Description:FORM 2
The Patents Act, 1970
(39 of 1970)
&
The Patents Rules, 2003
(See sec 10 and rule 13)

COMPLETE SPECIFICATION

“Continuously monitoring operational and regulatory controls system by deep data analysis with intuitive compliance work-flow ’’

Claptek Private Limited, an Indian,
having address at Der Deutsche Parkz, 31, Subhash Nagar Rd, near Nahur Station, Nahur West, Mumbai, Maharashtra 400078, India.

The following specification describes the invention:
FIELD OF THE INVENTION:

The present invention relates to a control monitoring system for ERP applications. More particularly, the present invention relates to a Continuous Control Monitoring and Self-control Assessment system for ERP applications for identification of fraudulent activities, behavioral patterns and to fulfill auditory and regulatory requirements and for controlling the subjectivity of the opinion using quantified responses and survey.

Background of the invention:

Enterprise Resource Planning Is a type of business management software that allows for all departments of a company to be managed in one place. An ERP application typically refers to one of several apps or modules within an ERP software system. Enterprise resource planning (ERP) is a software system that helps you run your entire business, supporting automation and processes in finance, human resources, manufacturing, supply chain, services, procurement, and more. ERP manages organizations day-to-day business activities, such as accounting, finance, procurement, project management, supply chain, and manufacturing. Enterprise resource planning systems are complete, integrated platforms, either on-premises or in the cloud, managing all aspects of a production-based or distribution business. Furthermore, ERP systems support all aspects of financial management, human resources, supply chain management, and manufacturing with your core accounting function.
Regulatory requirements are rules and guidelines put forth by a governing body. These include standards for different products like food safety and environmental protection, regulations for how businesses operate such as minimum wage laws, and laws that protect consumers from monopolies or fraud.
Examples of regulatory compliance laws and regulations include the Payment Card Industry Data Security Standard (PCI DSS), Health Insurance Portability and Accountability Act (HIPAA), Federal Information Security Management Act (FISMA), Sarbanes-Oxley Act (SOX), EU's General Data Protection Regulation (GDPR).
In order to control fraudulent activities, behavioral patterns and to fulfill auditory and regulatory requirements, Continuous controls monitoring is necessary. Continuous controls monitoring (CCM) is a set of activities to reduce business losses through continuous monitoring and reducing the cost of audits through continuous auditing of the controls in Financial, Transactional or any other ERP applications. Every organization has their business processes. These processes need to be monitored on periodic basis. These assessments provide confidence to management that all business is running as per expectations. Process owners are defining certain control checkpoints to assess the process. Many of checkpoints are data driven. These data driven control check points monitored periodically against the data generated by applications. If there are any observations or findings will be taken up with the business owners for further follow ups and rectifications of issues/ findings

This entire monitoring process is known as Continuous Control Monitoring. Broadly this process comprises Data Understanding, Data fetching and consolidations, Data Massaging, Business Rules processing and compliance. The major stakeholders are IT team, Database team, Central Process Unit team, Business owners and senior management.
This monitoring process also helps to identify any fraudulent activities, regulatory requirements, Closure to real time reporting, Reducing compliance cost, etc.

We live in a time of rising risks including financial, reputational and now health risks. Changing regulations, increased scrutiny and compliance costs are major drivers. An organization’s ability to scale its operations and increase efficiency through reduced cycle times are of paramount importance. As the complexities of risk management and compliance increase, businesses must work to operationalize the overall risk management effort. Further, firms have built up multiple duplicative and overlapping controls that must be rationalized.

Industry Problem:
Currently the industry is managing Continuous Control Monitoring in bits and pieces through various different tools and technologies. Also, there are lots of dependencies of manual interventions among different teams. There is no end-to-end solution available to automate this process.
For e.g. Central Processing team is heavily depends on IT team and ETL tools for data fetching. Data massaging and consolidation is another manual process. Business rule processing is managed by BoTs, Refinements of further results again carried out manually and compliance of observations are managed either through emails or any workflow management tool.

One of the prior art means is disclosed in remote industrial monitoring and analytics using a cloud infrastructure. A cloud-based infrastructure facilitates gathering, transmitting, and remote storage of control and automation data using an agent-based communication channel. The infrastructure collects the industrial data from an industrial enterprise and intelligently sorts and organizes the acquired data based on selected criteria. Message queues can be configured on the cloud platform to segregate the industrial data according to priority, data type, or other criteria. Behavior assemblies stored in customer-specific manifests on the cloud platform define customer-specific preferences for processing data stored in the respective message queues. An agent-based analytics framework in the cloud platform performs desired analytics on the data using distributed parallel processing.

