CN116521900A - Account abnormity attribution analysis and processing method and device - Google Patents
Account abnormity attribution analysis and processing method and device Download PDFInfo
- Publication number
- CN116521900A CN116521900A CN202310512282.2A CN202310512282A CN116521900A CN 116521900 A CN116521900 A CN 116521900A CN 202310512282 A CN202310512282 A CN 202310512282A CN 116521900 A CN116521900 A CN 116521900A
- Authority
- CN
- China
- Prior art keywords
- entity
- target
- accounting
- account
- model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 107
- 238000003672 processing method Methods 0.000 title claims abstract description 33
- 230000002159 abnormal effect Effects 0.000 claims abstract description 58
- 238000012545 processing Methods 0.000 claims abstract description 58
- 238000000034 method Methods 0.000 claims abstract description 28
- 230000005856 abnormality Effects 0.000 claims abstract description 5
- 239000007787 solid Substances 0.000 claims description 68
- 238000001228 spectrum Methods 0.000 claims description 17
- 238000004422 calculation algorithm Methods 0.000 claims description 15
- 238000004364 calculation method Methods 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 15
- 238000003860 storage Methods 0.000 claims description 11
- 238000010586 diagram Methods 0.000 description 12
- 238000005516 engineering process Methods 0.000 description 9
- 238000010276 construction Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 230000008569 process Effects 0.000 description 5
- 238000011144 upstream manufacturing Methods 0.000 description 4
- 230000002776 aggregation Effects 0.000 description 3
- 238000004220 aggregation Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000004931 aggregating effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 238000010845 search algorithm Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
- G06F16/367—Ontology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/288—Entity relationship models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Animal Behavior & Ethology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computational Linguistics (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The invention provides an account abnormal attribution analysis and processing method and device, relates to the technical field of account data processing, and can be used in the financial field or other technical fields. The method comprises the following steps: acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts; determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model; and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result. The apparatus performs the above method. The method and the device for analyzing and processing the account abnormality attribution can improve the operation efficiency of the account abnormality attribution analysis.
Description
Technical Field
The invention relates to the technical field of financial data processing, in particular to an analysis and processing method and device for account abnormity attribution.
Background
The attribution analysis of the abnormal accounts is widely existing in enterprises of financial classes, and the attribution analysis of the abnormal accounts is mainly realized in a mode of manually analyzing according to a multi-service system in a service processing flow. When abnormal conditions such as error account and account hanging are reflected under the account of the general account subject, the staff of the general account system of the accounting core analyzes the system problem or the problem of the related accounting and clearing system possibly at the upstream, and then the upstream analysis is carried out, and the like, and the upstream accounting and clearing system can also continue to feed back to the analysis of the foreground transaction system after the analysis.
The manual analysis mode of the multi-service system is often required to be based on the technology of each service system and the historical experience of service personnel, the automatic system analysis processing is limited to a single service system, and the analysis of the abnormal problem of the accounts of a large number of cross-service system products is easy to cause the defects of a large number of service and technical manpower investments, and the system has the defects of untimely analysis processing due to the two factors of low communication cost or low personnel maturity of multi-system multi-role personnel, so that the system operation risk and the operation cost are increased.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiment of the invention provides an account anomaly attribution analysis processing method and device, which can at least partially solve the problems in the prior art.
On one hand, the invention provides an account anomaly attribution analysis and processing method, which comprises the following steps:
acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
The obtaining the target general ledger entity containing the target account attribute comprises the following steps:
and retrieving a target general ledger entity containing the target account attribute according to the graph calculation engine.
Wherein the determining, based on the ledger data profile model, a target transaction entity and a target accounting entity associated with the target ledger entity comprises:
searching to obtain a target accounting entity associated with the target general ledger entity according to a preset graph searching algorithm;
and searching to obtain a target transaction entity associated with the target accounting entity according to the preset graph searching algorithm.
Wherein creating the ledger data map model includes:
respectively constructing a transaction detail solid model, an accounting detail solid model and a general account detail and account solid model according to the source data type;
constructing a first association relationship between the transaction detail solid model and the accounting detail solid model, and constructing a second association relationship between the accounting detail solid model, the general ledger detail and the account solid model;
and sequentially combining the transaction detail solid model, the first association relation, the accounting detail solid model, the second association relation, the general ledger detail and the account solid model to obtain the ledger-related data map model.
