Rule-based service identification method and device, equipment and storage medium

Abstract

The invention relates to the technical field of data processing, and discloses a rule-based business identification method and device, equipment and a storage medium, and the method comprises the steps: obtaining the identification information of a target object, and extracting a target field associated with the object from a database based on the identification information; inputting the target field into a preset rule set, and executing matching through conditional logic to obtain a rule matching state set; determining a target rule expression according to the matching state set, and calculating the target rule expression to generate a corresponding service identifier processing result; and establishing association between the processing result and the target object to form corresponding service identification information. According to the invention, structuring, automation and high efficiency of service identifier generation can be realized, and the problems of delay and inconsistency of manual configuration are avoided; the service judgment accuracy is improved, and the flexibility and expansibility of rule processing are improved, so that the system can quickly adapt to complex and changeable service scenes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a rule-based business identification method and device, equipment and a storage medium. BACKGROUND

[0002] With the rapid development of banking business, the characteristics of customer groups are increasingly diversified. Banks need to accurately divide and label customer groups according to customer attributes, transaction behavior and business planning to support credit approval, risk control and marketing and other business scenarios. In the prior art, customer group tagging rules are usually directly embedded in the business system in a hard-coded manner, that is, each rule is fixedly written into the program logic, and is updated through code compilation and deployment. Although this method can ensure the determinacy of rule execution, it has inherent deficiencies in flexibility and maintainability in the case of a large number of rules, complex scenarios and frequent adjustments.

[0003] The existing hard-coded method exposes many problems in practical application: first, each rule update requires re-development, compilation and deployment, and the update cycle often exceeds 24 hours, which cannot meet the needs of rapid business response; second, there are rule redundancies and conflicts in multiple business scenarios, making it difficult to achieve flexible reuse and management of rules through static code structures; third, as the business complexity increases, hard coding leads to high coupling of rule logic, making it difficult to support multi-department collaboration and rapid expansion. SUMMARY

[0004] Therefore, the embodiments of the present application provide a rule-based business identification method, device, equipment and storage medium, which can effectively solve the problems of hard-coded rules in the prior art, re-development and deployment of rule updates, long update cycle, and rule redundancy and conflict in multiple scenarios.

[0005] In a first aspect, the embodiments of the present application provide a rule-based business identification method, comprising: Obtaining identification information of a target object, and extracting a target field from a database based on the identification information; Matching according to the target field and the condition logic in the preset rule set to obtain a rule matching state set; Determining a target rule expression based on the rule matching state set, and calculating the target rule expression to obtain a business identification processing result; Associating the business identification processing result with the target object to form corresponding business identification information.

[0006] In some embodiments, the method further comprises: write the service identification information into an identification storage area associated with the target object.

[0007] In some embodiments, the method further comprises, before the obtaining the identification information of the target object: selecting, based on a rule version control policy, a current effective rule set from a plurality of rule versions, and using the rule set as the preset rule set for conditional logic matching.

[0008] In some embodiments, the obtaining the identification information of the target object and extracting the target field from the database based on the identification information comprises: obtaining a unique identifier of the target object; constructing a database query instruction based on the unique identifier; executing the query instruction to extract the target field from the database.

[0009] In some embodiments, the matching according to the target field and the conditional logic in the preset rule set to obtain a rule matching state set comprises: loading the target field into a rule cache area; invoking the conditional logic in the preset rule set in the rule cache area; generating a rule matching state set based on the determination state of the target field and the conditional logic.

[0010] In some embodiments, the determining a target rule expression based on the rule matching state set and performing calculation on the target rule expression to obtain a service identification processing result comprises: extracting a target rule item satisfying a matching condition from the rule matching state set; determining a corresponding rule expression template based on the target rule item; performing variable substitution on the rule expression template to generate a calculable target rule expression; performing calculation on the target rule expression to obtain a corresponding service identification processing result.

[0011] In some embodiments, the associating the service identification processing result with the target object to form corresponding service identification information comprises: constructing an object mapping structure based on a unique identifier of the target object; encapsulating the service identification processing result as structured identification data; binding the structured identification data with the object mapping structure to generate service identification information corresponding to the target object.

