TECHNICAL FIELD

[0001] The embodiments herein relate generally to data processing, and more particularly to a system and process for cannabis compliance and exchange platform.

BACKGROUND ART

[0002] In general, cannabis related businesses have a wide range of regulations they must comply with. In some cases, a cannabis related business may run afoul of a regulation by not adapting to the local rules of one jurisdiction even though their current practice may comply with the rules of another jurisdiction. In some cases, the business itself does not violate a regulation but a third party business they are working with may have business practices or individuals whose activities may explicitly violate regulations or show a propensity toward risky behavior that increases the likelihood of violating a regulation.

[0003] Accordingly, some cannabis related businesses may manually establish risk tolerances for compliance controls, whether internal or external, and for sharing cannabis data. The factors underlying a manual risk tolerance may be generated by gathering data from various sources; for example through online searches and reading articles. The business may then attempt to create their own risk levels manually. For example, an individual might have to determine the risk of dealing with a cannabis business by weighing, all materials research, manually and adjusting based upon their risk model; further, the risk model would be inaccurate if data is neither validated nor shared among participants to establish an industry standard. While the preceding manual processes can be presented to either the individual or entity through a manual process, it fails to address dynamic legal and regulatory changes.

[0004] As can be seen, there is a need for a system that automates the generation of risk tolerance data that can be readily seen by a user. In addition, there is a need for establishing a risk metric and for a system that automatically validates the data so that the user is assured of its accuracy.

DISCLOSURE OF THE INVENTION

[0005] In one aspect of the subject disclosure, a computer program product for an online host platform generating a risk tolerance value associated with cannabis related business comprises a non-transitory computer readable storage medium having computer readable program code embodied therewith. The computer readable program code is configured to: host, through a computer server, the online platform, wherein the online platform is part of a computer network and serving in the role of an exchange for cannabis related activity data; generate and host user interfaces for a plurality of user accounts, wherein the plurality of user accounts communicate with the host computer server through the computer network; receive by the host server, the cannabis related activity data, wherein the cannabis related activity data is stored in association with each cannabis related businesses involved with an individual piece of cannabis related activity data; provide, through respective user interfaces, the cannabis related activity data for one or more of the cannabis related businesses in response to a user request for the cannabis related activity data; and generate for display through the user interfaces, a risk metric generated for a selected one of the cannabis related businesses, wherein the risk metric is based on an aggregate of values assigned to each of the cannabis related activity data associated with the selected one of the cannabis related business.

BRIEF DESCRIPTION OF THE FIGURES

[0006] The detailed description of some embodiments of the invention is made below with reference to the accompanying figures, wherein like numerals represent corresponding parts of the figures.

[0007] FIG. 1 is a block diagram of a system environment in which a cannabis exchange system operates, in accordance with an embodiment.

[0008] FIG. 2 is a block diagram of a cannabis exchange system, predicative analysis, rule sharing, and reporting system, in accordance with an embodiment.

[0009] FIG. 3 is a block diagram and flowchart of data ingestion of a cannabis exchange system, in accordance with an embodiment.

[0010] FIG. 4 is a flowchart of a method of the exchange of cannabis database between entities and users of a cannabis exchange system, in accordance with an embodiment.

[0011] FIG. 5 is a block diagram with a flowchart of a method of creating risk models with risk prioritization, weight values, in accordance with an embodiment.

[0012] FIG. 6 is a flowchart of how rule sharing models are created, shared, and viewed, in accordance with an embodiment. [0013] FIG. 7 is a flowchart of how data is utilized within the cannabis exchange system to provide predicative analysis with patterns and trends based upon collected data and real-time data comparison, in accordance with an embodiment.

[0014] FIG. 8 is a flowchart of how on how data is used by the cannabis exchange system to create compliance profiles and outputs for risk modeling, in accordance with an embodiment.

[0015] FIG. 9 is a flowchart on how data is exchanged and requested through a brokered exchanged between multiple users, in accordance with an embodiment.

[0016] FIG. 10 is a flowchart on how data is either anonymized or pseudonymized, or combined, and exchanged within the system and among users, in accordance with an embodiment.

[0017] FIG. 11 is a flowchart on the exchange of data, inclusive of gated exchanges and data validation exchange, in accordance with an embodiment.

[0018] The figures depict various embodiments of the present invention for purposes of illustration only. One skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the invention described herein.

BEST MODE OF THE INVENTION

[0019] The detailed description set forth below is intended as a description of various configurations of the subject technology and is not intended to represent the only configurations in which the subject technology may be practiced. The appended drawings are incorporated herein and constitute a part of the detailed description. The detailed description includes specific details for the purpose of providing a thorough understanding of the subject technology. However, it will be apparent to those skilled in the art that the subject technology may be practiced without these specific details. Like or similar components are labeled with identical element numbers for ease of understanding.

