Conformity determination of cross-regional affairs

A method, a device and a computer program for conformity determination of cross-regional affairs. The method comprises obtaining characteristics from a description of an affair at least crossing a local region and a non-local region. The method further comprises generating a multi-level constraint based on the characteristics from a knowledge base, and the knowledge base includes regulations for cross-regional affairs, and the multi-level constraint includes a local constraint associated with the local region and a non-local constraint associated with the local region and the non-local region. Moreover, the method also comprises determining conformity of the affair to the multi-level constraint. The method can determine the conformity of the cross-regional affairs automatically, thereby reducing the consumption of human resources and the inconformity risk in the cross-regional affairs.

BACKGROUND

Cross-regional affairs generally relate to many different regulations on the same topic or theme. For example, different regions may have different regulations for the same affair. In the transaction compliance audit, the staffs need to study all the related regulations from different regions in order to check the compliance of the transaction. As a result, it requires much more efforts to identify the difference and compliance risk against these regulations. For example, some organizations may put tens of thousands of employees to work on compliance checking because the cost is very expensive if an affair is in incompliance with the regulations.

Generally, the term in regulations is abstract constraint description, for example, a domestic enterprise, while the entity in the affairs or transactions is usually individual or detail information, for example, a specific company name. Thus, it is a big challenge to figure out whether the detail information in the affairs or transactions conforms to the current regulations. However, traditional methods merely provide some text comparisons among regulations, for example, there is provided a regulatory compliance assistance framework which may link to any reference regulation provisions and display terms and definitions. Therefore, the traditional methods could not figure out semantic constraint on the cross-regional affair among the regulations.

SUMMARY

Example embodiments of the present disclosure provide a method, a device, and a computer program product for conformity determination of cross-regional affairs.

In an aspect, a computer-implemented method is provided. The method comprises obtaining characteristics from a description of an affair at least crossing a local region and a non-local region. The method further comprises generating a multi-level constraint based on the characteristics from a knowledge base, wherein the knowledge base includes regulations for cross-regional affairs, and the multi-level constraint includes a local constraint associated with the local region and a non-local constraint associated with the local region and the non-local region. Moreover, the method also comprises determining conformity of the affair to the multi-level constraint.

In another aspect, a device is provided. The device includes a processing unit and a memory coupled to the processing unit and storing instructions thereon. The instructions can be executed by the processing unit to perform acts including: obtaining characteristics from a description of an affair at least crossing a local region and a non-local region; generating a multi-level constraint based on the characteristics from a knowledge base; and determining conformity of the affair to the multi-level constraint.

In yet another aspect, a computer program product is provided. The computer program product is tangibly stored on a non-transient machine-readable medium and comprises machine-executable instructions. When executed on a device, the instructions cause the device to obtain characteristics from a description of an affair at least crossing a local region and a non-local region; to generate a multi-level constraint based on the characteristics from a knowledge base; and to determine conformity of the affair to the multi-level constraint.

According to embodiments of the present disclosure, the conformity of the affair can be automatically determined without any manual operation, thereby reducing the consumption of human resources and the inconformity risk in the cross-regional affairs. Moreover, the multi-level constraint can be accurately generated based on the type of the affair and the location at which the affair is to be executed. Further, the embodiments of the present disclosure can provide the result of conformity determination to the users, and the embodiments of the present disclosure can provide some related regulations with which the affair does not comply in the case that the affair involves an aspect of inconformity.

DETAILED DESCRIPTION

As used herein, the term “includes” and its variants are to be read as open terms that mean “includes, but is not limited to”. The term “based on” is to be read as “based at least in part on”. The term “one embodiment” and “an embodiment” are to be read as “at least one embodiment.” The term “another embodiment” is to be read as “at least one other embodiment”.

In the embodiments of the present disclosure, the term “affair” is to be read as a transaction deal between two or more entities, it is also referred to as “transaction”, “contract” and so forth. As used herein, the term “region” refers to a country, a state, a province, or an area within a country. The term “conformity” means that the affair conforms to the regulations, it is also referred to as “compliance”, “consistent” and so forth. The term “regulations” may include laws, regulations and policies of both local region and non-local regions. Other definitions, explicit and implicit, may be included below.

