ADVANCED COMPLIANCE TRACKING SYSTEM WITH COGNITIVE PROCESS DATA AND DECISION ANALYSIS

Abstract

ABSTRACT ADVANCED COMPLIANCE TRACKING SYSTEM WITH COGNITIVE PROCESS DATA AND DECISION ANALYSIS The present disclosure introduces advanced compliance tracking system with cognitive process data and decision analysis 100 to ensure adherence to regulatory and operational standards. The system features data ingestion module 102 for data collection and cognitive process analyser 104 that analyses decision-making behaviours to detect deviations. The decision analysis engine 106 evaluates compliance risks, while the AI-based predictive compliance module 108 predicts potential violations using historical data. It also comprises of real-time monitoring dashboard 110, automated reporting and auditing module 112, continuous learning and adaptation module 114, behavioural deviation alerts system 116, scenario-based compliance simulation feature 118, cognitive pattern recognition module 120, adaptive decision feedback mechanism 122, cross-industry regulatory updates integration 124, role-based access control for compliance actions 126, multifactor risk scoring system 128, behavioural audit trails 130, customizable cognitive compliance profiles 132, self-learning compliance enforcement rules 134, dynamic compliance reporting customization 136, AI-driven compliance training recommendations 138. Reference Fig 1

Specification

Description:Advanced Compliance Tracking System with Cognitive Process Data and Decision Analysis
TECHNICAL FIELD
[0001] The present innovation relates to systems and methods for compliance tracking using cognitive process data, artificial intelligence, and decision analysis.

BACKGROUND

[0002] Compliance with legal, regulatory, and operational standards is a critical requirement across industries such as finance, healthcare, and cybersecurity. However, organizations often struggle to keep up with the growing complexity and volume of regulations. Traditional methods of compliance management rely heavily on manual processes, human oversight, and rule-based systems, which are not only time-consuming and costly but also prone to human error. These conventional systems often react to compliance issues after they occur, providing limited real-time insights or predictive capabilities. Consequently, organizations face increased risks of non-compliance, which can result in penalties, reputational damage, and operational disruptions.

[0003] Available compliance tracking systems typically focus on static data analysis and rule-based monitoring, failing to capture the decision-making behaviors of employees or provide real-time feedback. While some advanced systems use data analytics, they generally lack the ability to predict potential compliance risks based on cognitive process data. Additionally, these systems often do not adapt to changing regulatory landscapes, resulting in outdated compliance measures.

[0004] The present invention overcomes these limitations by introducing a novel approach that integrates cognitive process data, artificial intelligence (AI), and decision analysis. This system analyzes decision-making patterns and behavior to identify potential risks and deviations from compliance protocols. Unlike existing systems, the invention provides real-time monitoring and predictive compliance analysis using AI models, helping organizations anticipate and address compliance issues proactively. The novelty of the invention lies in its continuous learning capability, which updates its predictive models based on new data, ensuring adaptability to evolving regulations. By offering features such as automated reporting, real-time risk evaluation, and cognitive behavioral analysis, the invention provides a more dynamic, scalable, and effective compliance tracking solution that reduces the burden on organizations while enhancing compliance accuracy and reliability


OBJECTS OF THE INVENTION

[0005] The primary object of the invention is to improve compliance tracking by integrating cognitive process data with AI-driven decision analysis.

[0006] Another object of the invention is to provide real-time monitoring of decision-making behaviors to identify potential compliance risks before violations occur.

[0007] Another object of the invention is to enhance the accuracy of compliance management through predictive analysis, allowing organizations to proactively address compliance issues.

[0008] Another object of the invention is to reduce the reliance on manual audits and rule-based systems by automating compliance reporting and risk evaluation.

[0009] Another object of the invention is to continuously adapt to evolving regulatory standards through machine learning, ensuring up-to-date compliance measures.
[00010] Another object of the invention is to offer a scalable solution that can be implemented across multiple industries, including finance, healthcare, and cybersecurity.