[0020] In general, embodiments of the disclosed subject technology provide content via a cannabis exchange system and platform. More specifically the exchange, collection, view, and validation of cannabis data to provide an enhanced KYC and CDD process for cannabis-related activities to establish a risk tolerance ("risk metric"). The risk metric includes user-driven risk indicia based upon user-based inputs, as either weighted or prioritized as importance. The cannabis exchange allows users and entities to configure their indicia to determine their risk metric when interacting, whether directly or indirectly, with those involved within the cannabis industry. Indicia are limitless and customized with conditional statements to allow users and entities to establish their risk metrics. Users and entities can have multiple risk metrics and can couple those risk metrics together to establish an overall risk tolerance metric. The cannabis exchange is comprised of user-based inputs, data exchange processes and controls, risk modeling, validation tools, and machine learning to provide predicative analysis of cannabis-related activities.

[0021] A cannabis exchange system may be provided through an online system or through an Automatic Programming Interface (API) integrated with other systems, which allows for its users to connect to and communicate with other systems and system users.

[0022] Due to the legalization of cannabis, whether recreational or medical, and competing state and federal regulations, a cannabis exchange system provides an ideal forum for both entities and individuals to increase compliance towards regulations and reporting requirements; further, a cannabis exchange system allows for cannabis and non-cannabis entities and individuals to establish a risk tolerance when engaging in either current or prospective business opportunities with those involved, whether directly or indirectly, in the cannabis industry.

[0023] In some aspects, the embodiments disclosed herein present content items to cannabis exchange users which allow either an individual or entity to create a risk tolerance threshold for their organization and validate cannabis data. This allows a cannabis exchange user to establish risk metrics tailored to their needs, as well as regulatory requirements, and create conditional rules and share those rules with others through rule-sharing.

[0024] A cannabis compliance and data exchange (“cannabis exchange”) platform allows for users and entities to collect, view, validate, and exchange information, whether direct, brokered, or gated, between each other to address regulations, compliance, and reporting requirements as required by local, state, and federal laws, regulations, and ordinances. This further extends to internal business practices and controls required by an entity and/or individual who is either directly or indirectly involved in the cannabis industry. Users and entities can collect, view, and, whether separately or in its aggregate, validate data, activities, documents, and purchases (“cannabis data”); further, a cannabis exchange system allows for users and entities to share and compare cannabis data to make informed decisions and abide by regulatory, compliance, and reporting requirements for Know-Your-Customer (“KYC”), Continuing Due Diligence (“CDD”), and internal business controls. [0025] A cannabis data exchange allows for users and entities to develop profiles on businesses and individuals involved in cannabis-related activities, whether directly or indirectly, such as but not limited to business transactions, vendor transactions, vendor profiles, and customer profiles (“business operations data”). A cannabis data exchange provides users and entities with both a historical and real-time analysis to make decisions based upon the business operations data received either independently or among the cannabis data exchange participants.

[0026] A cannabis exchange allows for patterns and forecasting to establish predictive trends and a concept called rule-sharing for both cannabis data and business operations data. As will be appreciated, aspects of the rule sharing feature may be considered an unconventional element in the field of exchange platforms. The predictive trends allow the user and entities to establish a threshold to determine irregularities and patterns to calculate their own risk tolerance (“risk metric”). The risk metric may include multiple indicia (“risk indicia”) to calculate the risk metric; further, each risk indicium may be weighted and/or prioritized. In some embodiments, risk metric and risk indicia may be driven by user input; consequently, cannabis exchange participants can create different risk indicia to calculate their risk metric unless they adopt risk indicia from rule-sharing.

[0027] Rule-sharing allows users and entities to share, view, and adopt conditional logical rules for the cannabis data (“cannabis rules”). Cannabis rules can be created, shared, and tested within the cannabis exchange. Rule-sharing, coupled with predictive trends and analysis, allows users and entities to deploy enhanced KYC and CDD to address regulatory, compliance, internal business practices and controls and reporting requirements; further, cannabis rules allow for user and entities to perform ad-hoc scenarios with cannabis data, whether their own or shared data, without impacting their environment.

[0028] The validation of cannabis data incorporates the process of Determining a Metric and Predicative Analysis for Cannabis Compliance (“cannabis validation”). Validation data can occur from internal and third-party data sources connected to the cannabis compliance system. During the exchange of data within the cannabis exchange, users and entities may validate cannabis data to determine its authenticity and accuracy. The validation of cannabis data, coupled with the cannabis exchange, allows users and entities to configure cannabis data validation as a risk indicium for their risk metric. The cannabis exchange does not require the inclusion of cannabis validation to function properly.