The method for respectively constructing the transaction detail entity model, the accounting detail entity model, the general account detail and the account entity model according to the source data type comprises the following steps:
and constructing and obtaining the transaction detail entity model, the accounting detail entity model, the general ledger detail and the account entity model according to a pre-written first data processing rule script.
The step of sequentially combining the transaction detail entity model, the first association relation, the accounting detail entity model, the second association relation, the general ledger detail and the account entity model to obtain the ledger data map model comprises the following steps:
and sequentially combining the transaction detail entity model, the first association relation, the accounting detail entity model, the second association relation and the general ledger detail and account entity model according to a pre-written second data processing rule script to obtain the ledger-related data map model.
Before the steps of respectively constructing the transaction detail entity model, the accounting detail entity model, the general ledger detail and the account entity model according to the source data types, the accounting anomaly attribution analysis processing method further comprises the following steps:
acquiring source data according to a pre-written source data acquisition script;
classifying the source data according to the source data type, and storing the classification result into a data lake.
In one aspect, the present invention provides an account anomaly attribution analysis processing apparatus, including:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
a determining unit configured to determine a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and the analysis unit is used for carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
In still another aspect, an embodiment of the present invention provides an electronic device, including: a processor, a memory, and a bus, wherein,
the processor and the memory complete communication with each other through the bus;
the memory stores program instructions executable by the processor, the processor invoking the program instructions capable of performing the method of:
acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
Embodiments of the present invention provide a non-transitory computer readable storage medium comprising:
the non-transitory computer readable storage medium stores computer instructions that cause the computer to perform the method of:
acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
According to the accounting anomaly attribution analysis processing method and device provided by the embodiment of the invention, a target general ledger entity containing target account attributes is obtained according to the target account attributes with accounting anomalies; determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model; the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity; and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result, so that the operation efficiency of the accounting abnormal attribution analysis can be improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
fig. 1 is a flowchart illustrating an accounting anomaly attribution analysis processing method according to an embodiment of the present invention.
Fig. 2 is an explanatory diagram of an account anomaly attribution analysis processing method provided by an embodiment of the present invention.
Fig. 3 is an explanatory diagram of an account anomaly attribution analysis processing method according to another embodiment of the present invention.
Fig. 4 is a schematic structural diagram of an accounting anomaly attribution analysis processing device according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present invention and their descriptions herein are for the purpose of explaining the present invention, but are not to be construed as limiting the invention. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be arbitrarily combined with each other.
Description of related terms:
knowledge graph technology: knowledge graph is a structured knowledge base, a multiple relationship graph, providing the ability to analyze problems from a "relationship" perspective, describing knowledge in three parts, entity, relationship, and attribute. The knowledge graph technology system is a technology for applying a full life cycle around knowledge graph construction, storage and calculation, and is divided into knowledge modeling, knowledge extraction, knowledge storage, knowledge calculation and the like, and relates to technologies such as graph database, graph calculation and the like.
The stream type calculation processing technology comprises the following steps: the streaming computing processing technology provides streaming computing service based on the distributed computing technology, realizes quick processing of transaction information by transaction, and provides real-time transaction processing. A streaming model (Component) implements a processing logic. The streaming model development mainly comprises the steps of model program development, model deployment and the like, and the model generally consumes data from a Kafka message queue.
Fig. 1 is a flow chart of an accounting anomaly attribution analysis processing method according to an embodiment of the present invention, as shown in fig. 1, the accounting anomaly attribution analysis processing method according to an embodiment of the present invention includes:
step S1: and acquiring a target general ledger entity containing the target account attribute according to the target account attribute with abnormal accounts.
Step S2: determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity.
Step S3: and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
In the step S1, the device obtains a target general ledger entity including the target account attribute according to the target account attribute with abnormal accounting. The apparatus may be a computer device performing the method and may comprise, for example, a server. It should be noted that, the data acquisition and analysis according to the embodiments of the present invention are authorized by the user. As shown in fig. 2, the target account attribute may be an account accounting event ID, an account transmission amount, an account balance, an account detail ID, and the like in the attribute set of the general ledger entity 1.
