CN112435033A - System and method for realizing financial anti-fraud rule engine - Google Patents
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Abstract
The invention discloses a system and a method for realizing a financial anti-fraud rule engine, which comprises a basic platform layer, a rule configuration platform and a financial anti-fraud rule engine, wherein the basic platform layer is used for model training and data analysis, and the rule configuration platform at a bank end is constructed based on big data and an artificial intelligence algorithm at the bottom layer; the model data layer is used for providing relevant models and data; the basic engine layer is used for calculating various basic characteristics of the model data layer; and the decision layer is used for judging according to the input model data and the result of the basic engine layer. The investment cost for the repeated construction of the existing information systems of all levels and departments in the national anti-electricity fraud management and control field is effectively reduced; the personal property safety of people can be guarded, and the dominable income flow to entity economy is indirectly guaranteed; the capacity of preventing and treating fraud molecules in China for washing money and sorting dirt by using financial channels is remarkably improved.
Description
Technical Field
The invention relates to the technical field of financial services, in particular to a system and a method for realizing a financial anti-fraud rule engine.
Background
With the continuous deepening of anti-telecommunication network fraud works, the prevention and striking work is heavily directed to financial institutions. In the financial field, financial institutions pay more attention to credit fraud prevention in the anti-fraud link, but for the treatment of telecommunication network fraud, a set of mature and standardized support system from related data sources to corresponding model rules has not been established yet.
Obviously, no matter which form the fraud is carried out, the money and money which are cheated by the people are circulated in the financial channel and also reflected on the bank account. Therefore, the management of the bank account is equal to the management of the fraudulent fund flow, the management of the fraudulent fund flow is equal to the management of the fraudulent fund flow, the money cheated by the cheater cannot be transferred out, the fraudulent fund flow cannot be put into the pocket of the cheater, and the fraudulent fund flow is equal to the fraud of seven inches, so that the fraudulent case can be treated with half the effort.
At present, telecommunication network fraud cases are numerous in terms of fraud means, continuously extend in terms of fraud scenes and still have high fraud numbers by virtue of popularization of mobile internet, and financial institutions are obligated to establish a financial anti-power-off fraud rule engine as initiators and monitors of fund settlement.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
Aiming at the technical problems in the related art, the invention provides a system and a method for realizing a financial anti-fraud rule engine, which can analyze and judge telecommunication network fraud cases, summarize latest fraud behavior characteristics, integrate and clean anti-electric fraud industry data and establish an authoritative telecommunication fraud blacklist; providing efficient and stable decision service and providing a simple and easy-to-use rule decision configuration platform; the above-mentioned deficiencies of the prior art can be overcome.
In order to achieve the technical purpose, the technical scheme of the invention is realized as follows: a system for realizing a financial anti-fraud rule engine is characterized by comprising a rule configuration platform, a rule decision engine and a cloud architecture platform; the rule configuration platform comprises a login module, a scene module, a rule module and a flow module; the rule decision engine comprises a rule decision service module and a decision overloading module;
the cloud architecture comprises a basic platform layer, a data platform and a cloud service layer, wherein the basic platform layer is used for model training and data analysis, and the data platform of the bank end is constructed based on big data and an artificial intelligence algorithm of the bottom layer;
the system comprises a model data layer, a data processing layer and a data processing layer, wherein the model data layer is used for providing relevant models and data, and the relevant models comprise a transaction identity verification model, a transaction behavior characteristic model, an account issuer identity verification model, an account opening behavior characteristic model, an early warning protection model, a frequency model and a resource discrete model; the relevant data comprises a power failure system blacklist library, a public security blacklist library and a border control system attack and defense penetration database;
a base engine layer for computing various base features of the model data layer;
and the decision layer is used for carrying out decision according to the input model data and the result of the basic engine layer, and comprises a rule decision engine and a loading strategy set.
Further, the login module is used for encrypting a password input by a user according to user data and verifying the password with the user password stored in the rule configuration platform.
Further, the scene module is configured to find scene data associated with the user ID in the model data layer according to the user name, and add or delete a scene list, where the scene list includes: user number, name, creator, and update time.
Further, the rule module is used for storing variables and rule logics selected by the user, and adding or modifying the rule logics in the selected rule set.
Further, the flow module is used for converting the user input data into a BPMN file and persisting the BPMN file into a database of the base platform layer according to a flow chart drawn by a user and information contained in the flow chart.
Further, the rule decision engine is used for executing configured decision logic according to user input parameters, and is provided with an API (application programming interface) for receiving decision results.
Furthermore, the loading strategy set synchronously updates the decision logic of the online service according to the rule decision definition of the business personnel online on the configuration platform.