[0029] The system and platform may be configured for the exchange of data through gated exchanges. A gated exchange allows the receiving user to set conditions on the type of cannabis data being received from another user. A gated exchange can include data validation as a criteria for cannabis data to be received.

[0030] The cannabis exchange system may utilize a central repository and/or host server to collect, exchange, and analyze the data. In addition, the cannabis exchange allows for the connection of third-party services to either collect, compare, and/or validate cannabis data outside the system.

[0031] The cannabis exchange utilizes a risk metric with configurable through customized risk indicium. The risk metric can be weighted, prioritized of importance, and coupled with cannabis validation, whether through the cannabis exchange or connected third- party services.

[0032] A cannabis exchange system, such through an online system or through an Automatic Programming Interface (API) integrated with other systems, allows for its users to connect to and communicate with other systems and system users.

[0033] Due to the legalization of cannabis, whether recreational or medical, and competing state and federal regulations, a cannabis exchange system provides an ideal forum for both entities and individuals to increase compliance towards regulations and reporting requirements; further, a cannabis exchange system allows for cannabis and non-cannabis entities and individuals to establish a risk tolerance when engaging in either current or prospective business opportunities with those involved, whether directly or indirectly, in the cannabis industry.

[0034] Presenting content items to cannabis exchange users allow either an individual or entity to create a risk tolerance threshold for their organization and validate cannabis data. This allows a cannabis exchange user to establish risk metrics tailored to their needs, as well as regulatory requirements, and create conditional rules and share those rules with others through rule-sharing.

[0035] In general, establishing risk tolerances for compliance controls, whether internal or external, and sharing cannabis data, coupled with cannabis data, can be performed through searching online, reading articles, and attempting to create their own risk levels manually. For example, an individual might have to determine the risk of dealing with a cannabis business by weighing, all materials research, manually and adjusting based upon their risk model; further, the risk model would be inaccurate if data is neither validated nor shared among participants to establish an industry standard. While the preceding manual processes can be presented to either the individual or entity through a manual process, it fails to address the dynamic legal and regulatory changes; further, it fails to establish both a risk metric and validation of the data.

[0036] The cannabis exchange is comprised of user-based inputs, data exchange processes and controls, risk modeling, validation tools, and machine learning to provide predicative analysis of cannabis-related activities

[0037] To better establish a risk model for cannabis-related activities and predicting compliance and irregularities, a cannabis exchange platform, such as through an online system or through an Automatic Programming Interface (API) integrated within other systems, computes risk metrics, either weighted or prioritized, based upon cannabis data to provide individuals and entities with a risk assessment model based upon either shared or user-inputted cannabis data. The system receives information from either user-based input, shared data, amount participants within the cannabis exchange system, or internet-based crawlers from public and/or private sources (“data requests”) on either a default or user-driven scheduled basis. Data requests are ingested into the cannabis exchange system. Once ingested, the cannabis data is categorized and labeled; if cannabis data is either conflicting or unassignable with existing categorizes or labels, then the cannabis exchange assigns the cannabis data based upon the cannabis data type. In one embodiment, the data requests are analyzed based upon the data structure of the cannabis data values through a probability threshold match. For example, Business “A” might collect and store only the last four digits of a personally identifiable number, such as but not limited to business licenses and social security numbers. Whereas Business “B” might store the whole personally identifiable number. During data ingestion, the cannabis exchange system would compare the data values and determine, based upon a probability threshold, that the cannabis data from both Business “A” and Business “B” are personally identifiable numbers.

[0038] The cannabis exchange system allows users and entities to configure a risk model with multiple indicia to determine risk tolerance based upon the ingested data. Risk models may be configured by the user based upon the risk indicia. Risk indicia may include the ingested data and external data sources. The risk indicia may be weighted and/or prioritized of importance, as well as combined. Weighted risk indicia are configurable by the user. Weighted values may be percentage based and may be categorizable. The percentage weight and range may be configured by the user; further, weighted values may be categorized. Categorization of weighted values may either be used for management purposes (internal usage) or with prioritization. In terms of the latter, a user may configure weighted values with prioritization. This means that the user may weigh the prioritization. For example, Business “A” can have Data 1 and Data 2 and their own weighted values; in addition, Business “A” can set a prioritization weight to Data 2 that would supersede Data 1. Since Data 2 has its own, independent weighted value, it also has a weighted prioritization value. In addition to weighted values, users can configure risk indicia with prioritization (“risk prioritization”). Risk prioritization allows a user to configure how to prioritize cannabis data. In one embodiment, an input feature allows a user to add a weight value to specific data values and set risk prioritization by assigning specific data values to take priority when all the values are weighted during the calculation process. For example, User “A” can weigh a value for a violation as 99% and a weighted value of 1% for total sales; however, User “A” can set a risk prioritization where total sales is prioritized over violations. In this instance, total sales would be weighted more heavily initially than violations since there is a risk prioritization. As will be understood, “total sales” and “violations” represent labels of categories or risk factors a user would see in an embodiment of the interface.