[0012] Secondly, embodiments of this application provide a rule-based service identification device, comprising: The rule processing module is used to obtain the identification information of the target object and extract the target field from the database based on the identification information; The matching processing module is used to perform matching based on the target field and the conditional logic in the preset rule set to obtain a rule matching status set; The business processing module is used to determine the target rule expression based on the rule matching status set, and to calculate the target rule expression to obtain the business identifier processing result; The data association module is used to associate the business identifier processing result with the target object to form corresponding business identifier information.

[0013] Thirdly, embodiments of this application provide a terminal device, the terminal device including a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the rule-based service identification method of the first aspect described above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium, wherein when the computer program is executed on a processor, it implements the rule-based business identification method of the first aspect described above.

[0015] The embodiments of this application have the following beneficial effects: The identification information of the target object is obtained, and the target field is extracted from the database based on the identification information; the target field and the conditional logic in the preset rule set are matched to obtain a rule matching state set; a target rule expression is determined based on the rule matching state set, and the target rule expression is calculated to obtain a business identification processing result; the business identification processing result is associated with the target object to form corresponding business identification information. Through the solution of this application, accurate matching and judgment of the target field and rule conditions are achieved, ensuring the logical consistency and accuracy of the business identification generation process; at the same time, based on structured expression calculation and result association, the generation efficiency and scalability of business identification information are improved, enabling stable application in diverse business scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1A flowchart of a rule-based business identification method according to an embodiment of this application is shown; Figure 2 This illustration shows a schematic diagram of the rule version control strategy and rule set distribution and loading mechanism in the rule-based business identification method of this application embodiment; Figure 3 This paper illustrates a structural schematic diagram of a rule-based business identification device according to an embodiment of this application. Detailed Implementation

[0018] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0019] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0020] In the following text, the terms "comprising," "having," and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more combinations thereof. Furthermore, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0021] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0022] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0023] Considering the problems in existing technologies, such as rules being hard-coded into business code, the need for redevelopment and deployment for rule updates, long update cycles, and redundant and conflicting rules in multiple scenarios, this application proposes a rule-based business identification method. This method combines the identification information of the target object with the target field extracted from the database and performs matching calculations based on the conditional logic in the preset rule set to generate and associate business identification information, thereby achieving flexible configuration and rapid activation of rules.

[0024] The following examples illustrate this rule-based business identification method.

[0025] Figure 1 A flowchart of a rule-based service identification method according to an embodiment of this application is shown. Exemplarily, the rule-based service identification method includes the following steps: Step S100: Obtain the identification information of the target object, and extract the target field from the database based on the identification information.

[0026] The target object's identification information refers to the data identifier used to uniquely identify customers, applications, or organizations during business processing, and is used to accurately locate data records in the database. Based on this identification information, target fields related to rule determination can be further extracted.

[0027] For example, when the target is a loan application, its identification information may include the application number (applyNo) and the customer number (custNo). The system first retrieves the corresponding record in the database table using this identification information, and then extracts fields related to the rules, such as the user's age ($age) and the credit extension tag ($lowerTierTag).

[0028] In other implementations, the target object may also be a company object, whose identification information is companyNo, and the corresponding target fields extracted may include the company's credit rating or the number of historical transactions.

[0029] In an optional embodiment, step S100 includes the following sub-steps: S101, obtain the unique identifier of the target object.

[0030] Among them, the unique identifier refers to the key value that can uniquely locate a record in the database, ensuring the uniqueness and accuracy of the extracted fields.

[0031] For example, when querying the customer table c_customer, custNo can be used as a unique identifier; when querying the application table ap_apply, applyNo can be used as a unique identifier. That is, the unique identifier for the target object can be applyNo, custNo, or companyNo, and this type of identifier can uniquely identify the business object record in the database.

[0032] In other implementations, the unique identifier can be used in combination with a variety of additional attributes to enhance the flexibility and accuracy of data retrieval.

[0033] S102, construct a database query instruction based on a unique identifier.

[0034] Database query commands are retrieval statements generated using Structured Query Language (SCL) and are used to filter desired target fields in a data table. By constructing query commands, the abstract conditional logic in the rule set can be transformed into executable data access operations.

