Unlock the Power of Conflicts of Interest in Data Mining with Our Knowledge Base!
Are you tired of spending hours searching for the most relevant and urgent questions to ask when it comes to conflicts of interest in data mining? Look no further!
Our Conflicts of Interest in Data Mining Knowledge Base is here to provide you with a comprehensive and prioritized list of 1508 requirements, solutions, benefits, and results.
With our dataset, you will have access to the most essential and vital information about conflicts of interest in data mining.
No more wasting time sifting through irrelevant or outdated resources.
Our knowledge base is constantly updated to ensure that you are equipped with the most current and effective strategies for handling conflicts of interest in data mining.
But what sets us apart from the competition? Our dataset not only offers extensive and prioritized information, but also includes real-life case studies and use cases, giving you a practical and tangible understanding of how conflicts of interest in data mining can impact your business.
Our product is tailored for professionals looking to stay one step ahead in the rapidly evolving world of data mining.
Whether you are an experienced practitioner or new to the field, our knowledge base is the perfect tool to enhance your skills and expertise.
And don′t worry, our product is not just limited to large corporations with hefty budgets.
It is an affordable and DIY alternative, making it accessible to businesses of all sizes.
Our Conflicts of Interest in Data Mining Knowledge Base is easy to use, providing you with a clear and detailed overview of specifications and product details.
It also offers a comparison with similar products, highlighting its superior features and benefits.
Speaking of benefits, our dataset offers more than just a list of requirements.
It provides insights and techniques to help streamline your data mining process, ultimately saving you time and resources.
This translates into increased efficiency and improved results for your business.
But don′t just take our word for it, our product has been researched and tested by professionals in the field of data mining.
They have seen firsthand how our knowledge base has positively impacted their businesses, making it a highly valuable asset.
And let′s not forget about potential conflicts of interest in data mining for businesses.
Our dataset arms you with the necessary tools to identify, manage, and prevent conflicts of interest, minimizing the risk of adverse effects on your company′s reputation and bottom line.
With all these benefits, you may be wondering about the cost.
But fear not, our product is affordable and offers a great return on investment when compared to alternative options.
In summary, our Conflicts of Interest in Data Mining Knowledge Base is a must-have for any business looking to stay ahead in the world of data mining.
It offers unparalleled insights and solutions, helping you tackle conflicts of interest with confidence.
So why wait? Get your hands on our product today and watch your business thrive!
How could financial analysis applications be used to identify possible conflicts of interest?
Conflicts of Interest
Financial analysis applications can detect patterns and inconsistencies in financial activity, potentially revealing conflicts of interest such as insider trading or biased investment recommendations.
1. Utilize data analytics to identify patterns in transaction records.
2. Apply machine learning algorithms to detect suspicious links and relationships between parties.
3. Utilize natural language processing techniques to analyze text data for potential conflicts.
4. Implement anomaly detection methods to identify unusual or fraudulent activities.
5. Use data visualization tools to identify and display potential conflicts of interest.
6. Utilize predictive models to forecast potential conflicts based on historical data.
7. Apply network analysis to identify interconnected relationships between parties.
8. Utilize data integration to combine financial data from multiple sources for comprehensive analysis.
9. Implement regular audits and reviews of financial data to identify any discrepancies or inconsistencies.
10. Utilize advanced analytics techniques, such as text mining, sentiment analysis, and social media monitoring, to gather additional data and insights.
CONTROL QUESTION: How could financial analysis applications be used to identify possible conflicts of interest?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
By 2030, Conflicts of Interest will revolutionize the financial industry by using advanced and innovative financial analysis applications to identify and prevent conflicts of interest in all aspects of financial transactions and investments.
Our applications will go beyond traditional risk assessment methods and utilize artificial intelligence and machine learning algorithms to actively detect potential conflicts of interest. This will include analyzing data from all parties involved in a transaction, including individuals, companies, and third-party entities.
Our goal is for Conflicts of Interest to become the industry standard for identifying and managing conflicts of interest, providing complete transparency and trust in financial transactions. We aim to eliminate any potential for biased or unethical practices, leading to greater accountability and integrity in the financial world.
Through our advanced technology and collaboration with industry experts and regulators, we will be able to prevent widespread financial scandals and breaches of trust, ultimately creating a more stable and trustworthy financial ecosystem for all stakeholders.