[0039] The risk indicia can include conditional statements to allow the user to filter the data, including weighted and risk prioritization values. Conditional statements allow the user to configure statements with the cannabis data in different variations. For example, User “B” can configure a conditional statement if in which violations are equal to or greater than a value of five, then set percentage weight at 51% and place into a category. Conditional statements do not require weighted nor categorization for risk models.

[0040] Once cannabis data is ingested, the user can validate the data through cannabis validation, as set forth within U.S. Patent Application Number 16812576. Coupled with cannabis validation, the cannabis exchange system allows users to validate the data when performing risk models; further, cannabis validation can be combined with weighted, risk prioritizations, and conditional logic whether combined or independently. Cannabis validation improves the accuracy of the cannabis data. Cannabis validation is not required for risk modeling. In one embodiment, a user can enable cannabis validation and validate license numbers, even if the license numbers are either partially collected, masked, or anonymized. For example, User “C” can configure a conditional statement to validate license agreement and assign the validated license a weighted percentage of 90% with a risk prioritization over total sales.

[0041] In one embodiment, the risk modeling module of the system includes a rule sharing module. The rule sharing module may be configured for users and entities to share rules with each other within the cannabis exchange system to either adopt the issues and/or perform risk scenarios with their data. “Issues” in this context may refer to issues faced in the industry; for example, there might be a change in the regulations/legislation that requires additional documentation to verify a business. Another example may include industry participants able to share information and determine there are issues with how data is being exchange, shared, and/or analyzed. The rule sharing module allows users and entities to adopt common rules to establish, if desired, an industry standard on how to develop, maintain, and improve risk models for both cannabis related businesses and non-cannabis related businesses involved in the cannabis industry. The rule sharing module may include a forum for comments and discussions to the shared rule and provides versioning of recommended changes. Rule Sharing can be coupled with cannabis validation. In one embodiment, User “D” can view available rules being shared by participants within the cannabis exchange system and perform preview transactions utilizing User “D’s” data without changing their existing risk modeling; further, User “D” can compare a shared rule against their rule and both view and compare the data output.

[0042] The cannabis exchange system allows for predictive analysis based upon the cannabis data being shared within the hosted environment. In predictive analysis, patterns and forecasting are creatable by users by utilizing the collected cannabis data. The cannabis exchange system is configured to extrapolate historical data and trends to forecast trends that the user may use in the various features of the system. Coupled with the cannabis validation tool, predictive analysis may be used to compare the collected data with real-time data being ingested within the cannabis exchange system to establish a pattern and trend. In one embodiment, User “E” creates conditional statements to run a predicative analysis and compares their data against the cannabis system data. Further, User “E” may couple their data against the cannabis validation tool to compare against real-time data being collected and ingested within the cannabis exchange system.

[0043] The cannabis exchange system is configured to allow users and entities to create, maintain, and share business operations data. Business operations data creates Compliance Profiles. A Compliance Profile is an aggregation of cannabis data associated with an entity and/or individual user. Compliance Profiles allow for historical, current, and real-time business operations data to gain insight and predictive behavior by creating risk metrics with risk indicia.

[0044] Cannabis data can be exchange within and outside the cannabis compliance system. The cannabis compliance system is configured for three (3) different exchange types: direct, brokered, and gated. The exchange types can be combined. A direct exchange is between users without any barriers to the exchange. A brokered exchange may include a disinterested party to collect data from different users and exchange when specific conditions are met, as determined by the users. A gated exchange requires either a direct or brokered exchange type. A gated exchange permits the receiving user to establish certain criteria prior to receiving the cannabis data to ensure its integrity and applicability. A gated exchange can include a data validation from either internal or external data sources, such as those within U.S. patent application 16/812,576.

[0045] FIG. 1 is a high-level block diagram of a system environment 100 for a cannabis exchange (“exchange”) system 140. The system environment 100 shown by FIG. 1 comprises one or more client devices 110, a network 120, one or more third party systems 130, the exchange system 140, one or more user or entity 150, and data input 160. The embodiments described herein can be adapted to other suitable online systems and backend systems, including offline environments in which a network 120 is either not required or an intranet.