Reference is first made toFIG. 1, in which an exemplary computer system/server12which is applicable to implement the embodiments of the present disclosure is shown. Computer system/server12is only illustrative and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the disclosure described herein.

In computer system/server12, I/O interfaces22may support one or more of various different input devices that can be used to provide input to computer system/server12. For example, the input device(s) may include a user device such keyboard, keypad, touch pad, trackball, and the like. The input device(s) may implement one or more natural user interface techniques, such as speech recognition, touch and stylus recognition, recognition of gestures in contact with the input device(s) and adjacent to the input device(s), recognition of air gestures, head and eye tracking, voice and speech recognition, sensing user brain activity, and machine intelligence.

Now some example embodiments of the present disclosure will be described. As mentioned above, conventional ways for determining conformity of the cross-regional affairs are performed manually. This process will consume considerable human resources and might miss some fatal regulations. In order to reduce non-compliance risk in the cross-regional affairs, deep regulation understanding is very important way of compliance determination. According to embodiments of the present disclosure, conformity of the cross-regional affairs is determined automatically, thereby reducing the consumption of human resources and the inconformity risk in the cross-regional affairs.

For example, an entity M and an entity N make a cross-regional transaction at region A. The cross-regional transaction should comply with the regulations for cross-regional affairs, which comprises a local constraint associated with the region A and a non-local constraint associated with the local and non-local regions. The transaction may be regarded as the term “affair” in the following embodiments, that is, a transaction may be an example of an affair.

FIG. 2is a flowchart of a method200for determining conformity of cross-regional affairs in accordance with embodiments of the present disclosure. In step202, characteristics are obtained from a description of an affair, and the affair at least crosses a local region and a non-local region. For example, the affair may be a transaction and contract between two or more entities, and each entity may be a person or an organization. That is, a plurality of characteristics may be extracted from the transaction or the contract by using characteristic recognition model.

In some embodiments, the characteristics may include at least one of affair information about the affair and entity information about an executive entity for the affair. Examples of the affair information include, but are not limited to, location, time, number, industry, amount of money and ratio of return of the affair, and the entity information may include, but are not limited to, natural attribute (such as gender, nationality), social role (such as state-owned enterprise, foreign enterprise), social attribute (such as qualification, certificate) and social relation (such as subsidiary, relative) of the entity.

Next, the method200proceeds to step204, where a multi-level constraint is generated based on the characteristics from a knowledge base, wherein the knowledge base includes regulations for cross-regional affairs, and the multi-level constraint includes a local constraint associated with the local region and a non-local constraint associated with the local region and the non-local region. For example, the non-local constraint may be a global consistent constraint, while the local constraint may be a local specific constraint.

In some embodiments, the knowledge base may store existing laws, regulations and policies of both local region and non-local regions. In some embodiments, an example of the non-local constraint may be that the investor should be a manufacturing enterprise, and an example of the local constraint may be that the investor should not be a foreign enterprise. The constraint may be represented as conformity and inconformity, and thus the example of the non-local constraint may be represented as: investor {conformity: manufacturing enterprise}, and the example of the local constraint may be represented as: investor {inconformity: foreign enterprise}.

In step206, conformity of the affair to the multi-level constraint is determined. Still consider the example embodiments where the non-local constraint comprises that the investor should be a manufacturing enterprise and the local constraint comprises that the investor should not be a foreign enterprise. In such embodiments, if a foreign manufacturing enterprise wants to make an investment deal with a domestic enterprise in this local region, then this investment deal is in conformity with the non-local constraint, but it is in inconformity with the local constraint because the investor is a foreign enterprise. As a result, it is determined that this investment deal is in inconformity with the regulations. Accordingly, the embodiments of method200can reduce the consumption of human resources and the inconformity risk in the cross-regional affairs by automatically determining the conformity of the affair.