[0035] As an example, when the rule set requires the user's age, a query can be constructed based on the customer ID custNo: SELECT TIMESTAMPDIFF( YEAR, STR_TO_DATE(SUBSTRING(cert_no,7,8),'%Y%m%d'), CURDATE() AS age FROM c_customer WHERE cust_no='C96612978312351744'; Its semantics are: extract the birth date (digits 7-14) from cert_no, parse it into a date, calculate the year difference with the current date, and obtain the integer age. The input is custNo and cert_no, and the output is a single numeric field age.

[0036] For example, when conditional logic needs to determine whether "the legal age has been reached" or "whether it is within a given age range", the age field will be used as an lvalue in comparison operations (such as >=, BETWEEN, etc.).

[0037] In other implementations, the properties of the Apply object (such as applyNo, custNo, companyNo) can be used as SQL parameters to obtain other fields related to the rule conditions.

[0038] S103, execute the query command to extract the target field from the database.

[0039] The target field refers to the atomic field related to the rule conditions, which can be of types such as Int, String, Boolean, and Date. The system uses a dynamic value parsing engine to identify the type of the extracted field values, ensuring accuracy in subsequent logical judgments.

[0040] As an example, when credit extension to the tag is required, it is executed based on the application number (applyNo): SELECT lower_tier_tag FROM ap_apply WHERE apply_no='AP251691569147551745'; Its semantics are: read the lower_tier_tag value corresponding to the specified application; The input is applyNo, and the output is the lower_tier_tag field. It can then be used in a Boolean comparison with the conditional logic "$lowerTierTag!=null&&$lowerTierTag.contains("90241150")" and imported into the "rule matching status set".

[0041] For example, when the label contains "90241150", the judgment status of the corresponding rule item is set to "satisfied", which is used to promote the determination and calculation of the target rule expression.

[0042] In addition, the extracted fields are automatically identified by the dynamic value parsing engine (numeric, string, boolean, date) before entering the matching stage, so as to ensure that the comparison with the condition logic is performed on the premise that the types are consistent.

[0043] In an optional embodiment, the method further includes the following step before step S100: Based on the rule version control strategy, the currently valid rule set is selected from multiple rule versions, and the rule set is used as the preset rule set for conditional logic matching.

[0044] Among them, the rule version control strategy refers to managing and tracking rule sets by version number in the rule engine, establishing inter-version associations through version chains to achieve controlled updates and rollbacks; when an operational anomaly occurs, it can quickly locate and roll back to a historical stable version to ensure business continuity and auditability.

[0045] For example, when the system loads a rule for the first time, it is recorded as... After the upgrade, it will be generated. And in the rule storage structure, the prev_version field points to the previous version; if If an error occurs, the system can use this field to revert to the previous state with one click. During version switching, the system adopts a dual-buffer hot-swap mechanism: after the new rules are loaded in the backup buffer, it seamlessly switches to the main buffer, ensuring that requests in transit continue to use the old rules, and newly triggered requests immediately use the new rules.

[0046] At the rule compilation layer, the system introduces an incremental compilation mechanism. When the rule set changes, only the changed rules are recompiled and loaded, while the compilation results of the unchanged parts are reused. This reduces compilation time, lowers system resource consumption, and enables near real-time hot rule updates. For example, suppose the system already has a rule set... When updated to (of which only) Become When this happens, the system will first detect and mark the changed parts, and only then will it detect and mark the changed parts. Perform a recompile, and then the compiled result With the original The compilation results are merged to generate a new rule set. And it will take effect immediately.

[0047] In other implementations, after a new rule is published in the configuration management console, version broadcasting can be performed through the configuration center, and the changes can be distributed to each rule node using a Kafka message queue, for example, rule node 1, rule node 2, etc.; each node loads and switches rule sets according to a double-buffering process to ensure that the rule execution engine is always available. Figure 2 As shown, this distribution-loading-switching chain demonstrates the operational mechanism of version control strategies at the implementation level.

[0048] Step S200: Match the target field with the conditional logic in the preset rule set to obtain a rule matching status set.