According to another aspect of the present invention, there is provided a method of implementing a financial anti-fraud rules engine, comprising the steps of:
s1, constructing an anti-fraud information system according to data collection, information analysis and risk quantification, and knowing the service risk condition of an attacker from the perspective;
s2, monitoring a communication channel, a transaction platform, core resources, an attack flow and an attack tool of the black and gray product, and collecting black and gray product information data, wherein before collecting the black and gray product information data, the latest trend of the black and gray product needs to be known, the black and gray product tool is reversely shared, and a service logic leak utilized by the black and gray product tool is found;
s3, cleaning, analyzing, counting and mining the collected black and gray product intelligence data, and converting the data into intelligence information;
and S4, judging by adopting a rule engine according to the input and the result of the basic engine, and identifying by an expert rule method, wherein the rule configuration platform is configured at least through a command line tool to express the use condition of the existing rule.
Further, in the step S4, the rule engine employs a real-time decision engine for making different policies for different organizations or scenarios.
Further, in the step S4, the real-time decision engine employs an efficient RETE parallel inference algorithm for ensuring fast execution of expert configuration or automatic generation rules.
The invention has the beneficial effects that: the damage to people and society caused by cases can be directly reduced or avoided, the wealth of people is protected, and the useless consumption and loss are reduced; the investment cost for the repeated construction of the existing information systems of all levels and departments in the national anti-electricity fraud management and control field is effectively reduced; the personal property safety of people can be guarded, and the dominable income flow to entity economy is indirectly guaranteed; the ability of preventing and treating fraud molecules in China to wash money and sort dirty by using financial channels is remarkably improved, so that related cases and damage caused by the cases are prevented and reduced to the greatest extent; the operation stability of the financial market is maintained, and the comprehensive, coordinated and sustainable development of the economic society is promoted.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a block diagram of a system implementing a financial anti-fraud rules engine according to an embodiment of the present invention;
FIG. 2 is a block flow diagram of a method of implementing a financial anti-fraud rules engine, according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
1-2, the system for implementing a financial anti-fraud rule engine according to an embodiment of the present invention includes a rule configuration platform, a rule decision engine and a cloud architecture platform; the rule configuration platform comprises a login module, a scene module, a rule module and a flow module; the rule decision engine comprises a rule decision service module and a decision overloading module;
the cloud architecture comprises a basic platform layer, a data platform and a cloud service layer, wherein the basic platform layer is used for model training and data analysis, and the data platform of the bank end is constructed based on big data and an artificial intelligence algorithm of the bottom layer;
the system comprises a model data layer, a data processing layer and a data processing layer, wherein the model data layer is used for providing relevant models and data, and the relevant models comprise a transaction identity verification model, a transaction behavior characteristic model, an account issuer identity verification model, an account opening behavior characteristic model, an early warning protection model, a frequency model and a resource discrete model; the relevant data comprises a power failure system blacklist library, a public security blacklist library and a border control system attack and defense penetration database;
a base engine layer for computing various base features of the model data layer;
and the decision layer is used for carrying out decision according to the input model data and the result of the basic engine layer, and comprises a rule decision engine and a loading strategy set.
In a specific embodiment of the present invention, the login module is configured to encrypt a password input by a user according to user data, and verify the password with a user password stored in the rule configuration platform.
In a specific embodiment of the present invention, the scene module is configured to find scene data associated with the user ID in the model data layer according to the user name, and add or delete a scene list, where the scene list includes: user number, name, creator, and update time.
In a specific embodiment of the present invention, the rule module is configured to store variables and rule logic selected by a user, and add or modify the rule logic in the selected rule set.
In an embodiment of the present invention, the flow module is configured to convert the user input data into a BPMN file and persist the BPMN file in a database of the base platform layer according to a flow chart drawn by a user and information included in the flow chart.
In an embodiment of the present invention, the rule decision engine is configured to execute the configured decision logic according to the user input parameter, and is provided with an API interface for receiving the decision result.
In a specific embodiment of the present invention, the loading policy set synchronously updates the decision logic of online service according to the rule decision definition of online service personnel on the configuration platform.
According to another aspect of the present invention, there is provided a method of implementing a financial anti-fraud rules engine, comprising the steps of:
s1, constructing an anti-fraud information system according to data collection, information analysis and risk quantification, and knowing the service risk condition of an attacker from the perspective;
s2, monitoring a communication channel, a transaction platform, core resources, an attack flow and an attack tool of the black and gray product, and collecting black and gray product information data, wherein before collecting the black and gray product information data, the latest trend of the black and gray product needs to be known, the black and gray product tool is reversely shared, and a service logic leak utilized by the black and gray product tool is found;
s3, cleaning, analyzing, counting and mining the collected black and gray product intelligence data, and converting the data into intelligence information;
and S4, judging by adopting a rule engine according to the input and the result of the basic engine, and identifying by an expert rule method, wherein the rule configuration platform is configured at least through a command line tool to express the use condition of the existing rule.