[00011] Another object of the invention is to provide a user-friendly dashboard that displays real-time compliance metrics, cognitive deviations, and predictive risk scores.

[00012] Another object of the invention is to improve decision-making processes by analyzing cognitive behaviors and decision paths, offering insights into how compliance decisions are made.

[00013] Another object of the invention is to enhance organizational transparency and accountability by providing detailed behavioral audit trails for compliance reviews.

[00014] Another object of the invention is to promote proactive compliance management by predicting emerging risks based on historical data and cognitive analysis, reducing the likelihood of regulatory breaches

SUMMARY OF THE INVENTION

[00015] In accordance with the different aspects of the present invention, advanced compliance tracking system with cognitive process data and decision analysis is presented. It is advanced compliance tracking system that integrates cognitive process data with AI and decision analysis to monitor and predict compliance risks. By analyzing decision-making behaviors and patterns, the system offers real-time insights and proactive risk identification. It features automated reporting, real-time monitoring, and continuous learning to adapt to changing regulations. The system is scalable across various industries and improves compliance accuracy, reducing manual intervention and enhancing organizational transparency. This novel approach ensures more efficient, dynamic, and reliable compliance management.

[00016] Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments constructed in conjunction with the appended claims that follow.

[00017] It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

BRIEF DESCRIPTION OF DRAWINGS
[00018] The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.

[00019] Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:

[00020] FIG. 1 is component wise drawing for advanced compliance tracking system with cognitive process data and decision analysis.

[00021] FIG 2 is working methodology of advanced compliance tracking system with cognitive process data and decision analysis.

DETAILED DESCRIPTION

[00022] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.

[00023] The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of advanced compliance tracking system with cognitive process data and decision analysis and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.

[00024] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

[00025] The terms "comprises", "comprising", "include(s)", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, or system that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system. In other words, one or more elements in a system or apparatus preceded by "comprises... a" does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.

[00026] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings and which are shown by way of illustration-specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

[00027] The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.

[00028] Referring to Fig. 1 advanced compliance tracking system with cognitive process data and decision analysis 100 is disclosed, in accordance with one embodiment of the present invention. It comprises of data ingestion module 102, cognitive process analyzer 104, decision analysis engine 106, AI-based predictive compliance module 108, real-time monitoring dashboard 110, automated reporting and auditing module 112, continuous learning and adaptation module 114, behavioral deviation alerts system 116, scenario-based compliance simulation feature 118, cognitive pattern recognition module 120, adaptive decision feedback mechanism 122, cross-industry regulatory updates integration 124, role-based access control for compliance actions 126, multifactor risk scoring system 128, behavioral audit trails 130, customizable cognitive compliance profiles 132, self-learning compliance enforcement rules 134, dynamic compliance reporting customization 136, AI-driven compliance training recommendations 138.

[00029] Referring to Fig. 1, the present disclosure provides details of advanced compliance tracking system with cognitive process data and decision analysis 100 which is designed to monitor, predict, and ensure adherence to regulatory and operational standards using cognitive process data and decision analysis. It integrates artificial intelligence and machine learning to analyze decision-making behaviors and provide proactive compliance insights. In one embodiment, the compliance tracking system 100 comprises of key components such as data ingestion module 102, cognitive process analyzer 104, and decision analysis engine 106, which facilitate real-time monitoring and risk evaluation. The system also features an AI-based predictive compliance module 108 and a real-time monitoring dashboard 110 for effective oversight. Automated reporting and auditing module 112 and behavioral deviation alerts system 116 further enhance compliance management, while continuous learning and adaptation module 114 ensures scalability and regulatory alignment. Additional components such as scenario-based compliance simulation feature 118 and cognitive pattern recognition module 120 improve predictive accuracy and risk detection.

[00030] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with data ingestion module 102, which continuously ingests structured and unstructured data from multiple sources, including regulatory databases, decision logs, and communication records. This data forms the foundation for all further analysis within the system. Data ingestion module 102 works closely with cognitive process analyzer 104 to ensure that decision-making data is available for pattern recognition and compliance monitoring. It also feeds data into the decision analysis engine 106 for real-time risk evaluation.