[0049] In this context, conditional logic refers to the judgments defined in the rule set, consisting of fields, operators, and thresholds, and supporting nesting to form compound expressions. To ensure the versatility of rule processing, the database uses structured fields to store atomic rule items, supporting multiple data types such as Int, String, Boolean, and Date. A dynamic value parsing engine automatically identifies the data types to ensure flexible matching in different scenarios. By executing these conditional logics in the rule engine, the satisfaction of target fields can be determined one by one, ultimately forming a rule matching status set.

[0050] For example, when the target fields include $age and $lowerTierTag, the condition logic can be "$ageBETWEEN 18 AND 65" and "$lowerTierTag.contains("90241150")" respectively. After the engine determines the condition, the output state set is: {$age BETWEEN 18 AND 65→TRUE,$lowerTierTag.contains("90241150")→TRUE}.

[0051] In an optional embodiment, step S200 includes the following sub-steps: S201, Load the target field into the rule cache area.

[0052] The rule cache area is the data context space during engine execution, used to store the extracted target fields so that they can be uniformly invoked by multiple conditional logics.

[0053] For example, when retrieved via SQL: When $age=35 and $lowerTierTag="90241150,90241151", this step loads these two field values ​​into the rule cache area, and the dynamic value parsing engine identifies the type to ensure the correctness of subsequent logic execution.

[0054] In other implementations, the target field may also include preset fields such as $drawCheck (supporting 30+ fields) to support more complex rule scenarios.

[0055] S202, Invoke the conditional logic in the preset rule set in the rule cache area.

[0056] In this context, conditional logic execution refers to running rule expressions one by one within the same execution context and generating a judgment state based on the comparison result between field values ​​and thresholds. Conditional logic supports not only eight basic operators (equal to, not equal to, greater than, less than, IN, BETWEEN, etc.) but also four advanced operators (string matching, regular expression matching, logical combination, etc.) and can implement compound atomic rules through nested expressions. The execution of conditional logic is handled by a configuration engine using QLExpress as its execution framework. This engine supports eight basic operators and four advanced operators and allows for the extension of custom operators, with a syntax style similar to Java. During execution, the engine prioritizes blocking sub-scenario rules; if the judgment result is negative, subsequent logic is terminated directly. Non-blocking sub-scenarios employ a "pass if at least one condition is met" strategy.

[0057] For example, when $age=35, the result of executing $age BETWEEN 18 AND 65 is true; When $lowerTierTag contains the characters "90241150", executing $lowerTierTag.contains("90241150") will also return true.

[0058] For example, when $drawCheck==false triggers a blocking sub-scene rule, the system will immediately terminate subsequent logic and output a failed result.

[0059] In other implementations, the conditional logic may contain more complex nested expressions, such as ($age>30&&$drawCheck==true), to support joint determination of multiple conditions.

[0060] S203, based on the determination status of the target field and the condition logic, generate a set of rule matching statuses.

[0061] The rule matching status set is a structured collection that stores the judgment results of conditional logic, recording whether each logic pass or fail. To enhance expressiveness, the system employs a hierarchical rule structure, comprising four levels: field level, operator level, threshold level, and composite atom level. The field level corresponds to atomic fields such as $age and $drawCheck; Operator level corresponds to basic and advanced operators; The threshold level is determined by the dynamic value parsing engine to identify the constant type (such as the numerical value 30, the string "VIP"); Composite atoms support nested expressions, such as: $lowerTierTag!=null&&$lowerTierTag.contains("90241150").

[0062] For example, if $age BETWEEN 18 AND 65 is true, then $lowerTierTag.contains("90241150") is also true. The set of states can then be represented as {$age BETWEEN 18 AND 65→TRUE,$lowerTierTag.contains("90241150")→TRUE}.

[0063] In other implementations, the determination status can be not only a Boolean value, but can also be extended to "partially satisfied" or "weight value" to support more complex business scenarios.