In an embodiment of the present invention, in the step S4, the rule engine employs a real-time decision engine for making different policies for different organizations or scenarios.
In a specific embodiment of the present invention, in the step S4, the real-time decision engine employs an efficient RETE parallel inference algorithm for ensuring fast execution of expert configuration or automatic generation rules.
By utilizing the rule engine and the model platform, financial security risks are effectively identified, prevented and intercepted in advance and in the process, the source control of telecommunication network fraud and illegal crimes is further strengthened, and bank accounts identified for crime making are limited and intercepted, so that fraud cases are reduced from the source, the control target that fraud funds are not transferred and provided by the center of a party is effectively implemented, and the fund and property safety of financial consumers is practically guaranteed.
In order to facilitate understanding of the above-described technical aspects of the present invention, the above-described technical aspects of the present invention will be described in detail below in terms of specific usage.
The financial anti-fraud rule engine cloud architecture comprises a basic platform layer, a model data layer, a basic engine layer and a decision layer, wherein the data platform layer mainly comprises a big data analysis and modeling platform, specifically comprises Hadoop, Spark and Tesnsorflow, and is used for model training and data analysis; the basic engine layer comprises a behavior model service, a list service and a real-time portrait service, and calculates various basic characteristics.
Firstly, an anti-fraud information system is established
The method is characterized in that the service risk condition of the attacker is known from the dimensions of data collection, information analysis and risk quantification;
monitoring multiple dimensions such as a communication channel, a transaction platform, core resources, attack flow, an attack tool and the like of the black and gray product, and collecting information data of the black and gray product;
and cleaning, analyzing, counting and mining the collected black and gray product data to convert the collected black and gray product data into valuable information, knowing the latest trend of the black and gray products, reversely sharing the black and gray product tools and finding out the utilized business logic loopholes.
Employing a real-time decision engine to address the above-mentioned problems
Judging according to the input and the result of the basic engine, making a judgment result, identifying by an expert rule method, and expressing the use condition of the existing rule in the aspect of functional design;
the real-time decision engine can make different strategies aiming at different organizations and different scenes;
in rule execution, the real-time decision engine employs an efficient RETE parallel inference algorithm that ensures rapid execution of expert configured or auto-generated rules, in which system thousands of rules can complete execution within 10 milliseconds.
The financial anti-fraud rule engine consists of two sub-platforms, namely a rule configuration platform and a rule decision engine.
The rule configuration platform is provided with a plurality of modules, including the following modules:
the login module is used for inputting a user name and a password by a user to log in the rule configuration management system; the user needs to input a user name and a password, click to log in, the system background is compared with the password in the database, and if the user name and the password are consistent, the login is successful;
the scene module comprises a scene display for displaying a scene list; scene editing is used to edit a detail page of a specified scene.
A rule module including a rule editor for editing rules in a rule set; rule combinations are used to select the hit logic for the rule set as a whole, namely: combinational logic of a plurality of rules; rule testing is used to test the configured rule set.
The rule decision engine is provided with two modules, which are as follows,
the rule decision service module executes the configured decision logic according to the user input parameters and finally returns an API (application programming interface) of a decision result;
and the decision overloading module is used for synchronously updating the decision logic of the online service according to the rule decision definition of the business personnel online on the configuration platform.
The rule decision engine system is an online service system which supports real-time rule decision and index output and has the characteristics of high concurrency and low time delay.
Through a big data technology and an artificial intelligence technology, a financial anti-fraud rule engine with data authority, effective model, flexible configuration and response to real time is built.
When the system is used specifically, according to the system and the method for realizing the financial anti-fraud rule engine, firstly, the system is logged in; finding scene data associated with the user ID in the database according to the user name, and creating or editing a scene; searching the rule data and the process data associated with the selected scene in a database, and uploading the rule data and the process data to a rule engine service system; the user performs the function of online regular flow; the user is selecting the rule comparison logic and adding the value compared to the variable or another variable; the user can select the hit logic of the rule set on the rule editing interface, and the name of the rule is used as a parameter; the input parameters are system default values, and a data structure of a test result is displayed; a user needs to select a specific rule set, add a logic expression of a flow trend and mark a final decision termination node; a user needs to select variables for testing, assign values and execute the testing of the flow; checking a rule decision version deployed online, wherein the rule decision version comprises information such as scene names, process versions, operators, operation time and the like; the selectable variable information in the rule configuration is checked, and the variable information comprises information such as variable names, variable interpretations and variable types; receiving the API interface configured by the rules and the flow of a specific scene, and deploying the rule decision service of the scene in real time; calculating variables according to original parameters provided by a user, and deriving variable values used by the rules; loading the configuration information of the rule set, executing each rule in the rule set, and finally outputting the result of the rule set; and loading configuration information of the flow, executing the task of the selected rule set according to the flow defined in the BPMN, executing a correct flow trend according to the result of the rule set, and finally outputting the result of the whole decision flow.
