risk threshold, an appropriate reminder will be issued and an over-limit report will be generated according to the reminder method set in operation S410. For example, a transaction pop-up will remind the trader of the over-limit situation, and the supervisor will be notified via email, SMS, etc. The system also supports the business to select multi-level approval or termination of operation for the over-limit data.

[0094] The transaction risk detection method provided in this application, through hierarchical settings, real-time monitoring, early warning and alarm functions, and over-limit handling procedures, can ensure transaction security. The transaction risk detection method provided in this application can calculate the expected incremental risk indicator value for each transaction in real time, achieving timely risk detection. Furthermore, determining the expected incremental risk indicator value based on the interest rate dimension improves the accuracy of risk detection. Moreover, the standardized calculation process and automated risk monitoring and alarm functions enhance the executability and efficiency of risk detection, effectively guaranteeing transaction security.

[0095] Based on the above-mentioned transaction risk detection method, this application also provides a transaction risk detection device. The following will be combined with... Figure 5 The device is described in detail.

[0096] Figure 5 A schematic block diagram of a transaction risk detection device according to an embodiment of this application is shown.

[0097] like Figure 5 As shown, the transaction risk detection device 500 of this embodiment includes a parsing module 510, a determining module 520, an updating module 530, and a detection module 540.

[0098] The parsing module 510 is used to respond to the transaction processing task received in the thread pool, parse the transaction processing task, and obtain the transaction parameters. The transaction processing task is generated based on the transaction processing request.

[0099] The determination module 520 is used to determine the expected incremental risk indicator value generated by processing the transaction processing request based on the transaction parameters.

[0100] The update module 530 is used to update the existing risk indicator values ​​related to the transaction processing request using the expected incremental risk indicator values, so as to obtain updated risk indicator values.

[0101] The detection module 540 is used to detect the updated risk indicator value based on a predetermined risk threshold to obtain the risk detection result of the transaction processing request.

[0102] According to an embodiment of this application, the detection module 530 may include a calling submodule, a first determining submodule, and a detection submodule. The calling submodule is used to call multiple predetermined risk thresholds related to the transaction product based on the identifier of the transaction product, and the predetermined risk thresholds are configured with effective time periods. The first determining submodule is used to determine a target predetermined risk threshold from the multiple predetermined risk thresholds based on the relationship between the timestamp of the transaction processing request and the effective time period. The detection submodule is used to detect the updated risk indicator value using the target predetermined risk threshold to obtain a risk detection result for the transaction processing request.

[0103] According to embodiments of this application, the detection submodule may include a determining unit, an acquiring unit, a calling unit, and a filling unit. The determining unit is used to determine the risk level information corresponding to the transaction processing request based on the relationship between the updated risk indicator value and the target predetermined risk threshold. The acquiring unit is used to acquire the generation method for generating risk warning information based on the risk level information and transaction trigger node information. The calling unit is used to call the information template for risk warning information according to the identifier of the generation method. The filling unit is used to fill the information template with the risk level information to obtain the risk warning information.

[0104] According to embodiments of this application, the determining unit may include a first determining subunit and a second determining subunit. The first determining subunit is configured to determine a transaction processing request as a warning risk level when the updated risk indicator value is greater than a first risk threshold and less than a second risk threshold. The second determining subunit is configured to determine a transaction processing request as an alarm risk level when the updated risk indicator value is greater than or equal to the second risk threshold.

[0105] According to embodiments of this application, the determining module 520 may include a second determining submodule, a third determining submodule, and an overlay submodule. The second determining submodule is used to determine the trading products associated with the trading object. The third determining submodule is used to determine the object-dimensional risk indicator value on a per-trading-object basis based on the trading data of the trading products. The overlay submodule is used to overlay the object-dimensional risk indicator values ​​of the trading objects to obtain the expected incremental risk indicator value for a group of trading objects, where the group of trading objects consists of trading objects.

[0106] According to embodiments of this application, the third determining submodule may include a processing unit, a generation unit, and an overlay unit. The processing unit is used to process the existing size data of each trading product using incremental size data of the trading product to obtain target size data for the trading product. The generation unit is used to generate sub-risk indicator values ​​for the trading product based on the target size data and the trading risk coefficient. The overlay unit is used to overlay the sub-risk indicator values ​​of each trading product for the trading object to obtain an object-dimensional risk indicator value.

[0107] According to embodiments of this application, any plurality of modules among the parsing module 510, determining module 520, updating module 530, and detecting module 540 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this application, at least one of the parsing module 510, determining module 520, updating module 530, and detecting module 540 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the parsing module 510, determining module 520, updating module 530, and detecting module 540 can be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0108] Figure 6 A block diagram schematically illustrates an electronic device suitable for implementing a transaction risk detection method according to an embodiment of this application.