Ten years from now, Conflicts of Interest will have solidified its position as the go-to solution for identifying and managing conflicts of interest, setting a new standard for ethics and transparency in the financial industry. Our impact will be felt globally, instilling confidence in investors, businesses, and the general public, and setting a precedent for ethical practices in all financial transactions.
"I`ve been searching for a dataset that provides reliable prioritized recommendations, and I finally found it. The accuracy and depth of insights have exceeded my expectations. A must-have for professionals!"
Introduction
Conflicts of interest occur when an individual or organization is in a position where their personal interests may potentially conflict with their professional obligations. These conflicts can arise in a variety of situations, and if not identified and managed properly, they can lead to serious consequences such as legal and reputational damages. As the financial industry becomes increasingly complex and interconnected, conflicts of interest have become a growing concern for regulators, investors, and businesses alike.
In this case study, we will examine how financial analysis applications can be used to identify possible conflicts of interest within a large investment bank, XYZ Bank. We will analyze the client situation, explore the consulting methodology used, discuss the deliverables provided, and highlight the implementation challenges faced during the project. Additionally, we will outline the key performance indicators (KPIs) and other management considerations that were crucial in achieving the project′s objectives.
Client Situation
XYZ Bank is a leading global investment bank that offers a wide range of financial services, including investment banking, wealth management, and asset management. With operations spanning across multiple countries and sectors, the bank has a diverse portfolio of clients, including corporations, institutions, and high-net-worth individuals.
As part of its commitment to ensuring ethical and compliant business practices, XYZ Bank has a robust conflict of interest policy in place. However, the rapid growth of the bank′s operations and the evolving regulatory landscape have made it challenging to effectively monitor and manage potential conflicts of interest. The bank has historically relied on manual processes, which are time-consuming, error-prone, and lack the necessary data analysis capabilities.
To address this issue, the bank engaged a team of financial consultants to develop and implement a solution that would enable them to proactively identify and manage conflicts of interest. The aim was to improve compliance with regulations, enhance transparency, and strengthen stakeholder confidence in the bank′s business practices.
Consulting Methodology
The consulting team approached the project with a structured and data-driven methodology. The first step was to conduct a thorough review of the bank′s existing conflict of interest policy, regulatory requirements, and industry best practices. This provided a baseline understanding of the current state and identified any potential gaps that needed to be addressed.
Next, the consultants conducted interviews with key stakeholders, including senior management, compliance officers, and front-line staff. This helped to gain insights into the bank′s operations, identify potential areas of conflicts, and understand how conflicts were currently being managed.
The consultants then developed a comprehensive framework for identifying and managing conflicts of interest. This included a risk assessment process to rank and prioritize potential conflicts based on their likelihood and impact. The team also outlined the controls and procedures that would be necessary to prevent, manage, and disclose conflicts of interest.
Deliverables
Based on the framework developed, the consulting team designed and implemented a financial analysis application to identify potential conflicts of interest. This application utilized advanced data analytics and machine learning techniques to analyze large volumes of data from various sources, including transactions, financial statements, news, and social media.
The application was integrated with the bank′s existing data systems, allowing for real-time monitoring and analysis of potential conflicts. The consultants also designed dashboards and reports to provide timely and actionable insights to front-line staff and management. Additionally, the consulting team provided training to bank employees on how to use the application effectively.
Implementation Challenges
The major challenge faced during the implementation was the integration of different data sources from across the bank′s operations. This required collaboration and coordination between the consultants and the bank′s IT department to ensure data accuracy and integrity. The team also faced resistance from some employees who were apprehensive about the new technology and its impact on their day-to-day processes. Effective change management strategies were employed to address these challenges and ensure successful adoption of the new system.
KPIs and Management Considerations
The project′s success was measured against several key performance indicators, including the number of potential conflicts identified, the resolution time, and the compliance level with regulatory requirements. Within the first year of implementation, the number of potential conflicts identified increased by 60%, and the resolution time for conflicts decreased by 40%. Additionally, the bank achieved a 95% compliance rate with its conflict of interest policy.
Effective management of the project was critical to its success. The consulting team worked closely with the bank′s senior management and compliance officers to ensure buy-in and support for the project. Regular communication and progress updates were provided to keep stakeholders engaged and informed throughout the project′s duration.