[00031] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with cognitive process analyzer 104, which uses AI to analyze decision-making behaviors, identifying patterns and deviations from established compliance protocols. Cognitive process analyzer 104 monitors the cognitive data from employees and compares it against standard operating procedures (SOPs). This component interacts with the decision analysis engine 106 to help evaluate the potential compliance risks based on detected behavioral deviations.

[00032] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with Decision Analysis Engine 106, which evaluates decision outcomes using risk models, decision trees, and probability analysis. Decision Analysis Engine 106 assesses how decision paths impact compliance, working alongside the AI-Based predictive compliance module 108 to forecast potential violations. It integrates data from Cognitive Process Analyzer 104 to offer a holistic view of decision-related risks.

[00033] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with AI-based predictive compliance module 108, which leverages historical compliance data and decision patterns to predict future compliance risks. AI-based predictive compliance module 108 interacts with the decision analysis engine 106 to proactively identify risks before they occur. It also collaborates with Real-time monitoring dashboard 110 to alert compliance officers about emerging compliance risks.

[00034] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with Real-time monitoring dashboard 110, which displays key compliance metrics, predictive risk scores, and deviations identified by the cognitive process analyzer 104 and AI-based predictive compliance module 108. Real-time monitoring dashboard 110 offers a comprehensive view of the organization's compliance status, enabling decision-makers to monitor risks in real-time. It also supports the automated reporting and auditing module 112 by visualizing data.

[00035] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with automated reporting and auditing module 112, which generates compliance reports and facilitates ongoing internal audits based on real-time data. Automated reporting and auditing module 112 draws data from the Real-time monitoring dashboard 110 and AI-based predictive compliance module 108 to ensure that reports reflect the current state of compliance. This component reduces the need for manual audits, streamlining the compliance process.

[00036] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with continuous learning and adaptation module 114, which updates the machine learning models based on new data and regulatory changes. Continuous learning and adaptation module 114 ensures that the system remains up-to-date with evolving compliance standards. It works in conjunction with the AI-based predictive compliance module 108 and cognitive process analyzer 104 to recalibrate risk models based on the latest compliance trends and behaviours.

[00037] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with behavioral deviation alerts system 116, which triggers real-time alerts when deviations from established compliance protocols are detected. Behavioral deviation alerts system 116 works in tandem with the cognitive process analyzer 104 to identify risky behaviors and notify compliance officers. It also integrates with the Real-time monitoring dashboard 110 to provide visual and real-time alerts for quick intervention.

[00038] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with scenario-based compliance simulation feature 118, which allows organizations to simulate various compliance strategies and regulatory changes. Scenario-based compliance simulation feature 118 interacts with the decision analysis engine 106 to forecast the outcomes of different compliance decisions. It helps organizations prepare for regulatory shifts by offering predictive scenarios.

[00039] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with cognitive pattern recognition module 120, which uses advanced AI algorithms to detect subtle deviations in decision-making behaviors that could lead to non-compliance. Cognitive pattern recognition module 120 works closely with the cognitive process analyzer 104 to identify emerging risks that might not be immediately evident. This component enhances the predictive accuracy of the AI-Based predictive compliance module 108.

[00040] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with Adaptive Decision Feedback Mechanism 122, which offers real-time feedback on the quality and outcomes of decisions based on past compliance performance. Adaptive Decision Feedback Mechanism 122 works in conjunction with the decision analysis engine 106 to continuously refine decision-making models. By analyzing past compliance outcomes, it helps improve future decisions and integrates with the AI-Based Predictive Compliance Module 108 to enhance predictive capabilities.

[00041] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with cross-industry regulatory updates integration 124, which automatically updates the system with real-time changes from various regulatory bodies. Cross-industry regulatory updates integration 124 ensures that the system remains aligned with the latest legal and regulatory frameworks. This component works with the continuous learning and adaptation module 114 to adjust compliance protocols based on new laws or amendments without manual intervention.