Referring to fig. 2, the obtaining the target ledger entity including the target account attribute is a ledger entity 1, where the obtaining the target ledger entity including the target account attribute includes:
and retrieving a target general ledger entity containing the target account attribute according to the graph calculation engine. The graph calculation engine can provide a flexible entity and relationship modeling method and rapidly generate the association graph for large-scale heterogeneous data. And rich graph algorithms are embedded, excellent visual display and interaction capability are realized, and deep penetration and mining analysis of potential relations among entities in a complex network are realized.
In the step S2, the device determines a target transaction entity and a target accounting entity associated with the target general ledger entity based on the ledger data map model; referring to fig. 2, the target accounting entity associated with the general ledger entity 1 is determined to be the accounting entity 1 through the association relationship B, and the target transaction entity associated with the accounting entity 1 is determined to be the transaction entity 1 and the transaction entity 2 through the association relationship a.
The account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity. The components of the triplet map model are shown with reference to fig. 2.
The determining, based on the ledger data profile model, a target transaction entity and a target accounting entity associated with the target ledger entity, comprising:
searching to obtain a target accounting entity associated with the target general ledger entity according to a preset graph searching algorithm;
and searching to obtain a target transaction entity associated with the target accounting entity according to the preset graph searching algorithm. The preset map search algorithm may further include a breadth-first traversal algorithm, a depth-first traversal algorithm, and the like.
Creating the ledger data map model, comprising:
respectively constructing a transaction detail solid model, an accounting detail solid model and a general account detail and account solid model according to the source data type; the source data types can specifically comprise foreground system transaction details, transaction reference data, transaction market data, background system accounting details, accounting rule data, and key correlation source data generated by business systems such as general ledger system details, subject account balances and the like.
And aggregating current day foreground system data of the foreground system to form a transaction detail solid model, an accounting detail solid model, a general ledger detail and an account solid model. The process of constructing the aggregation model instance is specifically realized by writing a first data processing rule script (Hive SQL script is commonly adopted based on a data analysis scene), and after the flow calculation is finished, the source data detail enters a lake, the rule script is called in near real time to complete the construction of the latest instance of the aggregation data entity model.
Constructing a first association relationship between the transaction detail solid model and the accounting detail solid model, and constructing a second association relationship between the accounting detail solid model, the general ledger detail and the account solid model; referring to fig. 2, an association a between a transaction entity and an accounting entity, an association B between an accounting entity and a general account statement, and an account entity are constructed.
And sequentially combining the transaction detail solid model, the first association relation, the accounting detail solid model, the second association relation, the general ledger detail and the account solid model to obtain the ledger-related data map model. The method can be expressed in the form of (entity, association relation A or B and entity) triples, and an entity relation graph model is integrally formed.
The triplet Graph spectrum data selection Graph database is used for data storage (a Janus Graph open source Graph database can be adopted and a Graph X open source Graph calculation engine can be combined), so that subsequent searching and application are facilitated. After the definition of the map relation triplet static model is finished based on the map database and the map calculation engine, the construction process of the map model example is finished, the creation of the map triplet example is finished based on a second data processing rule script (Hive SQL script) and the quasi real-time performance is guaranteed, and the map is written into the map database for storage through the map calculation engine.
Before the step of respectively constructing the transaction detail entity model, the accounting detail entity model, the general account detail and the account entity model according to the source data types, the accounting anomaly attribution analysis processing method further comprises the following steps:
acquiring source data according to a pre-written source data acquisition script; the source data acquisition script of the relevant core data of the upstream and downstream of the business system is realized through autonomous programming, and the acquisition function of key relevant source data generated by business systems such as foreground system transaction details, transaction reference data, transaction market data, background system accounting details, accounting rule data, general account system details, subject account balance and the like is realized.
Classifying the source data according to the source data type, and storing the classification result into a data lake. And (3) streaming computing processing technology is based, the acquired data flows into the data lake in near real time to serve as the source data detail of the current day service system to be stored, and the next data centralized processing is carried out.