Conclusion
In conclusion, financial analysis applications play a crucial role in identifying possible conflicts of interest within organizations. In this case, the application provided by the consulting team helped XYZ Bank to proactively manage potential conflicts, improve compliance with regulations, and enhance stakeholder trust. By following a structured methodology, delivering effective training, and addressing implementation challenges, the project achieved its objectives and provided long-term value to the bank.
Are you tired of spending hours searching for the most relevant and urgent questions to ask when it comes to conflicts of interest in data mining? Look no further!
Our Conflicts of Interest in Data Mining Knowledge Base is here to provide you with a comprehensive and prioritized list of 1508 requirements, solutions, benefits, and results.
With our dataset, you will have access to the most essential and vital information about conflicts of interest in data mining.
No more wasting time sifting through irrelevant or outdated resources.
Our knowledge base is constantly updated to ensure that you are equipped with the most current and effective strategies for handling conflicts of interest in data mining.
But what sets us apart from the competition? Our dataset not only offers extensive and prioritized information, but also includes real-life case studies and use cases, giving you a practical and tangible understanding of how conflicts of interest in data mining can impact your business.
Our product is tailored for professionals looking to stay one step ahead in the rapidly evolving world of data mining.
Whether you are an experienced practitioner or new to the field, our knowledge base is the perfect tool to enhance your skills and expertise.
And don′t worry, our product is not just limited to large corporations with hefty budgets.
It is an affordable and DIY alternative, making it accessible to businesses of all sizes.
Our Conflicts of Interest in Data Mining Knowledge Base is easy to use, providing you with a clear and detailed overview of specifications and product details.
It also offers a comparison with similar products, highlighting its superior features and benefits.
Speaking of benefits, our dataset offers more than just a list of requirements.
It provides insights and techniques to help streamline your data mining process, ultimately saving you time and resources.
This translates into increased efficiency and improved results for your business.
But don′t just take our word for it, our product has been researched and tested by professionals in the field of data mining.
They have seen firsthand how our knowledge base has positively impacted their businesses, making it a highly valuable asset.
And let′s not forget about potential conflicts of interest in data mining for businesses.
Our dataset arms you with the necessary tools to identify, manage, and prevent conflicts of interest, minimizing the risk of adverse effects on your company′s reputation and bottom line.
With all these benefits, you may be wondering about the cost.
But fear not, our product is affordable and offers a great return on investment when compared to alternative options.
In summary, our Conflicts of Interest in Data Mining Knowledge Base is a must-have for any business looking to stay ahead in the world of data mining.
It offers unparalleled insights and solutions, helping you tackle conflicts of interest with confidence.
So why wait? Get your hands on our product today and watch your business thrive!
Discover Insights, Make Informed Decisions, and Stay Ahead of the Curve:
Key Features:
Comprehensive set of 1508 prioritized Conflicts of Interest requirements. - Extensive coverage of 215 Conflicts of Interest topic scopes.
- In-depth analysis of 215 Conflicts of Interest step-by-step solutions, benefits, BHAGs.
- Detailed examination of 215 Conflicts of Interest case studies and use cases.
- Digital download upon purchase.
- Enjoy lifetime document updates included with your purchase.
- Benefit from a fully editable and customizable Excel format.
- Trusted and utilized by over 10,000 organizations.