It is to be understood that although step202is shown prior to step204, this is merely for the purpose of illustration without suggesting any limitation as to the scope of the present disclosure. In some embodiments, these two steps can be carried out in parallel. That is, it is possible to use a single instruction to obtain the characteristics and generate the multi-level constraint.

FIG. 3Ais a flowchart of a method300for generating the multi-level constraint in accordance with embodiments of the present disclosure. It will be understood that the method300may be regarded as a specific implementation of the step204in the method200with respect toFIG. 2. In step302, a type of the affair is determined. In some embodiments, the type may represent a kind of the transaction or contract, and the type may be, but is not limited to, investment, lease, agency, permission and so forth.

In step304, regulations corresponding to the type of the affair are selected from the regulations stored in the knowledge base. For example, if the affair is a type of investment deal, the investment related regulations are selected from the knowledge base. In step306, the multi-level constraint for the characteristics is generated based on the selected regulations. Still considering the example that the affair is a type of investment deal, a multi-level constraint suitable for the investment may be generated.

FIG. 3Bis a flowchart of a method350for generating the local constraint in accordance with embodiments of the present disclosure. It will be understood that the method350may be regarded as a specific implementation of the step204in the method200with respect toFIG. 2. In step352, a location at which the affair is to be executed is determined from the affair information. Since different regions may have different regulations on the same topic or theme, for example, the region A may ban exports to the region B, while the region C may allow exports to the region B, the location of the affair needs to be determined. In some embodiments, the location may be a state or a city. In step354, the local region is determined based on the location of the affair. For example, if the location of the affair is a city in region A, it can be determined that the local region is the region A. Next, in step356, the local regulations associated with the determined local region are determined from the regulations stored in the knowledge base. For example, the local regulations for region A are generated from the knowledge base. In step358, the local constraint for the characteristics is generated based on the determined local regulations. Considering the embodiment that the local region is the region A, a local constraint suitable for the region A is generated, which means that the affair should conform to the regulations of the region A, for example, goods cannot be exported to the region B.

In some embodiments, the conformity of the affair to the multi-level constraint may include first conformity and second conformity. The first conformity is determined based on the affair information, while the second conformity is determined based on the entity information. That is, in the case that the characteristics include affair information about the affair and entity information about an executive entity for the affair, both the affair information and entity information should be checked against the multi-level constraint. In some embodiments, the affair will be determined to be allowable only if both the first conformity and the second conformity are satisfied. Thus, the multi-level constraint can be accurately generated based on the type of the affair by means of the method300, and the local constraint can be accurately generated based on the location at which the affair is to be executed by means of the method350. Moreover, by use of two types of conformities, the conformity of the affair can be enhanced.

FIG. 4is a flowchart of a method400for providing an indication indicating the conformity of cross-regional affairs in accordance with embodiments of the present disclosure. The method400starts after generating a multi-level constraint based on the characteristics from a knowledge base in step204in method200.

In step402, items in the multi-level constraint corresponding to the characteristics are determined. For example, a template that indicates a plurality of definitions of characteristics to be obtained may be generated firstly, and the extraction patterns for the template are created manually or automatically. Then, a process of pattern matching is performed by means of the extraction patterns between the template and the description of the affair in order to obtain the characteristics associated respectively with the definitions in the template. Accordingly, each of the obtained characteristics may be tagged with a definition of the characteristic after the characteristics are obtained from the description of the affair. Moreover, each item in the multi-level constraint together with a definition thereof also may be obtained by means of the similar pattern matching process. Then, cross-regional constraint linkage may be performed for each characteristic by matching the definitions of the characteristics and the items. In this way, each of the characteristics may be aligned to an item in the multi-level constraint corresponding to the definition of the characteristic.

In some embodiments, for example, the multi-level constraint may be represented as a tree as illustrated in the belowFIG. 5A or 5B, the tree includes a plurality of nodes, and each node may indicate an item related to the local constraint or the non-local constraint. In some embodiments, the tree is searched or traversed to look for nodes indicating the items corresponding to the characteristics. For example, each of the characteristics is aligned to a node in the tree based on semantic feature vector of its definition and background in the regulations, and the multi-level constrain association is performed for the affair.