In the step S3, the device performs an anomaly attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity, to obtain an anomaly attribution analysis result. As shown in fig. 3, the model construction and the process of tracing the accounting-related anomalies of the constructed model are illustrated. As shown in fig. 2, the target transaction attributes may be a transaction ID, a transaction amount, a transaction time, a transaction parameter 1, and a transaction parameter 2 of the attribute set in the transaction entity 1.
The target accounting attributes may be a transaction ID, an accounting rule 1, an accounting rule 2, and an accounting event ID of the attribute set in the accounting entity 1.
The specific method of abnormality attribution analysis may be selected from methods conventional in the art, and will not be described in detail.
According to the analysis and processing method for the abnormal account attribution, provided by the invention, the automatic system processing of the abnormal account event attribution analysis such as error account, account hanging and the like during the daily final general account processing in the independent accounting unit of the financial service is finally realized through a plurality of functional modules such as independent development source data acquisition, data aggregation entity model construction, data entity correlation map model construction, graph calculation attribution tracing processing and the like. The problem of timeliness of processing the abnormal problems of the accounts generated by the cross-business system is well solved, the labor cost in the analysis processing process is reduced, and the automation level of analysis processing of the abnormal problems of the core accounts is improved.
According to the accounting anomaly attribution analysis processing method provided by the embodiment of the invention, a target general ledger entity containing target account attributes is obtained according to the target account attributes with accounting anomalies; determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model; the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity; and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result, so that the operation efficiency of the accounting abnormal attribution analysis can be improved.
Further, the obtaining the target general ledger entity including the target account attribute includes:
and retrieving a target general ledger entity containing the target account attribute according to the graph calculation engine. The description of the embodiments may be referred to above, and will not be repeated.
According to the accounting anomaly attribution analysis processing method provided by the embodiment of the invention, the target general ledger entity can be rapidly acquired by means of the graph database access computing capability provided by the graph computing engine.
Further, the determining, based on the ledger data profile model, a target transaction entity and a target accounting entity associated with the target ledger entity includes:
searching to obtain a target accounting entity associated with the target general ledger entity according to a preset graph searching algorithm; the description of the embodiments may be referred to above, and will not be repeated.
And searching to obtain a target transaction entity associated with the target accounting entity according to the preset graph searching algorithm. The description of the embodiments may be referred to above, and will not be repeated.
According to the accounting anomaly attribution analysis processing method provided by the embodiment of the invention, the target accounting entity and the target transaction entity can be quickly and accurately associated through the preset graph searching algorithm.
Further, creating the ledger data map model includes:
respectively constructing a transaction detail solid model, an accounting detail solid model and a general account detail and account solid model according to the source data type; the description of the embodiments may be referred to above, and will not be repeated.
Constructing a first association relationship between the transaction detail solid model and the accounting detail solid model, and constructing a second association relationship between the accounting detail solid model, the general ledger detail and the account solid model; the description of the embodiments may be referred to above, and will not be repeated.
And sequentially combining the transaction detail solid model, the first association relation, the accounting detail solid model, the second association relation, the general ledger detail and the account solid model to obtain the ledger-related data map model. The description of the embodiments may be referred to above, and will not be repeated.
The accounting anomaly attribution analysis processing method provided by the embodiment of the invention can realize efficient creation of the accounting data map model.
Further, the respectively constructing a transaction detail entity model, an accounting detail entity model, a general ledger detail and an account entity model according to the source data type comprises:
and constructing and obtaining the transaction detail entity model, the accounting detail entity model, the general ledger detail and the account entity model according to a pre-written first data processing rule script. The description of the embodiments may be referred to above, and will not be repeated.
According to the account anomaly attribution analysis processing method provided by the embodiment of the invention, the transaction detail entity model, the accounting detail entity model, the general account detail and the account entity model are constructed efficiently, so that the account data map model can be further created efficiently.