- Covering: Speech Recognition, Debt Collection, Ensemble Learning, Data mining, Regression Analysis, Prescriptive Analytics, Opinion Mining, Plagiarism Detection, Problem-solving, Process Mining, Service Customization, Semantic Web, Conflicts of Interest, Genetic Programming, Network Security, Anomaly Detection, Hypothesis Testing, Machine Learning Pipeline, Binary Classification, Genome Analysis, Telecommunications Analytics, Process Standardization Techniques, Agile Methodologies, Fraud Risk Management, Time Series Forecasting, Clickstream Analysis, Feature Engineering, Neural Networks, Web Mining, Chemical Informatics, Marketing Analytics, Remote Workforce, Credit Risk Assessment, Financial Analytics, Process attributes, Expert Systems, Focus Strategy, Customer Profiling, Project Performance Metrics, Sensor Data Mining, Geospatial Analysis, Earthquake Prediction, Collaborative Filtering, Text Clustering, Evolutionary Optimization, Recommendation Systems, Information Extraction, Object Oriented Data Mining, Multi Task Learning, Logistic Regression, Analytical CRM, Inference Market, Emotion Recognition, Project Progress, Network Influence Analysis, Customer satisfaction analysis, Optimization Methods, Data compression, Statistical Disclosure Control, Privacy Preserving Data Mining, Spam Filtering, Text Mining, Predictive Modeling In Healthcare, Forecast Combination, Random Forests, Similarity Search, Online Anomaly Detection, Behavioral Modeling, Data Mining Packages, Classification Trees, Clustering Algorithms, Inclusive Environments, Precision Agriculture, Market Analysis, Deep Learning, Information Network Analysis, Machine Learning Techniques, Survival Analysis, Cluster Analysis, At The End Of Line, Unfolding Analysis, Latent Process, Decision Trees, Data Cleaning, Automated Machine Learning, Attribute Selection, Social Network Analysis, Data Warehouse, Data Imputation, Drug Discovery, Case Based Reasoning, Recommender Systems, Semantic Data Mining, Topology Discovery, Marketing Segmentation, Temporal Data Visualization, Supervised Learning, Model Selection, Marketing Automation, Technology Strategies, Customer Analytics, Data Integration, Process performance models, Online Analytical Processing, Asset Inventory, Behavior Recognition, IoT Analytics, Entity Resolution, Market Basket Analysis, Forecast Errors, Segmentation Techniques, Emotion Detection, Sentiment Classification, Social Media Analytics, Data Governance Frameworks, Predictive Analytics, Evolutionary Search, Virtual Keyboard, Machine Learning, Feature Selection, Performance Alignment, Online Learning, Data Sampling, Data Lake, Social Media Monitoring, Package Management, Genetic Algorithms, Knowledge Transfer, Customer Segmentation, Memory Based Learning, Sentiment Trend Analysis, Decision Support Systems, Data Disparities, Healthcare Analytics, Timing Constraints, Predictive Maintenance, Network Evolution Analysis, Process Combination, Advanced Analytics, Big Data, Decision Forests, Outlier Detection, Product Recommendations, Face Recognition, Product Demand, Trend Detection, Neuroimaging Analysis, Analysis Of Learning Data, Sentiment Analysis, Market Segmentation, Unsupervised Learning, Fraud Detection, Compensation Benefits, Payment Terms, Cohort Analysis, 3D Visualization, Data Preprocessing, Trip Analysis, Organizational Success, User Base, User Behavior Analysis, Bayesian Networks, Real Time Prediction, Business Intelligence, Natural Language Processing, Social Media Influence, Knowledge Discovery, Maintenance Activities, Data Mining In Education, Data Visualization, Data Driven Marketing Strategy, Data Accuracy, Association Rules, Customer Lifetime Value, Semi Supervised Learning, Lean Thinking, Revenue Management, Component Discovery, Artificial Intelligence, Time Series, Text Analytics In Data Mining, Forecast Reconciliation, Data Mining Techniques, Pattern Mining, Workflow Mining, Gini Index, Database Marketing, Transfer Learning, Behavioral Analytics, Entity Identification, Evolutionary Computation, Dimensionality Reduction, Code Null, Knowledge Representation, Customer Retention, Customer Churn, Statistical Learning, Behavioral Segmentation, Network Analysis, Ontology Learning, Semantic Annotation, Healthcare Prediction, Quality Improvement Analytics, Data Regulation, Image Recognition, Paired Learning, Investor Data, Query Optimization, Financial Fraud Detection, Sequence Prediction, Multi Label Classification, Automated Essay Scoring, Predictive Modeling, Categorical Data Mining, Privacy Impact Assessment
Conflicts of Interest Assessment Dataset - Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):
Conflicts of Interest
Financial analysis applications can detect patterns and inconsistencies in financial activity, potentially revealing conflicts of interest such as insider trading or biased investment recommendations.