In step406, it is determined whether the characteristics conform to the multi-level constraint on the items. For example, the constraint conformity analysis is performed with deep semantic association to determine whether the affair is in conformity with the multi-level constraint.

If it is determined that an aspect of the affair is in inconformity with the multi-level constraint, the method proceeds to step408, where a first indication of the aspect of the affair is provided, which indicates that the aspect of the affair is inconformity with the multi-level constraint. Then, in step410, a second indication indicating regulation(s) related to the aspect is provided. For example, it is assumed that the local constraint is represented as follows: investor {inconformity: foreign enterprise}. If a foreign manufacturing enterprise wants to make an investment deal with a domestic enterprise in this local region, this investment deal is in inconformity with the local constraint because the investor is a foreign enterprise. Accordingly, a first indication may be provided to indicate that the executive entity for the investment deal is in inconformity with the local constraint. Additionally, a second indication may be provided to indicate a regulation that the executive entity for the investment deal should not be a foreign enterprise. In this way, if the affair is incompliant, the entity of the affair may be aware of the reasons why the affair is incompliant, and then the entity can modify or withdraw the description of the affair (such as, transaction or contract) in order to comply with the regulations.

On the other hand, if it is determined in step406that all aspects of the affair are in conformity with the multi-level constraint, the method400proceeds to step412. In this step, a third indication is provided, which indicates that the affair is in conformity with the multi-level constraint. That is, the description of the affair, such as, transaction or contract, complies with the regulations. According to the embodiments of method400, the result of conformity determination can be provided to the users, and some related regulation(s) with which the affair does not comply can be also provided in the case that the affair involves an aspect of inconformity. Thus, the efficiency of conformity determination of the affair can be greatly increased.

FIG. 5Ashows an affair level tree for the multi-level constraint in accordance with embodiments of the present disclosure. As show inFIG. 5A, the affair level tree includes a multi-level constraint on the affair information, that is, a non-local constraint and a local constraint. The non-local constraint is associated with both the local region and the non-local region, while the local constraint is only associated with the local region. As shown inFIG. 5A, the root node in a first level has six child nodes in a second level, that is, a time node, a location node, a number node, a money node, an industry node and a ratio node, which collectively form the non-local constraint on the affair information. Some of these nodes in the second level may have nodes in the third level, and the nodes in the third level form the local constraint on the affair information. For example, as illustrated in the local constraint ofFIG. 5A, there are two aspects for the region A in local constraint, such as the local constraint for location and the local constraint for industry. For example, as to the local constraint for industry, in the region A, the investment deals in the industry of aviation and communication are banned, while in the region D, the investment deals in the industry of banking and securities are banned.

FIG. 5Bshows an entity level tree for the multi-level constraint in accordance with embodiments of the present disclosure. As show inFIG. 5B, the entity level tree includes a multi-level constraint on the entity information, that is, a non-local constraint and a local constraint. The root node in a first level has four child nodes in a second level, that is, a natural attribute node, a social role node, a social attribute node and a social relation node, which collectively form the non-local constraint on the affair information. Some of these nodes in the second level may have nodes in the third level, and the nodes in the third level form the local constraint on the affair information. For example, in the local constraint ofFIG. 5B, in the region A, the entity in a certain type of deal should be a non-foreign enterprise, while in the region D, the entity in the same type of deal should be a WTO member.

In some embodiments, the affair information and entity information in the description of the affair is associated with the nodes in the affair level tree and the entity level tree. Then, the conformity of the affair is determined by means of determining whether the affair information and entity information conforms to the constraints in all the nodes.

Consequently, the method in the present disclosure can automatically provide the conformity of the cross-regional affairs without any manual operations, thereby reducing the consumption of human resources and the inconformity risk in the cross-regional affairs. Moreover, the multi-level constraint may be generated based on the type of the affair and the location at which the affair is to be executed. Further, the embodiments of the present disclosure may provide the result of conformity determination to the users, and the embodiments of the present disclosure may provide some related regulation(s) with which the affair does not comply in the case that the affair involves an aspect of inconformity.