Another one prior art means is disclosed in Intelligent condition monitoring and fault diagnostic system for preventative maintenance. A system for condition monitoring and fault diagnosis includes a data collection function that acquires time histories of selected variables for one or more of the components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, and a reasoning function for determining the condition of the one or more components from the one or more hypotheses.

The prior art solution are not able to do the continuous control monitoring and self-assessment for ERP applications simultaneously. So there is a need for a continuous control monitoring and self-assessment system which provides end to end solution for CCM and CSA requirement. The present invention has rule based allocation engine with facility for manual overriding of assignments and delegations. The present invention has conditional response capabilities (dynamic workflow) and has ease in workflow design. The present invention has N-number of node configuration and inbuilt interactive dash boarding. The present invention has compliance rating and configurable survey module and has Smart auto closure of exception to save the reviewer’s efforts. The present invention has configurable De Dup capabilities and has configurable correlation capabilities to find out existence of similar criteria or patterns in other scenarios. The present invention has download and upload capabilities with larger set of data and has AI ML capabilities to support central process unit for decision making. The present invention has role based authorization, Form based and LDAP authentication, APIs for centralized User Management and has on premise installation.

Objects of the invention:

The main object of the present invention is to capture data effortlessly and to evaluate, extract and validate the data using AI and rule based BOTS to find exceptions by validating the data points.
Yet another object of the present invention is to reduce manual work, errors, minimize costs and improve overall efficiency and to provide a cost effective system.
Another object of the present invention is to identify fraudulent activities and to fulfil auditory requirements and regulatory requirements.
Another object of the present invention is to control the subjectivity of the opinion using quantified responses and survey

Another object of the present invention is to identify the user behavior for auditing, analysis of data.

Summary of the invention:
Accordingly, an AI/Ml based system for Continuous Control Monitoring and Self-Assessment system for ERP applications. The present invention helps in fulfilling the complex requirements of Continuous Control Monitoring and Continuous Self-Assessment for different industries. The present invention is able to configure Data Fetching, Data fetching, Correctness and completeness of data. BoTs configuration, Refinement of results, workflow management and dash boarding & Reporting in a single solution. The present invention has capability to configure augmented interactive dashboards for different kinds of users. It has inbuilt data processing BOTs with pre-defined classified libraries of scenarios to fetch and filtered out data at initial stages. The Smart Workflow module of the present invention helps the users to easily prepare workflow for different scenarios.
Configurational Workflow is implemented accommodating any kind of Organizational hierarchy and underlined data hence makes itself much flexible and open to any kind of industry and organizations within. The ownership definition of workflow is fully automated through central allocation rule-based engine. Workflow responses are quantified hence used to get compliance ratings & health at different levels. Multiple rating parameters are configured at different levels like Organization hierarchy, Exception data and BOT.

Description of the drawings:

Fig 1 is the front view of the system.
Fig 2 is the internal flow of the system.
Fig 3 is the block diagram of the system.
Fig 4 is the CCM/CSA framework.
Detailed description of the invention with respect to drawings:
The present invention is an AI/Ml based system for Continuous Control Monitoring and Self-Assessment system for ERP applications. The present invention helps in fulfilling the complex requirements of Continuous Control Monitoring and Continuous Self-Assessment for different industries. The present invention is able to configure Data Fetching, BoTs configuration, Refinement of results, workflow management and dash boarding & Reporting in a single solution. The present invention has capability to configure augmented interactive dashboards for different kinds of users. It has inbuilt data processing BOTs with pre-defined classified libraries of scenarios to fetch and filtered out data at initial stages. The Smart Workflow module of the present invention helps the users to easily prepare workflow for different scenarios.
Configurational Workflow is implemented accommodating any kind of Organizational hierarchy and underlined data hence makes itself much flexible and open to any kind of industry and organizations within. The ownership definition of workflow is fully automated through central allocation rule-based engine. Workflow responses are quantified hence used to get compliance ratings at different levels. Multiple rating parameters are configured at different levels like Organization hierarchy, Exception data and BOT.
The present invention use data points for process validation and to find exceptions and use exceptions in work flow management. There is no human intervention. ERP data is used and is monitored and is operated in auto pilot mode. If there are no exceptions, email goes to the auditor that there are no exceptions.
In one embodiment, the present invention helps to capture data effortlessly and to evaluate, extract and validate the data using AI to find exceptions. The present invention reduces manual work, errors, minimize costs and improve overall efficiency and to provide a cost effective system. The present system has a capability of auto closure, Auto Drop, Dedup and correlation detection across the application universe of exceptions based on BOTs configuration. The inbuilt AI ML capabilities of application helps to refine and further BOT rule discovery and also provides intelligence in exception closure cycle by marking exception severity. ML capabilities of the present system are also used to identify false positive exception patterns and anomalies criticality classification. The present system has a modular approach and within modules it has several flexibilities to make it most adoptable solution for any type, size, need of the customer. Each module is plug and play and is added as per the needs of future. As the system of the present invention is an end to end solution, data points are collected together and information is achieved which is beneficial for any kind of information about the process and organization.