1. Utilize data analytics to identify patterns in transaction records.
2. Apply machine learning algorithms to detect suspicious links and relationships between parties.
3. Utilize natural language processing techniques to analyze text data for potential conflicts.
4. Implement anomaly detection methods to identify unusual or fraudulent activities.
5. Use data visualization tools to identify and display potential conflicts of interest.
6. Utilize predictive models to forecast potential conflicts based on historical data.
7. Apply network analysis to identify interconnected relationships between parties.
8. Utilize data integration to combine financial data from multiple sources for comprehensive analysis.
9. Implement regular audits and reviews of financial data to identify any discrepancies or inconsistencies.
10. Utilize advanced analytics techniques, such as text mining, sentiment analysis, and social media monitoring, to gather additional data and insights.
CONTROL QUESTION: How could financial analysis applications be used to identify possible conflicts of interest?
Big Hairy Audacious Goal (BHAG) for 10 years from now:
By 2030, Conflicts of Interest will revolutionize the financial industry by using advanced and innovative financial analysis applications to identify and prevent conflicts of interest in all aspects of financial transactions and investments.
Our applications will go beyond traditional risk assessment methods and utilize artificial intelligence and machine learning algorithms to actively detect potential conflicts of interest. This will include analyzing data from all parties involved in a transaction, including individuals, companies, and third-party entities.
Our goal is for Conflicts of Interest to become the industry standard for identifying and managing conflicts of interest, providing complete transparency and trust in financial transactions. We aim to eliminate any potential for biased or unethical practices, leading to greater accountability and integrity in the financial world.
Through our advanced technology and collaboration with industry experts and regulators, we will be able to prevent widespread financial scandals and breaches of trust, ultimately creating a more stable and trustworthy financial ecosystem for all stakeholders.
Ten years from now, Conflicts of Interest will have solidified its position as the go-to solution for identifying and managing conflicts of interest, setting a new standard for ethics and transparency in the financial industry. Our impact will be felt globally, instilling confidence in investors, businesses, and the general public, and setting a precedent for ethical practices in all financial transactions.
Customer Testimonials:
"I`ve been searching for a dataset that provides reliable prioritized recommendations, and I finally found it. The accuracy and depth of insights have exceeded my expectations. A must-have for professionals!"
"I`ve been using this dataset for a few weeks now, and it has exceeded my expectations. The prioritized recommendations are backed by solid data, making it a reliable resource for decision-makers."
"The creators of this dataset did an excellent job curating and cleaning the data. It`s evident they put a lot of effort into ensuring its reliability. Thumbs up!"
Conflicts of Interest Case Study/Use Case example - How to use:
Introduction
Conflicts of interest occur when an individual or organization is in a position where their personal interests may potentially conflict with their professional obligations. These conflicts can arise in a variety of situations, and if not identified and managed properly, they can lead to serious consequences such as legal and reputational damages. As the financial industry becomes increasingly complex and interconnected, conflicts of interest have become a growing concern for regulators, investors, and businesses alike.
In this case study, we will examine how financial analysis applications can be used to identify possible conflicts of interest within a large investment bank, XYZ Bank. We will analyze the client situation, explore the consulting methodology used, discuss the deliverables provided, and highlight the implementation challenges faced during the project. Additionally, we will outline the key performance indicators (KPIs) and other management considerations that were crucial in achieving the project′s objectives.
Client Situation
XYZ Bank is a leading global investment bank that offers a wide range of financial services, including investment banking, wealth management, and asset management. With operations spanning across multiple countries and sectors, the bank has a diverse portfolio of clients, including corporations, institutions, and high-net-worth individuals.
As part of its commitment to ensuring ethical and compliant business practices, XYZ Bank has a robust conflict of interest policy in place. However, the rapid growth of the bank′s operations and the evolving regulatory landscape have made it challenging to effectively monitor and manage potential conflicts of interest. The bank has historically relied on manual processes, which are time-consuming, error-prone, and lack the necessary data analysis capabilities.
To address this issue, the bank engaged a team of financial consultants to develop and implement a solution that would enable them to proactively identify and manage conflicts of interest. The aim was to improve compliance with regulations, enhance transparency, and strengthen stakeholder confidence in the bank′s business practices.
Consulting Methodology
The consulting team approached the project with a structured and data-driven methodology. The first step was to conduct a thorough review of the bank′s existing conflict of interest policy, regulatory requirements, and industry best practices. This provided a baseline understanding of the current state and identified any potential gaps that needed to be addressed.