[0046] The client devices 110 are one or more computing devices capable of receiving user input as well as transmitting and/or receiving data via the network 120. The crawlers 160 are one or more systems capable of receiving data from public and private sources on the internet as well as transmitting and/or receiving data via the network 120. In one embodiment, a client device 110 is a conventional computer system, such as a desktop or laptop computer. Alternatively, a client device 110 may be a device having computer functionality, such as a personal digital assistant (PDA), a mobile telephone, a smartphone or another suitable device. A client device 110 is configured to communicate via the network 120. In one embodiment, a client device 110 executes an application allowing a user of the client device 110 to interact with the cannabis system 140. For example, a client device 110 executes a browser application to enable interaction between the client device 110 and the cannabis system 140 via the network 120. In another embodiment, a client device 110 interacts with the cannabis system 140 through an application programming interface (API) running on a native operating system of the client device 110, such as but not limited to IOS® or ANDROID™.

[0047] The client devices 110 are configured to communicate via the network 120, which may comprise any combination of local area and/or wide area networks, using both wired and/or wireless communication systems. In one embodiment, the network 120 uses standard communications technologies and/or protocols. For example, the network 120 includes communication links using technologies such as Ethernet, 802.11, worldwide interoperability for microwave access (WiMAX), 3G, 4G, code division multiple access (CDMA), digital subscriber line (DSL), etc. Examples of networking protocols used for communicating via the network 120 include multiprotocol label switching (MPLS), transmission control protocol/Intemet protocol (TCP/IP), hypertext transport protocol (HTTP), simple mail transfer protocol (SMTP), and file transfer protocol (FTP). Data exchanged over the network 120 may be represented using any suitable format, such as hypertext markup language (HTML) or extensible markup language (XML). In some embodiments, all or some of the communication links of the network 120 may be encrypted using any suitable technique or techniques.

[0048] FIG. 2 is high-level block diagram of the cannabis compliance system 140 that operates within a web server 240. The block enumerated as 240 is shown to represent an access point to the web server. The system environment 140 shown by FIG. 2 comprises of a user profile 205, content management system 210, action logger 215, a web server 240, rule sharing platform 201, reporting platform 202, and a product analysis platform 203 to create the cannabis compliance system 140. The user profile 205 comprises both individual, business, and government information within the cannabis compliance system 140. The user profile 205 contains personally identifiable information on the user 150 to operate within the cannabis compliance system 140. The user profile 205 creates the content management system 210 based upon their data, data inputted, data ingested, and data being shared within the cannabis compliance system 140 by users 150, third-party systems 130, and crawlers 160. The content management system is also inclusive and the rule sharing 201 and product analysis 203 as those processes create and process data to achieve different outcomes. The action logger 215 logs the action of all users 150, crawlers 160, third-party system 130, and data collection and sharing of the cannabis exchange and compliance system 140. The rule sharing system 201 provides an instance where users can create, manage, and exchange customized rules, which are known as conditional statements based upon collected and ingested data within the cannabis compliance system 140. The reporting system 202 utilizes collected data that allows users 150 to create reports. The production analysis 203 provides the analysis processes to analysis and provide predictions of collected data.

[0049] FIG 3 is a high-level flowchart of a method for ingesting, processing, and arranging cannabis data within the cannabis compliance system 140. Cannabis data is defined as data collected related, indirectly or directly, to cannabis activities. Cannabis data types is neither static nor easily definable as multiple data points are obtainable. Cannabis Data Type can include, but not limited to company information, beneficial owners’ information of cannabis companies, social media postings, blog posts, videos, and other data generated and collected by a third-party. In one embodiment, the cannabis compliance system 140 can collect cannabis data from social networking sites, such as the Twitter® handle and related replies and comments from Twitter® handles. In another embodiment, the cannabis compliance system 140 can match social media handles, such as Facebook® and Twitter®, to existing cannabis businesses and their owners.

[0050] Cannabis data is ingested 301 into the cannabis compliance system 140 from users 150, third party system 130, crawlers 160, and client devices 110. Ingested data 301 is processed 302 by the cannabis compliance system 140. Data processing 302 is the analysis of the type of cannabis data being ingested 301 in the cannabis compliance system 140. In one embodiment, the ingested data 301 of news articles about a particular cannabis business or individual who owns a cannabis business are processed within the cannabis compliance system 140 to be analyzed to determine the data type; in this instance, it would be a news article. Cannabis data is analyzed based the Cannabis Data Type and is labeled and assigned 303. Cannabis Data Type is based upon the source and the type of data. In one embodiment, a blog, social media, news article, and government sources are Cannabis Data Types. In another embodiment, the cannabis data type is analyzed and assigned a risk metric based upon the sentiment type. See also US patent application 16/812,574. As cannabis data and cannabis data type are labeled and assigned 303 within the cannabis compliance system, the cannabis data is validated 304 by third-party services. Data validation 304 occurs from third-party systems 130, client devices 110, and crawlers 160, whether internal or external. In one embodiment, cannabis data is validated from government sources to determine the accuracy of the information being collected; for example, social media information is ingested 301 and alleges violations of Company “A”. The ingested information is compared against the information from multiple states to validate the accuracy of the claims against Company “A”. In this embodiment, the data is properly assigned based upon the matching of the cannabis data. See also US patent application 16/812,574.