In conclusion, by means of the technical scheme, the damage to people and society caused by cases can be directly reduced or avoided, the wealth of people is protected, and the useless consumption and loss are reduced; the investment cost for the repeated construction of the existing information systems of all levels and departments in the national anti-electricity fraud management and control field is effectively reduced; the personal property safety of people can be guarded, and the dominable income flow to entity economy is indirectly guaranteed; the ability of preventing and treating fraud molecules in China to wash money and sort dirty by using financial channels is remarkably improved, so that related cases and damage caused by the cases are prevented and reduced to the greatest extent; the operation stability of the financial market is maintained, and the comprehensive, coordinated and sustainable development of the economic society is promoted.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A system for realizing a financial anti-fraud rule engine is characterized by comprising a rule configuration platform, a rule decision engine and a cloud architecture platform; the rule configuration platform comprises a login module, a scene module, a rule module and a flow module; the rule decision engine comprises a rule decision service module and a decision overloading module;
the cloud architecture comprises a basic platform layer, a data platform and a cloud service layer, wherein the basic platform layer is used for model training and data analysis, and the data platform of the bank end is constructed based on big data and an artificial intelligence algorithm of the bottom layer;
the system comprises a model data layer, a data processing layer and a data processing layer, wherein the model data layer is used for providing relevant models and data, and the relevant models comprise a transaction identity verification model, a transaction behavior characteristic model, an account issuer identity verification model, an account opening behavior characteristic model, an early warning protection model, a frequency model and a resource discrete model; the relevant data comprises a power failure system blacklist library, a public security blacklist library and a border control system attack and defense penetration database;
a base engine layer for computing various base features of the model data layer;
and the decision layer is used for carrying out decision according to the input model data and the result of the basic engine layer, and comprises a rule decision engine and a loading strategy set.
2. The system according to claim 1, wherein said login module is configured to encrypt a password inputted by a user according to user data, and verify the password with a user password stored in said rule configuration platform.
3. The system according to claim 1, wherein said scenario module is configured to find scenario data associated with a user ID in said model data layer according to a user name, add or delete a scenario list, wherein a scenario list comprises: user number, name, creator, and update time.
4. The system of claim 1, wherein said rules module is configured to store user-selected variables and rule logic, add or modify rule logic in selected rule sets.
5. The system according to claim 1, wherein said flow module is adapted to transform user input data into BPMN file and persist it into the database of the underlying platform layer according to the user-drawn flow chart and the information contained in the chart.
6. The system according to claim 1, wherein said rules decision engine is configured to execute configured decision logic according to user input parameters, and is provided with an API interface for receiving decision results.
7. The system for implementing a financial anti-fraud rules engine of claim 1, wherein said set of loading policies synchronously update decision logic of online services according to rule decision definitions of business personnel online on a configuration platform.
8. A method of implementing a financial anti-fraud rules engine, comprising the steps of:
s1, constructing an anti-fraud information system according to data collection, information analysis and risk quantification, and knowing the service risk condition of an attacker from the perspective;
s2, monitoring a communication channel, a transaction platform, core resources, an attack flow and an attack tool of the black and gray product, and collecting black and gray product information data, wherein before collecting the black and gray product information data, the latest trend of the black and gray product needs to be known, the black and gray product tool is reversely shared, and a service logic leak utilized by the black and gray product tool is found;
s3, cleaning, analyzing, counting and mining the collected black and gray product intelligence data, and converting the data into intelligence information;
and S4, judging by adopting a rule engine according to the input and the result of the basic engine, and identifying by an expert rule method, wherein the rule configuration platform is configured at least through a command line tool to express the use condition of the existing rule.
9. The method of claim 8, wherein in said step S4, the rules engine employs a real-time decision engine for making different policies for different organizations or scenes.
10. The method of claim 9, wherein in said step S4, the real-time decision engine employs an efficient RETE parallel reasoning algorithm for fast execution of the guaranteed expert configuration or automatic generation rules.
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