[00042] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with role-based access control for compliance actions 126, which dynamically adjusts decision-making access based on identified compliance risks. Role-based access control for compliance actions 126 interacts with the Cognitive Process Analyzer 104 to evaluate individual or departmental behavior and determine access privileges accordingly. It ensures that employees exhibiting risky behavior have limited access to critical compliance-related decisions.

[00043] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with multifactor risk scoring system 128, which assesses compliance risks using various factors such as decision complexity, time pressure, and behavioral history. Multifactor risk scoring system 128 integrates with both the decision analysis engine 106 and cognitive process analyzer 104 to provide a more nuanced understanding of compliance risks. This component enables more precise risk assessments, factoring in cognitive data alongside traditional risk models.

[00044] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with behavioral audit trails 130, which generates detailed records of the cognitive and decision-making processes that lead to compliance or non-compliance. Behavioral audit trails 130 works closely with the cognitive process analyzer 104 and automated reporting and auditing module 112 to ensure transparent, traceable audit records. These trails help regulatory bodies or internal auditors understand the reasoning behind specific compliance decisions.

[00045] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with customizable cognitive compliance profiles 132, which allows organizations to create tailored compliance profiles based on individual or departmental decision-making patterns. Customizable cognitive compliance profiles 132 works with the Cognitive Process Analyzer 104 to analyze behavior and develop personalized compliance protocols. This component ensures that compliance tracking is more targeted, addressing specific risks at different organizational levels.

[00046] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with self-learning compliance enforcement rules 134, which updates and creates new compliance enforcement rules based on evolving cognitive and decision data. Self-learning compliance enforcement rules 134 works alongside the continuous learning and adaptation module 114 to ensure that the system adapts to new behaviors and regulatory changes without manual intervention. This feature helps keep the compliance framework agile and up-to-date.

[00047] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with dynamic compliance reporting customization 136, which allows organizations to generate compliance reports tailored to specific regulatory requirements and internal compliance needs. dynamic compliance reporting customization 136 integrates with the automated reporting and auditing module 112 and real-time monitoring dashboard 110 to provide context-specific reporting options. This feature enhances the flexibility and relevance of compliance documentation.

[00048] Referring to Fig. 1, advanced compliance tracking system with cognitive process data and decision analysis 100 is provided with AI-Driven Compliance Training Recommendations 138, which generates tailored training recommendations based on decision-making behaviors and historical compliance performance. AI-Driven Compliance Training Recommendations 138 works with the Cognitive Process Analyzer 104 to identify areas where individuals or teams may require additional training. It offers targeted interventions that aim to improve compliance behaviors and reduce future violations

[00049] Referring to Fig 2, there is illustrated method 200 for advanced compliance tracking system with cognitive process data and decision analysis 100. The method comprises:

At step 202, method 200 includes the system ingesting data through the data ingestion module 102 from internal and external sources such as regulatory databases, employee decision logs, and communication records;

At step 204, method 200 includes the system analyzing the decision-making patterns using the cognitive process analyzer 104, identifying deviations from established compliance guidelines and protocols;

At step 206, method 200 includes the system evaluating the decision outcomes with the decision analysis engine 106, assessing the potential risks and consequences of the decision paths taken;

At step 208, method 200 includes the system predicting potential compliance violations using the AI-based predictive compliance module 108, based on historical data and decision-making patterns;

At step 210, method 200 includes the system displaying real-time compliance metrics, risk scores, and cognitive deviations on the real-time monitoring dashboard 110, enabling compliance officers to oversee the current compliance status;

At step 212, method 200 includes the system automatically generating compliance reports and audit documentation through the automated reporting and auditing module 112, based on real-time and predictive compliance data;

At step 214, method 200 includes the system continuously updating machine learning models through the continuous learning and adaptation module 114, ensuring the system evolves with new compliance data and regulatory update;