[0051] Once the cannabis data type is labeled and assigned 303 and validated 304, then the cannabis data is stored 305 within the cannabis compliance system 140. After the cannabis data is stored 305, the cannabis data can be exchanged 306 within or outside the cannabis compliance system 140 between users 150, third-party system 130, and client devices 110. In one embodiment, cannabis data collected can be exchanged between financial institutions and government agencies to validate the cannabis data to determine account opening, risk, and continuing due diligence on existing accounts. In another embodiment, the cannabis data collected can be exchange the users 150 within the cannabis compliance system 140 to validate vendors and customers.

[0052] FIG. 4 is a flow chart of the exchange of cannabis data within the cannabis compliance system 140. Data exchange 306 occurs either within data within the cannabis compliance system 140 or from either third-party system 130 or crawlers 160 from outside the cannabis compliance system 140. Data may be exchanged through the cannabis compliance system 140 either through a direct exchange 401 or a brokered exchange 402. Whether a direct exchange 401 or a brokered exchange 402, the cannabis data may be exchanged through two forms of data masking: anonymization and pseudonymization; however, the user 150 can apply both data masking forms or neither form of data masking 403 to the cannabis data being exchanged. Cannabis data exchanges are initiated by a user 150 to another user 150. A user 150 can exchange cannabis between multiple users 150 either within or outside the cannabis compliance system 140. A direct exchange 401 or cannabis data occurs when either one user 150 requests specific cannabis data or a user 150 wants to exchange cannabis data without the receiving user 150 requesting the cannabis data. A brokered exchange 402 occurs between two users 150 and require a neutral party to collect and distribute the cannabis data, as per the agreed upon terms between the two users 150.

[0053] FIG. 5 is a high-level flow chart diagram of determining risk type of stored cannabis data within the cannabis compliance system 140. Risk assessment is based upon the stored data 305, including during data exchanges between users 150. The stored cannabis data 305 is analyzed to determine the risk type 502. Risk type is determined based upon the cannabis data type. The risk type 502 is either determined automatically by the cannabis compliance system 140 or by the user 150. The stored cannabis data 305 is assigned a risk value 503 based upon the data risk type 502. A risk value 503 is either a predetermined value type, whether an integer or word, or assigned manually by the user 150. A risk value 503 can be assigned a weighted risk value 504. A weighted risk value 504 provides a prioritization of the risk associated with the stored cannabis data 305. The prioritization of a weighted risk value 504 provides the user 150 with the ability to determine if the stored cannabis data 305 is significant enough when determining risk. Further, the user 150 can set a data risk penalty 505 to the stored cannabis data 305, as well as couple it with risk weight 504. A data risk penalty may be for example, a numeric value, a character, alphanumerical, or a combination of the preceding to assist the user 150 in determining whether the stored cannabis data 305 shall be construed as a penalty. A penalty risk 505 may be for example, a numerical value, a character, alphanumerical, or a combination of the proceeding. A penalty risk 505 may be an additional clarification, whether automated by the cannabis compliance system 140 or by the user 150. The user 150 can assign penalty and risk weight 506 to the stored cannabis data 305 when assessing risk; as such, those risk settings are stored 507 against the user’s profile 205. After the settings have been stored, then the user 150 can execute the risk analysis 508 against either the stored cannabis data 305 and during data exchanges, whether direct exchanges 401 or brokered exchanges 402 with other users 150 either within or outside the cannabis compliance system 140.

[0054] FIG. 6 is a flow chart of the rule sharing marketplace 601. A “rule” as used herein may be a custom logical statement in which the user can configure to perform specific tasks within the cannabis compliance system to address either local, state, federal, or cross- border regulations on cannabis (medical or recreational). A rule may be an if/then logical statement that can be simple or contain complex logical statements. The rule sharing marketplace 601 may be a part of the cannabis compliance system 140. The rule sharing marketplace 601 allows users 150 to either create rules 603 or view existing rules 602. The rule sharing marketplace 601 requires either cannabis data 305, data from third-party systems 130, or crawlers 160. A user 150 can view existing rules from other users 602. A user 150 can either preview a rule 606 with its own stored cannabis data 305 or get the adaptive rule 604 without previewing the rule 606. A rule preview 606 allows the user 150 to apply their own cannabis data 605, which the system may use to determine the output without adopting the rule 604. For example, the system will display a hypothetical output based upon the rule configured by the user. A user can preview the rule 606 from another user 150 and adjust the rule without impacting other users 150 who have either created the rules for the rule sharing marketplace 601 or who are using the shared rule within the cannabis compliance system 140. If the user 150 wants a rule, whether directly or after previewing the rule 606, then they can adopt the rule 604 and apply it to their cannabis data 605. A user 150 can execute a rule 607 at any time. The system 140 can execute a rule manually, scheduled, or automatically, as based upon the requirements of the user 150.