[0064] In other implementations, the system can maintain the rule set in a structured table format. The structured table includes fields such as rule ID (id), rule name (rule_name), rule expression, execution order (rule), and decision reason (reason). Multiple rules are configured in detail within the table. For example, the "pre-verification" rule with id 1 has the rule expression $taskNo=="tk004", the execution order is 1, and the judgment reason is "pre-verification not satisfied"; For example, the rule for "Mobile Number Range" with id 2 has the rule expression $mobileNoSuffix in["130";"131";"132";"133";"134";"135";"136";"137";"138"]. The execution order is 2, and the reason for judgment is "not within the mobile number range", etc. Similarly, the rule for "Non-PLUS Customer" with id 3 has the rule expression $plusCustFlag=="N". The execution order is 3, and the reason for judgment is "PLUS customer", etc.

[0065] This configuration approach enables the rapid invocation of corresponding rule conditions during execution, and after generating a set of rule matching states, it combines the execution order and the reason for judgment to realize traceable business identification logic.

[0066] Furthermore, after generating the rule matching status set, the system organizes and consumes the rules in conjunction with the scenario orchestration configuration. The system stores the mapping relationship between different business scenarios and rules in a table format. The table fields include ID, marking_scene (business scenario), marking_sub_scene (sub-scenario), scene_desc (scenario description), rule_id (list of rule IDs), fail_strategy (failure handling strategy), and rule_seq (execution order). For example, in the "credit pre-screening" scenario where marking_scene is "applyBefore" and marking_sub_scene is "applyBefore", its rule_id list is ["1","2","3","28","5","6","7","8","27"], fail_strategy is "end", and rule_seq is 1, indicating that these rules will be executed sequentially in this scenario, and if a rule is not satisfied, the entire rule chain for the scenario will be terminated immediately. For example, in the "Real-time Marking - General" scenario where marking_scene is "realTimeMarking" and marking_sub_scene is "common", the rule_id list is ["1","2","3","28","5","6","7","8","9","10"], fail_strategy is "continue", and rule_seq is 1, which means that even if a certain rule is not met, subsequent rules will still be executed.

[0067] The `fail_strategy` field controls the execution flow of the rule chain. When it is set to `end`, the scenario is terminated immediately if a rule is not satisfied; when it is set to `continue`, subsequent rules are executed even if a rule is not satisfied. The `rule_seq` field determines the execution order of rules within the scenario, thus ensuring the orderly execution of rules.

[0068] Step S300: Determine the target rule expression based on the rule matching state set, and calculate the target rule expression to obtain the business identifier processing result.

[0069] The target rule expression refers to a computable expression selected based on the rule matching state set. Its core consists of rule items that meet the conditions and their corresponding templates, and is evaluated by the QLExpress engine. This step transforms the judgment result into a specific business identifier output.

[0070] For example, when the rule matching status set contains multiple conditional logics that are true, this step will select the corresponding rule expression and perform calculation. For example, combining $age BETWEEN 18 AND 65 with $lowerTierTag.contains("90241150") will ultimately generate the business identifier processing result.

[0071] In an optional embodiment, step S300 includes the following sub-steps: S301, Extract the target rule item that meets the matching condition from the rule matching state set.

[0072] Among them, the target rule item refers to the conditional logic entry that is determined to be "satisfied" during the matching stage. Its extraction is used to form the basic candidate set for subsequent rule expressions.

[0073] For example, when E_ageRange→TRUE, E_lowerTierTag→TRUE, and E_drawCheck→FALSE are in the set, this step only extracts the first two items to form the target rule item set.

[0074] S302, determine the corresponding rule expression template based on the target rule item.

[0075] Among them, the rule expression template refers to the fixed expression framework corresponding to the target rule item. The variable positions exist in the form of placeholders, waiting to be replaced with actual values ​​or fields in the next step.

[0076] For example, if the target rule is an age range, the corresponding template is: ($age>=A_min&&$age<=A_max); if the target rule is a tag match, the corresponding template is ($lowerTierTag!=null&&$lowerTierTag.contains(T_code)).

[0077] S303 performs variable substitution on the rule expression template to generate a computable target rule expression.

[0078] Variable substitution refers to binding placeholders in the template with actual data, with the dynamic value parsing engine confirming the field type to ensure the correctness of expression execution.