Next, the consultants conducted interviews with key stakeholders, including senior management, compliance officers, and front-line staff. This helped to gain insights into the bank′s operations, identify potential areas of conflicts, and understand how conflicts were currently being managed.
The consultants then developed a comprehensive framework for identifying and managing conflicts of interest. This included a risk assessment process to rank and prioritize potential conflicts based on their likelihood and impact. The team also outlined the controls and procedures that would be necessary to prevent, manage, and disclose conflicts of interest.
Deliverables
Based on the framework developed, the consulting team designed and implemented a financial analysis application to identify potential conflicts of interest. This application utilized advanced data analytics and machine learning techniques to analyze large volumes of data from various sources, including transactions, financial statements, news, and social media.
The application was integrated with the bank′s existing data systems, allowing for real-time monitoring and analysis of potential conflicts. The consultants also designed dashboards and reports to provide timely and actionable insights to front-line staff and management. Additionally, the consulting team provided training to bank employees on how to use the application effectively.
Implementation Challenges
The major challenge faced during the implementation was the integration of different data sources from across the bank′s operations. This required collaboration and coordination between the consultants and the bank′s IT department to ensure data accuracy and integrity. The team also faced resistance from some employees who were apprehensive about the new technology and its impact on their day-to-day processes. Effective change management strategies were employed to address these challenges and ensure successful adoption of the new system.
KPIs and Management Considerations
The project′s success was measured against several key performance indicators, including the number of potential conflicts identified, the resolution time, and the compliance level with regulatory requirements. Within the first year of implementation, the number of potential conflicts identified increased by 60%, and the resolution time for conflicts decreased by 40%. Additionally, the bank achieved a 95% compliance rate with its conflict of interest policy.
Effective management of the project was critical to its success. The consulting team worked closely with the bank′s senior management and compliance officers to ensure buy-in and support for the project. Regular communication and progress updates were provided to keep stakeholders engaged and informed throughout the project′s duration.
Conclusion
In conclusion, financial analysis applications play a crucial role in identifying possible conflicts of interest within organizations. In this case, the application provided by the consulting team helped XYZ Bank to proactively manage potential conflicts, improve compliance with regulations, and enhance stakeholder trust. By following a structured methodology, delivering effective training, and addressing implementation challenges, the project achieved its objectives and provided long-term value to the bank.
Security and Trust:
- Secure checkout with SSL encryption Visa, Mastercard, Apple Pay, Google Pay, Stripe, Paypal
- Money-back guarantee for 30 days
- Our team is available 24/7 to assist you - support@theartofservice.com
About the Authors: Unleashing Excellence: The Mastery of Service Accredited by the Scientific Community
Immerse yourself in the pinnacle of operational wisdom through The Art of Service`s Excellence, now distinguished with esteemed accreditation from the scientific community. With an impressive 1000+ citations, The Art of Service stands as a beacon of reliability and authority in the field.Our dedication to excellence is highlighted by meticulous scrutiny and validation from the scientific community, evidenced by the 1000+ citations spanning various disciplines. Each citation attests to the profound impact and scholarly recognition of The Art of Service`s contributions.
Embark on a journey of unparalleled expertise, fortified by a wealth of research and acknowledgment from scholars globally. Join the community that not only recognizes but endorses the brilliance encapsulated in The Art of Service`s Excellence. Enhance your understanding, strategy, and implementation with a resource acknowledged and embraced by the scientific community.
Embrace excellence. Embrace The Art of Service.
Your trust in us aligns you with prestigious company; boasting over 1000 academic citations, our work ranks in the top 1% of the most cited globally. Explore our scholarly contributions at: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=blokdyk
About The Art of Service:
Our clients seek confidence in making risk management and compliance decisions based on accurate data. However, navigating compliance can be complex, and sometimes, the unknowns are even more challenging.
We empathize with the frustrations of senior executives and business owners after decades in the industry. That`s why The Art of Service has developed Self-Assessment and implementation tools, trusted by over 100,000 professionals worldwide, empowering you to take control of your compliance assessments. With over 1000 academic citations, our work stands in the top 1% of the most cited globally, reflecting our commitment to helping businesses thrive.
Founders:
Gerard Blokdyk
LinkedIn: https://www.linkedin.com/in/gerardblokdijk/
Ivanka Menken
LinkedIn: https://www.linkedin.com/in/ivankamenken/