[0055] The system 140 includes a feature for the user 150 to create their own rules 603 based upon either stored cannabis data 305 or ingested cannabis data 607 third-party systems 130, crawlers 160, and client devices 110. A user 150 may create their own rules 603 based upon conditional statements 607. A user 150 may create conditional statements 608 to properly filter cannabis data and get desired outputs. After a rule has been created by a user 150, the user 150 may either apply the rule to their cannabis data 605 or place it on a marketplace 606. A user 150 may also list their rule on the marketplace 606 and keep it private within their user account.

[0056] A rule from the rule sharing marketplace 601 is independent and may be applied to different cannabis data 605 sets configured by the user 150. A rule may be applied to third-party systems 130, crawlers 160, and client devices 110. Whether stored cannabis data 305 or ingested cannabis data 607, a rule may have different conditional 608 statements.

[0057] FIG. 7 is a flow chart of how predictive analysis is performed within the cannabis compliance system 140 from multiple data sources: crawlers 160, a user’s 150 cannabis data 305, or ingested cannabis data 607 from third-party systems 130 or client devices 110. The preceding data sources may be combined when data is inserted into the predicative analysis system 203. The predictive analysis system 203 is divided into three steps: analysis of the data 701, determining trends 702 based upon the analysis of the data 701, and the validation of the data 703 from data sources. See also US patent applicationl6/812,574. The preceding steps assist the user 150 to get the desired output.

[0058] FIG. 8 is a flow chart of how stored cannabis data 305 and ingested data 607 is matched against cannabis businesses and their respective owners 801. The stored cannabis data 305 may be either from the user’s 150 content management system 210 or from within the cannabis compliance system 140. The ingested data 607 may be from crawlers 160, third-party systems 130, or client devices 110. The cannabis data may be analyzed and matched to existing businesses and owners in the cannabis compliance system 140. If a match is found from the cannabis data, then the cannabis data may be stored against that the appropriate profile. If no match is found, then a profile is created 806 based upon the data. Whether an existing profile 801 or a new profile has been created 806, then the cannabis compliance system 140 analyzes the data to determine risk 802. Risk analysis by the system may either be done automatically or manually by the user 150. In some embodiments, the system may perform risk analysis based upon trends 703 within the industry, for example, as based upon either the data ingested from users or third-party services or based upon the information gathered by crawling other sites. Based upon that data, a risk analysis may be performed, whether in the aggregate, sectors, or by a single company. For example, the system can analyze all the data obtained and determined, based upon the data, that the trends are risky due to variety of factors. After the risk assessment, the cannabis data may be either be validated 805 or properly assigned to a risk category 803. Data validation 805 occurs from either, independently or collectively, third-party systems 130, crawlers 160, users 150, and client devices 110. See also US patent application 16/812,574. Dependent upon the data validation settings 805 (See also US patent application 16/812,574), the cannabis data is filtered and assigned a risk criterion 803. After the cannabis data is analyzed 802, validated 805, and assigned a risk criterion 803, the cannabis data is searchable 804. Searchable cannabis data 804 allows users 150 to search for and exchange the cannabis data to determine risk on a business or individual. [0059] FIG. 9 is a flow chart of the automatization of data anonymization and pseudonymization exchanges between users 150 within the cannabis compliance system 140, including third-party systems 130 and client devices 110. Both a brokered exchange 402 and direct exchange 401 between users 150 of cannabis data can require data anonymization and pseudonymization. A user 150 ingests data 901 into the cannabis compliance system 150. If anonymization and pseudonymization is required for data masking during either a brokered exchange 402 or a direct exchange 401 with no special anonymization and pseudonymization process, then the data is processed 902 to anonymize and pseudonymize the cannabis data 903. After the cannabis data is anonymized and pseudonymized, the cannabis is stored 904 in the cannabis compliance system 150. If a brokered exchange 402 is used, then the anonymized and pseudonymized cannabis data is stored with the third-party broker. If a direct exchange 401 is used, then the anonymized and pseudonymized cannabis data is stored within the user’s 150 respective instance in the cannabis compliance system 140. Once the cannabis has been anonymized and pseudonymized, a user 150 may either request 905 the cannabis data directly or through the broker, as dependent upon the type of exchange. A user request 905 can either be denied 908 or approved 906 by either the user 150 or the broker, if a brokered exchange 402 is used for the cannabis data exchange. If the user request 905 is denied 908, then the cannabis data is not shared 909. If the user request 905 is approved 906, then the user receives the anonymized and pseudonymized cannabis data 907. If approved 906, then the user can either have the cannabis compliance system 150 de-anonymize and de-pseudonymize the cannabis data 910 to receive the actual cannabis data 907 or the user 140 may receive the anonymized and pseudonymized cannabis directly 907.