[0079] For example, when $age=35, A_min=18, A_max=65, and T_code="90241150", this step replaces the above values ​​and labels in the template to generate a computable target rule expression: ($age>=18&&$age<=65)&&($lowerTierTag.contains("90241150")).

[0080] S304, calculate the target rule expression to obtain the corresponding business identifier processing result.

[0081] In this context, computation refers to evaluating the target rule expression in the rule engine, outputting a structured result, and using it as input for generating business identification information.

[0082] For example, when the above expression is calculated to have a Boolean value of true, the business identifier processing result output in this step is "meets the rule", which can be used in subsequent binding steps.

[0083] In other implementations, the calculation result can be not only a Boolean value, but also a multi-value enumeration, a score, or a weight, to support more complex business decision logic.

[0084] Step S400: Associate the business identifier processing result with the target object to form corresponding business identifier information.

[0085] The business identifier processing result refers to the final judgment output calculated through rule expressions, which serves to identify the processing status of the target object in the current business scenario. To ensure the traceability of the result, it needs to be bound to the target object to generate business identifier information.

[0086] For example, when the calculation result is "credit conditions are met", the system establishes a correspondence between the result and the application number applyNo=AP251691569147551745, so that the application can be quickly identified through business identification information in subsequent business processes.

[0087] In other implementations, the system can also set an expiration date and version number for the business identification information to support the timeliness management and historical traceability of business status.

[0088] In an optional embodiment, step S400 includes the following sub-steps: S401, construct an object mapping structure based on the unique identifier of the target object.

[0089] The object mapping structure refers to a mapping relationship established using a unique identifier as an index, used to store the business identification information of the target object. This structure can ensure that one object corresponds to one or more sets of identification information.

[0090] For example, when the target object is a customer, the system will create a mapping structure with custNo=C96612978312351744 as the key, so that all business identifiers related to the customer are stored under the same mapping entry.

[0091] As an example, the object mapping structure can be implemented in the form of database tables, key-value stores, or distributed caches to improve query and update efficiency.

[0092] S402 encapsulates the business identifier processing results into structured identifier data.

[0093] Structured identifier data refers to the encapsulation of judgment results in a unified format, including fields such as identifier type, result value, and generation time, to ensure standardization during storage and transmission.

[0094] For example, when the rule expression passes the evaluation, the system will generate a structured data object: {Identifier type: Trust verification, Result: TRUE, Time: 2024-09-20}, and use it as the data unit to be bound.

[0095] As an example, structured identification data can be in JSON, XML, or binary serialization format to support cross-system interface calls; at the same time, the system can also add a signature field to the identification data to verify the integrity of the data during transmission.

[0096] S403 binds the structured identifier data to the object mapping structure to generate business identifier information corresponding to the target object.

[0097] Binding refers to associating and storing the unique identifier of a target object with structured identification data in the object mapping structure, thereby forming the final business identification information. Through this binding, the system can quickly retrieve the business judgment result of the target object in subsequent queries.

[0098] For example, when the customer number is custNo=C96612978312351744, the system will add a record to the object mapping structure, bind {Credit Verification: TRUE, Time: 2025-09-20} to the customer, and generate the final business identification information.

[0099] In other implementations, the binding process may also trigger data persistence, writing business identification information to a log system or external audit system to support compliance checks and business backtracking.

[0100] In an optional embodiment, the rule-based business identification method further includes the following steps: Write the business identification information into the identification storage area associated with the target object.

[0101] The identifier storage area refers to the data storage location reserved by the system for each target object. It is used to permanently store the generated business identifier information, ensuring that this information can be quickly retrieved in subsequent business calls and external interfaces. By writing to this storage area, a stable mapping relationship can be ensured between the business judgment result and the target object.

[0102] For example, when the target object is customer number custNo=C96612978312351744, the system will write the business identification information {credit verification:TRUE, time:2024-09-20} into the corresponding identification storage area. This storage area can be directly accessed in subsequent risk control queries or credit approvals.

[0103] In other implementations, the identifier storage area can be implemented in the form of a database table, a distributed cache, or an object storage; the system can also introduce version number and timestamp fields to record the writing history of identifier information in order to support data consistency verification and audit trail.