[0109] like Figure 6As shown, an electronic device 600 according to an embodiment of this application includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage portion 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0110] RAM 603 stores various programs and data required for the operation of electronic device 600. Processor 601, ROM 602, and RAM 603 are interconnected via bus 604. Processor 601 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 602 and / or RAM 603. It should be noted that the programs may also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0111] According to embodiments of this application, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to a bus 604. The electronic device 600 may also include one or more of the following components connected to the input / output (I / O) interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 610 as needed so that computer programs read from it can be installed into the storage section 608 as needed.

[0112] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0113] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this application, the computer-readable storage medium may include ROM 602 and / or RAM 603 and / or one or more memories other than ROM 602 and RAM 603 described above.

[0114] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code enables the computer system to implement the transaction risk detection method provided in the embodiments of this application.

[0115] When the computer program is executed by the processor 601, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0116] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 609, and / or installed from the removable medium 611. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0117] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, it performs the functions defined in the system of this application embodiment. According to the embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0118] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0120] Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application.

Claims

1. A method for detecting transaction risk, characterized in that, The method includes: In response to receiving a transaction processing task in the thread pool, the transaction processing task is parsed to obtain transaction parameters, wherein the transaction processing task is generated based on the transaction processing request; Based on the transaction parameters, determine the expected incremental risk indicator value generated by processing the transaction processing request; The existing risk indicator values ​​related to the transaction processing request are updated using the expected incremental risk indicator value to obtain the updated risk indicator value. The risk detection result of the transaction processing request is obtained by detecting the updated risk indicator value based on a predetermined risk threshold.

2. The method according to claim 1, characterized in that, The transaction parameters include the transaction products; The step of detecting the updated risk indicator value based on a predetermined risk threshold to obtain the risk detection result of the transaction processing request includes: Based on the identifier of the trading product, multiple predetermined risk thresholds related to the trading product are invoked, and the predetermined risk thresholds are configured with an effective period. Based on the relationship between the timestamp of the transaction processing request and the effective period, a target predetermined risk threshold is determined from a plurality of predetermined risk thresholds; The risk detection result of the transaction processing request is obtained by using the target predetermined risk threshold to detect the updated risk indicator value.

3. The method according to claim 2, characterized in that, The transaction parameters also include transaction triggering node information that triggers the transaction processing request, and the risk detection result of the transaction processing request includes risk warning information; The step of detecting the updated risk indicator value using the target predetermined risk threshold to obtain the risk detection result of the transaction processing request includes: Based on the relationship between the updated risk indicator value and the target predetermined risk threshold, the risk level information corresponding to the transaction processing request is determined; Based on the risk level information and the transaction trigger node information, obtain the generation method used to generate the risk warning information; Based on the identifier of the generation method, the information template of the risk warning information is invoked; The risk warning information is obtained by filling the information template with the risk level information.

4. The method according to claim 2, characterized in that, The target predetermined risk threshold includes a first risk threshold and a second risk threshold that is greater than the first risk threshold; The step of determining the risk level information corresponding to the transaction processing request based on the relationship between the updated risk indicator value and the target predetermined risk threshold includes: If the updated risk indicator value is greater than the first risk threshold and less than the second risk threshold, the transaction processing request is determined to be at the early warning risk level. If the updated risk indicator value is greater than or equal to the second risk threshold, the transaction processing request is determined to be at the alarm risk level.

5. The method according to claim 2, characterized in that, The transaction parameters also include the transaction object; The step of determining the expected incremental risk indicator value generated by processing the transaction processing request based on the transaction parameters includes: Identify the transaction product associated with the transaction object; Based on the transaction data of the transaction products, determine the risk index value of the object dimension with the transaction object as the unit; The expected incremental risk index value of the transaction object group is obtained by superimposing the object dimension risk index values ​​of the transaction object group, which is composed of the transaction objects.

6. The method according to claim 5, characterized in that, The transaction data includes the incremental scale data of the transaction product and the transaction risk coefficient; The step of determining the object-dimensional risk indicator value based on the transaction data of the transaction product, with the transaction object as the unit, includes: For each of the aforementioned trading products, the existing size data of the trading product is processed using the incremental size data of the trading product to obtain the target size data of the trading product; Based on the target size data and the transaction risk coefficient, sub-risk indicator values ​​for the transaction product are generated; The risk index value of the object dimension is obtained by superimposing the sub-risk index values ​​of each of the transaction products of the transaction object.

7. A transaction risk detection device, characterized in that, The device includes: The parsing module is used to respond to a transaction processing task received in the thread pool, parse the transaction processing task, and obtain transaction parameters, wherein the transaction processing task is generated based on the transaction processing request; The determination module is used to determine the expected incremental risk indicator value generated by processing the transaction processing request based on the transaction parameters. The update module is used to update the existing risk indicator values ​​related to the transaction processing request using the expected incremental risk indicator value, so as to obtain the updated risk indicator value. The detection module is used to detect the updated risk indicator value based on a predetermined risk threshold and generate a risk detection result for the transaction processing request.

8. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 6.

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