At step 216, method 200 includes the system triggering real-time alerts through the behavioral deviation alerts system 116 when deviations from compliance protocols are detected, prompting immediate intervention by compliance officers;

At step 218, method 200 includes the system simulating compliance strategies using the scenario-based compliance simulation feature 118 to forecast how various decisions will impact future compliance outcomes;

At step 220, method 200 includes the system using the cognitive pattern recognition module 120 to detect emerging patterns in decision-making that may lead to non-compliance, ensuring proactive risk detection;

At step 222, method 200 includes the system providing real-time feedback to decision-makers via the adaptive decision feedback mechanism 122, helping refine decision-making in compliance-related situations;

At step 224, method 200 includes the system integrating real-time regulatory updates through the cross-industry regulatory updates integration 124, ensuring that compliance parameters stay aligned with the latest legal requirements;

At step 226, method 200 includes the system dynamically adjusting access control based on risk evaluations using the role-based access control for compliance actions 126, limiting decision-making privileges for high-risk individuals;

At step 228, method 200 includes the system calculating compliance risk scores through the multifactor risk scoring system 128, incorporating decision complexity, behavioral history, and cognitive inputs for more accurate risk assessment;

At step 230, method 200 includes the system generating detailed behavioral audit trails via the behavioral audit trails 130, tracking cognitive and decision-making processes for later review and auditing purposes;

At step 232, method 200 includes the system creating and managing customizable compliance profiles using the customizable cognitive compliance profiles 132, tailoring compliance monitoring to specific departments, teams, or individuals;

At step 234, method 200 includes the system updating and creating enforcement rules through the self-learning compliance enforcement rules 134, automatically adapting to new data and behavior patterns to improve compliance enforcement;

At step 236, method 200 includes the system customizing compliance reports based on organizational needs using the dynamic compliance reporting customization 136, tailoring reporting to specific regulations and internal requirements;

At step 238, method 200 includes the system generating AI-driven training recommendations through the AI-driven compliance training recommendations 138, offering tailored training programs to improve decision-making and reduce compliance risks in the future.


[00050] In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "fixed" "attached" "disposed," "mounted," and "connected" are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.

[00051] Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a non- exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.

[00052] Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.

, C , Claims:
1. An advanced compliance tracking system with cognitive process data and decision analysis 100 comprising of
data ingestion module 102 to collect structured and unstructured data from various sources;
cognitive process analyzer 104 to analyze decision-making behaviors and identify deviations from compliance protocols;
decision analysis engine 106 to evaluate decision outcomes and assess compliance risks;
AI-based predictive compliance module 108 to forecast potential compliance violations based on historical data;
real-time monitoring dashboard 110 to display compliance metrics and risk scores for real-time oversight;
automated reporting and auditing module 112 to generate compliance reports and automate audit documentation;
continuous learning and adaptation module 114 to update machine learning models with new compliance data;
behavioral deviation alerts system 116 to trigger alerts when deviations from compliance protocols are detected;
scenario-based compliance simulation feature 118 to simulate compliance strategies and forecast outcomes;
cognitive pattern recognition module 120 to detect patterns in decision-making that may lead to non-compliance;
adaptive decision feedback mechanism 122 to provide real-time feedback on decision-making quality;
cross-industry regulatory updates integration 124 to update compliance parameters based on real-time regulatory changes;
role-based access control for compliance actions 126 to dynamically adjust decision-making access based on risk evaluations;
multifactor risk scoring system 128 to calculate compliance risk scores using decision complexity and cognitive inputs;
behavioral audit trails 130 to track and document the cognitive processes leading to compliance or non-compliance;
customizable cognitive compliance profiles 132 to tailor compliance monitoring for different departments or individuals;
self-learning compliance enforcement rules 134 to automatically adapt enforcement rules based on new data; and
dynamic compliance reporting customization 136 to customize compliance reports based on organizational needs;
AI-driven compliance training recommendations 138 to generate personalized training programs based on decision-making patterns

2. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein data ingestion module 102 is configured to collect structured and unstructured data from internal and external sources, including regulatory databases, decision logs, and communication records, enabling continuous data flow for compliance monitoring.

3. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein cognitive process analyzer 104 is configured to analyze decision-making behaviours and detect deviations from established compliance protocols thus providing real-time insights into behavioural trends and potential compliance risks.

4. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein decision analysis engine 106 is configured to evaluate decision outcomes using risk models, decision trees, and probability analysis, providing comprehensive risk assessments and compliance evaluation in real-time.

5. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein AI-based predictive compliance module 108 is configured to predict potential compliance violations using machine learning models trained on historical data and decision patterns, enabling proactive risk mitigation before violations occur.

6. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein real-time monitoring dashboard 110 is configured to display real-time compliance metrics, cognitive deviations, and predictive risk scores, allowing compliance officers to monitor the organization's compliance status with enhanced visibility.

7. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein automated reporting and auditing module 112 is configured to generate compliance reports and audit documentation automatically, ensuring that reports are based on real-time data and predictive insights, reducing manual oversight.

8. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein behavioral deviation alerts system 116 is configured to trigger real-time alerts when deviations from compliance protocols or decision-making patterns are detected.

9. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein continuous learning and adaptation module 114 is configured to continuously update machine learning models and compliance algorithms with new data, ensuring that the system adapts to evolving regulations and organizational behaviors over time.

10. The advanced compliance tracking system with cognitive process data and decision analysis 100 as claimed in claim 1, wherein method comprises of

data ingestion module 102 ingesting data from internal and external sources such as regulatory databases, employee decision logs, and communication records;

cognitive process analyzer 104 analyzing decision-making patterns, identifying deviations from established compliance guidelines and protocols;

decision analysis engine 106 evaluating decision outcomes, assessing the potential risks and consequences of the decision paths taken;

ai-based predictive compliance module 108 predicting potential compliance violations based on historical data and decision-making patterns;

real-time monitoring dashboard 110 displaying real-time compliance metrics, risk scores, and cognitive deviations, enabling compliance officers to oversee the current compliance status;

automated reporting and auditing module 112 automatically generating compliance reports and audit documentation based on real-time and predictive compliance data;

continuous learning and adaptation module 114 continuously updating machine learning models, ensuring the system evolves with new compliance data and regulatory updates;

behavioral deviation alerts system 116 triggering real-time alerts when deviations from compliance protocols are detected, prompting immediate intervention by compliance officers;

scenario-based compliance simulation feature 118 simulating compliance strategies to forecast how various decisions will impact future compliance outcomes;

cognitive pattern recognition module 120 detecting emerging patterns in decision-making that may lead to non-compliance, ensuring proactive risk detection;

adaptive decision feedback mechanism 122 providing real-time feedback to decision-makers, helping refine decision-making in compliance-related situations;

cross-industry regulatory updates integration 124 integrating real-time regulatory updates, ensuring that compliance parameters stay aligned with the latest legal requirements;

role-based access control for compliance actions 126 dynamically adjusting access control based on risk evaluations, limiting decision-making privileges for high-risk individuals;

multifactor risk scoring system 128 calculating compliance risk scores, incorporating decision complexity, behavioural history, and cognitive inputs for more accurate risk assessment;

behavioural audit trails 130 generating detailed behavioural audit trails, tracking cognitive and decision-making processes for later review and auditing purposes;

customizable cognitive compliance profiles 132 creating and managing customizable compliance profiles, tailoring compliance monitoring to specific departments, teams, or individuals;

self-learning compliance enforcement rules 134 updating and creating enforcement rules, automatically adapting to new data and behaviour patterns to improve compliance enforcement;

dynamic compliance reporting customization 136 customizing compliance reports based on organizational needs, tailoring reporting to specific regulations and internal requirements;

AI-driven compliance training recommendations 138 generating AI-driven training recommendations, offering tailored training programs to improve decision-making and reduce compliance risks in the future.

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