Note: Descriptions are shown in the official language in which they were submitted.
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CANNABIS RISK COMPLIANCE AND EXCHANGE PLATFORM
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
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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.
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[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
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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.
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[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
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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
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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
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"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;
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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
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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 IOSO or ANDROIDTM.
[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/Internet protocol (TCP/IP), hypertext transport
protocol (HTTP),
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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
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140 can match social media handles, such as Facebook0 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
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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
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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
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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 application16/812,574.
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.
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[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
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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
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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.
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