[0060] FIG. 10 is a flow chart of the customization of data anonymization and pseudonymization exchanges between users 150 within the cannabis compliance system 140, including third-party systems 130 and client devices 110. A user 150 may configure their own logic 1001 related to the anonymization and pseudonymization of cannabis data to be exchanged within the cannabis compliance system 140. A user 150 configures their logic based upon conditional statements and patterns to be utilized for data anonymization and pseudonymization 1001. Once configured, the cannabis data is ingested 1002 into the cannabis compliance system 140. The user 150 then applies to their customized anonymization and pseudonymization 1003 to the cannabis data. Once the data is anonymized and pseudonymized 1003, then the cannabis data is stored 1004 in the cannabis compliance system 140 or with a broker, as dependent whether the exchange time is either a direct exchange 401 or a brokered exchange 402, respectively. A user 150 can request the cannabis data 1005. A user request 905 may either be denied 908 or approved 906 by either the user 150 or the broker, if a brokered exchange 402 is used for the cannabis data exchange. If the user request 1005 is approved 906, then the user either receives the anonymized and pseudonymized cannabis data directly 1006 or the receiving user 150 may apply their own anonymization and pseudonymization 1007 to receive the data 1008.

[0061] FIG. 11 is a flow chart of cannabis data validation either with or without a gated environment. As coupled with direct exchange 401, data validation may be utilized during the exchange. A user 150 may exchange directly 1101 with neither data validation 1102 nor gated process 1103. In the direct exchange 1101, the data is neither validated nor checked against the requirements of the receiving user 150. Data validation 1102 may occur with crawlers 160, third-party systems 130, and US 16/812,576 . A direct exchange 401 may include a gate 1103, including data validation 1102 with the gate 1103. A gate 1103 are a set of parameters configured by the receiving user 150 to ensure the appropriate cannabis data is properly exchanged. A gate 1103 with data validation 1102 configured by the receiving user 150 ensures the appropriate cannabis data is properly exchanged and validated by either crawlers 160, third-party systems 130, and US patent application 16/812,576.

[0062] The foregoing description of the embodiments has been presented for the purpose of illustration; it is not intended to be exhaustive or to limit the patent rights to the precise forms disclosed. Persons skilled in the relevant art can appreciate that many modifications and variations are possible in light of the above disclosure.

[0063] Some portions of this description describe the embodiments in terms of processes and symbolic representations of operations on information. These algorithmic descriptions and representations are commonly used by those skilled in the data processing arts to convey the substance of their work effectively to others skilled in the art. These operations, while described functionally, computationally, or logically, are understood to be implemented by computer programs or equivalent electrical circuits, microcode, or the like. Furthermore, it has also proven convenient at times, to refer to these arrangements of operations as modules, without loss of generality. The described operations and their associated modules may be embodied in software, firmware, hardware, or any combinations thereof.

[0064] Any of the steps, operations, or processes described herein may be performed or implemented with one or more hardware or software modules, alone or in combination with other devices. In one embodiment, a software module is implemented with a computer program product comprising a computer-readable medium containing computer program code, which can be executed by a computer processor for performing any or all of the steps, operations, or processes described.

[0065] Embodiments may also relate to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, and/or it may comprise a general-purpose computing device selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a non- transitory, tangible computer readable storage medium, or any type of media suitable for storing electronic instructions, which may be coupled to a computer system bus. Furthermore, any computing systems referred to in the specification may include a single processor or may be architectures employing multiple processor designs for increased computing capability.

[0066] Embodiments may also relate to a product that is produced by a computing process described herein. Such a product may comprise information resulting from a computing process, where the information is stored on a non-transitory, tangible computer readable storage medium and may include any embodiment of a computer program product or other data combination described herein.

[0067] Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the patent rights be limited not by this detailed description, but rather by any claims that issue on an application based hereon. Accordingly, the disclosure of the embodiments is intended to be illustrative, but not limiting, of the scope of the patent rights, which is set forth in the following claims. Persons of ordinary skill in the art may appreciate that numerous design configurations may be possible to enjoy the functional benefits of the inventive systems. Thus, given the wide variety of configurations and arrangements of embodiments of the present invention the scope of the invention is reflected by the breadth of the claims below rather than narrowed by the embodiments described above.

INDUSTRIAL APPLICABILITY

[0068] Embodiments of the invention can be useful for an online host platform generating a risk tolerance value associated with cannabis related business.