Further, the sequentially combining the transaction detail entity model, the first association relationship, the accounting detail entity model, the second association relationship, the general ledger detail and the account entity model to obtain the ledger data map model includes:
and sequentially combining the transaction detail entity model, the first association relation, the accounting detail entity model, the second association relation and the general ledger detail and account entity model according to a pre-written second data processing rule script to obtain the ledger-related data map model. The description of the embodiments may be referred to above, and will not be repeated.
According to the accounting anomaly attribution analysis processing method provided by the embodiment of the invention, the accounting data map model can be further efficiently created by efficiently and sequentially combining the model parts.
Further, before the step of respectively constructing the transaction detail solid model, the accounting detail solid model, the general ledger detail and the account solid model according to the source data type, the accounting anomaly attribution analysis processing method further comprises the following steps:
acquiring source data according to a pre-written source data acquisition script; the description of the embodiments may be referred to above, and will not be repeated.
Classifying the source data according to the source data type, and storing the classification result into a data lake. The description of the embodiments may be referred to above, and will not be repeated.
According to the accounting anomaly attribution analysis processing method provided by the embodiment of the invention, the data is stored in a classified mode, so that the subsequent data processing efficiency is further improved.
It should be noted that, the accounting anomaly attribution analysis processing method provided by the embodiment of the invention can be used in the financial field, and also can be used in any technical field except the financial field, and the application field of the accounting anomaly attribution analysis processing method is not limited.
Fig. 4 is a schematic structural diagram of an accounting anomaly attribution analysis processing device according to an embodiment of the present invention, as shown in fig. 4, where the accounting anomaly attribution analysis processing device according to an embodiment of the present invention includes an obtaining unit 401, a determining unit 402, and an analyzing unit 403, where:
the obtaining unit 401 is configured to obtain a target general ledger entity including a target account attribute according to the target account attribute with abnormal accounting; the determining unit 402 is configured to determine a target transaction entity and a target accounting entity associated with the target ledger entity based on the ledger data map model; the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity; the analysis unit 403 is configured to perform an abnormal attribution analysis on a target transaction attribute corresponding to the target transaction entity and a target accounting attribute corresponding to the target accounting entity, to obtain an abnormal attribution analysis result.
Specifically, the obtaining unit 401 in the device is configured to obtain, according to a target account attribute with abnormal accounting, a target general ledger entity including the target account attribute; the determining unit 402 is configured to determine a target transaction entity and a target accounting entity associated with the target ledger entity based on the ledger data map model; the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity; the analysis unit 403 is configured to perform an abnormal attribution analysis on a target transaction attribute corresponding to the target transaction entity and a target accounting attribute corresponding to the target accounting entity, to obtain an abnormal attribution analysis result.
According to the accounting anomaly attribution analysis processing device provided by the embodiment of the invention, a target general ledger entity containing target account attributes is obtained according to the target account attributes with accounting anomalies; determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model; the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity; and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result, so that the operation efficiency of the accounting abnormal attribution analysis can be improved.
Further, the obtaining unit 401 is specifically configured to:
and retrieving a target general ledger entity containing the target account attribute according to the graph calculation engine.
According to the accounting anomaly attribution analysis processing device provided by the embodiment of the invention, the target general ledger entity can be rapidly acquired by means of the graph database access computing capability provided by the graph computing engine.
Further, the determining unit 402 is specifically configured to:
searching to obtain a target accounting entity associated with the target general ledger entity according to a preset graph searching algorithm;
and searching to obtain a target transaction entity associated with the target accounting entity according to the preset graph searching algorithm.
According to the accounting anomaly attribution analysis processing device provided by the embodiment of the invention, the accounting anomaly attribution analysis processing device can be quickly and accurately related to the target accounting entity and the target transaction entity through the preset graph searching algorithm.
Further, the account anomaly attribution analysis processing apparatus is further configured to:
respectively constructing a transaction detail solid model, an accounting detail solid model and a general account detail and account solid model according to the source data type;
constructing a first association relationship between the transaction detail solid model and the accounting detail solid model, and constructing a second association relationship between the accounting detail solid model, the general ledger detail and the account solid model;
and sequentially combining the transaction detail solid model, the first association relation, the accounting detail solid model, the second association relation, the general ledger detail and the account solid model to obtain the ledger-related data map model.