In another embodiment, the pictorial presentation (fig 1) & block diagram (fig 2) of the Continuous Control Monitoring system. The present invention configured for the workflow process. Administrator uploads organizational structure Master through Excel upload. Same file will be further used by different modules for configuration and reporting.
Frequency Distribution: Scenario-wise Exception In-flow frequency is configured. Daily/Bi-weekly/monthly and so on. Pendency Ageing parameters is configured for dashboards.

In one embodiment, roles and responsibility is configured using existing organization master files. E.g. Staff Master is configured where rules based configuration is executed for Salary >10 Lakhs is assigned as Audit supervisor and Salary <10 Lakhs is assigned as Audit level 1 users.
BOTS Exception Rules:
• The present invention has predefined set of parameterized business rules for multiple processes. Configuration of those business rules are easy and is controlled by Application administrator.
• The present invention has feature to schedule BOTs at different frequency. BOTS are smart enough to validate the availability and completeness of data before applying business rules.
• The present invention is also able to configure new customized BOTs prepared by users.
• BOTS is temporarily suspended for defined timeframes.
BOTS Response Rules:
• BOTS is configured to automate repetitive patterns for alert closure / false positive tagging saving Auditors time and increasing efficiency.
• Rule based exception movement: Scenario wise unique workflow for exception movement is configured. Account >10 Lakhs exception is moved to Business supervisor while Account <10 Lakhs is moved to Business user.
• Predefined checklist such as Independent / depended / Ad-hoc questionnaire with Multiple type of answers data type are configured.
Analytics Layer
ETL:
In another embodiment, using extensive existing Libraries for control points business rules and capabilities to connect with multiple sources. ETL module has capability to fetch and transform large set of data into usable formats. The final output of ETL is used for analysis of BOTs.

Advance Analytics:
AI/ML capabilities Integrated solution where patterns for exception closure. Application is identifying the response patterns and based on confidence closes the exceptions. This saves lots of Auditor’s time for reviewing responses. AI/ML capabilities also helps to identify false positive exceptions. Application is learned and ultimately deliver inputs to the BOTS making the process for time and work efficient for AUDITORS. AIML capabilities is also lead to exception criticality classification which help users to set the priority.

RISK MATRIX:
Branch wise/unit wise risk classification is configured based on each scenario exception data. This helps to identify different units of organization hierarchy for risk categorization e.g. High / Medium / Low on time series basis.

Control self-assessment:

Business owner sometimes do control self assessment of his business process data. If some indications are there, they are shown in umber zone.

It is done for control self assessment if there is need to change the parameters.

In another embodiment, as shown in fig 2, the system of the present invention has capability to read and fetch data from variety of source system. Once data fetched into the system, scheduled BoTs are triggered for execution on auto pilot mode. The output of BoTs are considered as raw reports. The present invention has library of BoTs where user only has to configure parameters based on the organizational need. Raw reports are validated for removing duplicates. De dup parameters can be configured at granular level. Further Key fields data are correlated with other reports data. This final report data then used by Assignment rule engine for finding out assignments of owners at all stages of workflow. This output then used by Risk rating engine to calculate risk ratings at granular level. The system of the present invention allows to define configurable risk factors and parameters. This complete report data stored as exception database.

This exception data then used by workflow engine to perform compliance. Exception data can be tracked as single line item wise or group of line items based on predefined parameters. The system of the present invention allows to configure workflow of N stages for each type of scenario / report. The system of the present invention also allows to configure various conditions & escalation parameters while configuring flow from one stage to other. These features make workflow more robust and dynamic.