[0104] Figure 3A schematic diagram of a rule-based service identification device according to an embodiment of this application is shown. Exemplarily, the service identification device 100 includes: The rule processing module 110 is used to obtain the identification information of the target object and extract the target field from the database based on the identification information; The matching processing module 120 is used to perform matching based on the target field and the conditional logic in the preset rule set to obtain a rule matching status set; The business processing module 130 is used to determine the target rule expression based on the rule matching state set, and to calculate the target rule expression to obtain the business identifier processing result; The data association module 140 is used to establish an association between the business identification processing result and the target object to form corresponding business identification information.

[0105] It is understood that the apparatus of this embodiment corresponds to the method of the above embodiments, and the options in the above embodiments are also applicable to this embodiment, so they will not be described again here.

[0106] This application also provides a terminal device, exemplary of which includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to enable the terminal device to perform the functions of the various modules in the above-described method or apparatus.

[0107] The processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, including at least one of a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Network Processor (NP), Digital Signal Processor (DSP), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0108] The memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory is used to store computer programs, and the processor can execute the computer programs accordingly after receiving execution instructions.

[0109] This application also provides a computer-readable storage medium for storing the computer program used in the aforementioned terminal device. For example, the computer-readable storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0110] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, 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 alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive 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 the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0111] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0112] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a smartphone, personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0113] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A rule-based business identification method, characterized in that, The method includes: Obtain the identification information of the target object, and extract the target field from the database based on the identification information; The target field and the conditional logic in the preset rule set are matched to obtain a rule matching status set; The target rule expression is determined based on the rule matching state set, and the target rule expression is calculated to obtain the business identifier processing result; The business identifier processing result is associated with the target object to form corresponding business identifier information, including: Construct an object mapping structure based on the unique identifier of the target object; The business identifier processing result is encapsulated into structured identifier data; The structured identifier data is bound to the object mapping structure to generate business identifier information corresponding to the target object.

2. The rule-based business identification method according to claim 1, characterized in that, The method further includes: The business identification information is written into the identification storage area associated with the target object.

3. The rule-based business identification method according to claim 1, characterized in that, Before obtaining the identification information of the target object, the process also includes: Based on the rule version control strategy, a set of currently valid rules is selected from multiple rule versions, and the set of rules is used as the preset rule set for conditional logic matching.

4. The rule-based business identification method according to claim 1, characterized in that, The step of obtaining the identification information of the target object and extracting the target field from the database based on the identification information includes: Obtain the unique identifier of the target object; Construct a database query instruction based on the unique identifier; Execute the query instruction to extract the target field from the database.

5. The rule-based business identification method according to claim 1, characterized in that, The step of matching based on the target field and the conditional logic in the preset rule set to obtain a rule matching status set includes: Load the target field into the rule cache area; Invoke the conditional logic in the preset rule set within the rule cache area; Based on the determination status of the target field and the conditional logic, a rule matching status set is generated.

6. The rule-based business identification method according to claim 5, characterized in that, The process of determining the target rule expression based on the rule matching state set and calculating the target rule expression to obtain the business identifier processing result includes: Extract target rule items that meet the matching conditions from the rule matching state set; Determine the corresponding rule expression template based on the target rule item; The variable substitution is performed on the rule expression template to generate a computable target rule expression; The target rule expression is calculated to obtain the corresponding business identifier processing result.

7. A rule-based business identification device, characterized in that, include: The rule processing module is used to obtain the identification information of the target object and extract the target field from the database based on the identification information; The matching processing module is used to perform matching based on the target field and the conditional logic in the preset rule set to obtain a rule matching status set; The business processing module is used to determine the target rule expression based on the rule matching status set, and to calculate the target rule expression to obtain the business identifier processing result; The data association module is used to establish an association between the business identifier processing result and the target object to form corresponding business identifier information, including: Construct an object mapping structure based on the unique identifier of the target object; The business identifier processing result is encapsulated into structured identifier data; The structured identifier data is bound to the object mapping structure to generate business identifier information corresponding to the target object.

8. A terminal device, characterized in that, The terminal device includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the rule-based business identification method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed on a processor, implements the rule-based business identification method according to any one of claims 1-6.

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