The accounting anomaly attribution analysis processing device provided by the embodiment of the invention can realize efficient creation of the accounting data map model.
Further, the accounting anomaly attribution analysis and processing device is specifically configured to:
and constructing and obtaining the transaction detail entity model, the accounting detail entity model, the general ledger detail and the account entity model according to a pre-written first data processing rule script.
According to the accounting anomaly attribution analysis processing device provided by the embodiment of the invention, the transaction detail entity model, the accounting detail entity model, the general ledger detail and the account entity model are constructed efficiently, so that the account-related data map model can be further created efficiently.
Further, the accounting anomaly attribution analysis and processing device is specifically configured to:
and sequentially combining the transaction detail entity model, the first association relation, the accounting detail entity model, the second association relation and the general ledger detail and account entity model according to a pre-written second data processing rule script to obtain the ledger-related data map model.
According to the accounting anomaly attribution analysis processing device provided by the embodiment of the invention, the accounting data map model can be further efficiently created by efficiently and sequentially combining the model parts.
Further, before the step of respectively constructing a transaction detail solid model, an accounting detail solid model, a general ledger detail and an account solid model according to the source data type, the accounting anomaly attribution analysis processing device is specifically configured to:
acquiring source data according to a pre-written source data acquisition script;
classifying the source data according to the source data type, and storing the classification result into a data lake.
According to the accounting anomaly attribution analysis processing device provided by the embodiment of the invention, the data are stored in a classified manner, so that the subsequent data processing efficiency is further improved.
The embodiment of the present invention provides an apparatus for analyzing and processing account abnormality, which may be specifically used to execute the processing flow of each method embodiment, and the functions thereof are not described herein in detail, and reference may be made to the detailed description of the method embodiments.
Fig. 5 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present invention, as shown in fig. 5, where the electronic device includes: a processor (processor) 501, a memory (memory) 502, and a bus 503;
wherein, the processor 501 and the memory 502 complete communication with each other through a bus 503;
the processor 501 is configured to invoke the program instructions in the memory 502 to perform the methods provided in the above method embodiments, for example, including:
acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
The present embodiment discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, are capable of performing the methods provided by the above-described method embodiments, for example comprising:
acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
The present embodiment provides a computer-readable storage medium storing a computer program that causes the computer to execute the methods provided by the above-described method embodiments, for example, including:
acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In the description of the present specification, reference to the terms "one embodiment," "one particular embodiment," "some embodiments," "for example," "an example," "a particular example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The accounting anomaly attribution analysis and processing method is characterized by comprising the following steps:
acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
determining a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger-related data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
2. The account anomaly attribution analysis processing method according to claim 1, wherein the obtaining a target ledger entity containing the target account attribute comprises:
and retrieving a target general ledger entity containing the target account attribute according to the graph calculation engine.
3. The account anomaly attribution analysis processing method according to claim 1, wherein the determining a target transaction entity and a target accounting entity associated with the target general ledger entity based on the ledger data map model comprises:
searching to obtain a target accounting entity associated with the target general ledger entity according to a preset graph searching algorithm;
and searching to obtain a target transaction entity associated with the target accounting entity according to the preset graph searching algorithm.
4. The account anomaly attribution analysis processing method according to any one of claims 1 to 3, wherein creating the ledger data map model includes:
respectively constructing a transaction detail solid model, an accounting detail solid model and a general account detail and account solid model according to the source data type;
constructing a first association relationship between the transaction detail solid model and the accounting detail solid model, and constructing a second association relationship between the accounting detail solid model, the general ledger detail and the account solid model;
and sequentially combining the transaction detail solid model, the first association relation, the accounting detail solid model, the second association relation, the general ledger detail and the account solid model to obtain the ledger-related data map model.
5. The account anomaly attribution analysis processing method according to claim 4, wherein the constructing a transaction detail solid model, an accounting detail solid model, and a general ledger detail and account solid model according to the source data type, respectively, comprises:
and constructing and obtaining the transaction detail entity model, the accounting detail entity model, the general ledger detail and the account entity model according to a pre-written first data processing rule script.