The system of the present invention allows to configure survey for each scenario with granular level configuration that who will submit the survey and who will assess the answers. Survey engine allows to configure mandatories and dependency among questions based on answers. Survey engine allows to configure weightages to each answer. These weightages further used for defining patterns, compliance rating and Auto closure configurations.

AI /ML module uses response data and exception history to identify the severity and priority of exceptions. The system of the present invention allows to configure severity parameters for each scenario / report. AI/ML module also monitor exception and responses patterns and suggests possible changes at BoT levels.

Exception data further showcased in tracker to the users with pendency details. The system of the present invention allows to configure Pendency parameters as per organizational requirements. Exception data along with rating information and severity suggestions also used to prepare various dashboard for different kinds of users. The system of the present invention allows to configure different types of interactive dashboards as per user roles.

Advantages of the Product/ Process / Concept / Invention:

• End to end solution for CCM and CSA requirement
• Allocation Rule Engine
• Manual reassignment and delegation capability
• Conditional Response capabilities (Dynamic workflow)
• Ease in workflow design
• N-number of node configuration
• Inbuilt interactive dashboarding
• Global search
• Configurable survey module
• Compliance Rating Configurations
• Auto closure of exception
• Auto Drop of exception
• Configurable De Dup capabilities
• Configurable Co-relation capabilities
• Download and Upload capabilities with higher set of data
• AI ML capabilities
• Role based authorization
• Form based and LDAP authentication
• APIs for centralized User Management
• SaaS complied
• Fully scalable

, C , Claims:Claims:
We claim:
1) Operational and Regulatory Continuous control monitoring and self-assessment system for any kind of industry by deep data analysis with intuitive compliance work-flow comprising of;
a. inbuilt data processing BOTs with pre-defined classified and configurable libraries of Control check points covering different industry types to fetch and filtered out exceptional data at initial stages;
b. a bot operating on intranet for users to consume meaningful data and quickly action out the same;
c. Central monitoring Unit for effective and reasoning-based decision-making activity and assisting in quick Root Cause analysis and identification of resolutions to avoid future occurrence of such events and
d. a database for storing of the data;
wherein the system provides meaningful information and insights of operational weaknesses and regulatory processes gaps thereby reducing the time gap between the event and its identification.

2) Operational and Regulatory Continuous control monitoring and self-assessment system for any kind of industry as claimed in claim 1, wherein the said system configures multi source Data Fetching of varied Velocity, Veracity and Volumes, BoTs configuration based on Need to Know and Need to Do basis, Refinement of results based on Materiality of event and its impact on the organization, workflow management based on roles and Authority matrix, risk assessments based on international best practices and dash boarding & Reporting for quick visualization and corrective actions with Root Cause analysis.

3) Operational and Regulatorily Continuous control monitoring and self-assessment system for any kind of industry as claimed in claim 1, wherein the said system configures augmented interactive dashboards for different grades of users eliminating the spread-sheet based activities and creating a centralized database for better understanding of issues with unified view.

4) Operational and Regulatorily Continuous control monitoring and self-assessment system for any kind of industry as claimed in claim 1, wherein the said system is SaaS enabled providing quick deployment and enablement to end users with varied flexibility in utilizing the solution based on the organizational needs.

5) Operational and Regulatorily Continuous control monitoring and self-assessment system for any kind of industry as claimed in claim 1, wherein the said system helps the organization to increase efficiency by intelligently identifying Critical / High / Medium areas of risk for prioritized actions between different grades of users. The workflow auto assigns with help of BOTS the actionable and reasoning capturing mechanism for effective and transparent review with centralized monitoring teams.

6) Operational and Regulatorily Continuous control monitoring and self-assessment system for any kind of industry as claimed in claim 1, wherein the said system constantly keeps learning from the users behavior, comments and actions with Machine learning techniques and uses advance Artificial intelligence techniques to not only identify but predict certain futuristic behaviors that may lead to exception.

7) Operational and Regulatorily Continuous control monitoring and self-assessment system for any kind of industry as claimed in claim 1, wherein the said system enables users to quickly track pendency, escalate matters to senior management, draw sharp and clear inferences leading to value based resolution with help of extended and configurable dashboard leading to saving huge losses, regulatory fines and ensuring organizational goodwill.

Date: For, claptek pvt ltd
Agent of the applicant
Pallavi unmesh Deshmukh