6. The account anomaly attribution analysis processing method according to claim 4, wherein the sequentially combining the transaction detail solid model, the first association relation, the accounting detail solid model, the second association relation, and the general ledger detail and account solid model to obtain the ledger data map model comprises:
and sequentially combining the transaction detail entity model, the first association relation, the accounting detail entity model, the second association relation and the general ledger detail and account entity model according to a pre-written second data processing rule script to obtain the ledger-related data map model.
7. The account anomaly attribution analysis processing method according to claim 4, wherein before the step of constructing the transaction detail solid model, the accounting detail solid model, and the general ledger and account solid model, respectively, according to the source data type, the account anomaly attribution analysis processing method further comprises:
acquiring source data according to a pre-written source data acquisition script;
classifying the source data according to the source data type, and storing the classification result into a data lake.
8. An account abnormality attribution analysis processing apparatus, comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a target general ledger entity containing target account attributes according to the target account attributes with abnormal accounts;
a determining unit configured to determine a target transaction entity and a target accounting entity associated with the target ledger entity based on a ledger data map model;
the account related data map model is a pre-established triplet map model; the triplet graph spectrum model comprises a transaction entity, an accounting entity and a general ledger entity, and a first association relation between the transaction entity and the accounting entity, and a second association relation between the accounting entity and the general ledger entity;
and the analysis unit is used for carrying out abnormal attribution analysis on the target transaction attribute corresponding to the target transaction entity and the target accounting attribute corresponding to the target accounting entity to obtain an abnormal attribution analysis result.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any one of claims 1 to 7 when the computer program is executed by the processor.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310512282.2A CN116521900A (en) | 2023-05-08 | 2023-05-08 | Account abnormity attribution analysis and processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310512282.2A CN116521900A (en) | 2023-05-08 | 2023-05-08 | Account abnormity attribution analysis and processing method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116521900A true CN116521900A (en) | 2023-08-01 |
Family
ID=87395667
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310512282.2A Pending CN116521900A (en) | 2023-05-08 | 2023-05-08 | Account abnormity attribution analysis and processing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116521900A (en) |
-
2023
- 2023-05-08 CN CN202310512282.2A patent/CN116521900A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107943463B (en) | Interactive mode automation big data analysis application development system | |
| Yang et al. | A system architecture for manufacturing process analysis based on big data and process mining techniques | |
| US11314808B2 (en) | Hybrid flows containing a continous flow | |
| CN112181960B (en) | Intelligent operation and maintenance framework system based on AIOps | |
| CN109831478A (en) | Rule-based and model distributed processing intelligent decision system and method in real time | |
| US11496584B2 (en) | Extraction and distribution of content packages in a digital services framework | |
| CN109254901B (en) | A kind of Monitoring Indexes method and system | |
| CN113468159A (en) | Data application full-link management and control method and system | |
| CN105405221A (en) | Method and device for automated test | |
| CN108536718A (en) | A kind of method and system for the IT application in management realized based on input and output semantization | |
| CN112286957A (en) | API application method and system of BI system based on structured query language | |
| CN113220907A (en) | Business knowledge graph construction method and device, medium and electronic equipment | |
| CN109582837A (en) | A kind of visualized data processing method based on cloud and system | |
| CN113947468B (en) | Data management method and platform | |
| CN115809302A (en) | Metadata processing method, device, equipment and storage medium | |
| CN108446318A (en) | A kind of mass data intelligent decision analysis system | |
| Misnik et al. | Methodology for Development of Industrial Analytical Systems for Data Collection and Processing | |
| Omori et al. | Comparing concept drift detection with process mining tools | |
| CN112434831A (en) | Troubleshooting method and device, storage medium and computer equipment | |
| CN116521900A (en) | Account abnormity attribution analysis and processing method and device | |
| CN116431668A (en) | Metadata acquisition-based data blood-edge analysis method and device and electronic equipment | |
| Omori et al. | Comparing concept drift detection with process mining software | |
| CN109033196A (en) | A kind of distributed data scheduling system and method | |
| CN105405220A (en) | Method and device for automated test | |
| CN114860851A (en) | Data processing method, device, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |