Transforming Healthcare through Artificial Intelligence & Robotics

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Transforming Healthcare through Artificial Intelligence & Robotics

Over the past few decades, Artificial Intelligence (AI) has played a vigorous role in transforming our world. Especially today, AI presents itself in many different forms and influences our daily life. It is incontestable, that the potential of AI and robotics is nearly endless, opening up new doors for a vast array of industries. Inevitably, Healthcare is one of the latter. Technology allows for more accurate, systematic, and impactful interventions in patient care. Artificial Intelligence is expected to drive the changes and improvements towards healthcare excellence, by truly augmenting human activity.

Applications and Benefits of AI and Robotics in Healthcare

AI has become extremely sophisticated at doing what humans have been traditionally doing. What’s more, it’s incomparably time-efficient and cost-effective. It lays the ground for proactive health management and encourages an appropriate lifestyle for well-being. Although the applications of AI and Robotics in healthcare are vast, we list just a few of them below:

  • Self-Care, Prevention, and Healthy Lifestyle – Contemporary patients are becoming increasingly empowered to take care of their health and well-being. Starting from numerous healthcare applications all the way to sleep trackers and blood pressure measurers, AI-based solutions are able to provide personalized plans and guidance. They can track and process greater amounts of data and gain insights into care processes.
  • Improving Healthcare Operations – With the Help of AI, operations such as scheduling, hospital admissions, discharge, and capacity management become simplified.
  • Diagnosis – Many AI-based technologies can help triage patients and detect whether the symptoms present require additional attention. In turn, it creates a positive trend for the patients to appear at hospitals and emergency rooms only when essential.
  • Early Detection and Diagnostics – AI solutions suggest effective ways for improving early detection mechanisms and timely diagnosis along with its accuracy. This is due to strengthened pattern recognition abilities that can have significant clinical implications.
  • Decision-Making Support – AI can present a patient’s medical information in a well-structured way, that allows healthcare professionals to select the appropriate treatment option. Such facilitation results in a time-effective and evidence-based decision-making process.
  • Care Assistance – Contemporary robots and machines can refill stocks, take appropriate notes, and retrieve medical records if needed. These technologies can as well be of great help while monitoring the patient’s condition. 
  • Innovation Support – along with the clinical practice, AI can successfully support research and development activities.
  • Expanding access to healthcare – AI and Robotics could help fill the shortages of healthcare workers, especially in underserved or developing regions. E.g. AI imaging tools can screen chest x-rays for signs of tuberculosis, often achieving a level of accuracy comparable to humans.
  • Lowering the Burden of Record Use – AI can facilitate the process of receiving routine requests from the inbox, including medication refills and result notifications. It can help prioritize tasks that truly require the clinician’s attention, allowing the users to work through their to-do lists. In addition, Voice recognition and dictation can accelerate the clinical documentation process.
  • Prediction and Management of Patient Risks – AI can extract and analyze the abundance of patient data in an accurate, timely, and reliable manner. This makes patient risk assessment and management way easier.

What are the challenges with AI applications in Healthcare?

The main challenge with AI application in healthcare is reliable and relevant data. AI solutions are just as good as the data they base decisions on. Typically, in healthcare, the data is fragmented across various systems and in multiple formats. Such a fragmentation can increase the risk of errors and decreases the comprehensiveness of the datasets. In addition, AI systems might become biased on the data they are being trained on.

Furthermore, there are ongoing privacy concerns related to AI incorporation in the healthcare industry. Some patients have worries regarding their privacy being violated. This assumption becomes even more sizeable due to AI’s ability to predict the private information of the patient without the algorithm ever having received it.

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Risk-Based Pension Funds Supervision & Effective Governance Course in Amsterdam

Program Overview

Private Pensions are becoming an increasingly important part of retirement income. Therefore, the quality and the effectiveness of pension funds supervision is getting more and more critical, as well as challenging. In order to achieve effective supervision, supervisory authorities need to expand risk analysis and develop emerging risk capacities. Thus, risk-based supervision (RBS) is imperative to be adopted along with corresponding risk-assessment methodology, that incorporates both micro and macro perspectives.

Strategically selected RBS techniques can result in effective resource allocation, where assets are directed in a way to target the risk exposures that are of greatest concern to the supervisory authority. Hence, RBS is deemed to be a more flexible and dynamic process, that allows for greater efficiency in the event of resource scarcity.

This program has been specifically designed by Risalat Consultants Int’l. to equip its participants with in-depth knowledge and essential skills to successfully employ RBS techniques.

Target Audience

Risk-Based Pension Funds Supervision and Effective Governance Training Course in Amsterdam, Netherlands is the best suit for:

  • Professionals and Executives involved in Pension Fund Supervision and Governance
  • Specialists and Policy Makers involved in risk identification, assessment, and management
  • Legal and Financial Advisors concerned with Pension Risks and related disputes
  • BPO Pension Scheme Administrators
  • Public Sector Pension Scheme Legislators and Officials at the local and national level
  • Pension Managers and Pension Scheme Managers
  • Pension Officers and Registrars
  • Employee Benefits Directors and Managers
  • Anyone interested in Risk-Based Pension Fund Supervision and Governance.

Program Objectives

Upon the Successful Completion of this program, delegates will:

  • Possess Comprehensive Understanding of Pensions Schemes, Funds and Plans Worldwide
  • Compare and employ global best practices of risk-based pension fund supervision and good governance
  • Develop sound decision-making skills for strategic resource allocation and supervisory guidance
  • Cross-train other pension professionals in risk-based pension fund supervision strategies
  • Employ Various Risk techniques for pension fund risk management
  • Set appropriate controls and measures against identified risks
  • Analyze various situations and circumstances and foresee possible outcomes
  • Effectively and Efficiently handle and manage senior roles and responsibilities related to risk-based pension fund supervision and stay relevant and competitive for the industry.

Program Contents

Day 1 – Risks and Regulations for Pension Industry
  • The Broad categorization of Pension Industry Risks: Portfolio, Agency and Systemic Risks
  • Introduction to Pension Fund Regulatory Mechanism
  • Regulatory Requirements on Risk Management Architecture
  • Licensing, Governance, and Investment Rules
  • Independent Custodian, External Audits, and Disclosure Requirements
  • Guarantees, Minimum Capital, and Reserves
  • Cost & Fee Regulation and Sanctions
Day 2 – Introduction to Risk-Based Supervision of Pension Funds
  • The Financial Position of the Organization, Risk Level Intensity, and Supervision Scope
  • Shifting the focus to high-level controls and governance
  • Strategic Allocation of Time and Resources: Employing Proactive Approach
  • Common Objectives and Elements of Pension Fund RBS Design
  • Key focus areas of RBS Models
  • Employing Pension Fund RBS – Application and Adaptation of Models
  • Collecting Data
  • Supervisory Board, Staff, Industry, and Power
Day 3 – Analyzing Risk Landscape
  • Risk-Based Solvency and Risk Scoring Methods
  • Risk-Based Capital Rules
  • Funding risk
  • Solvency risk
  • Surplus risk and contribution risk
  • Counterparty credit risk
  • Interest rate mismatch risk
  • Longevity Risk Hedging and Transfers
  • Systemic Risks and Achievability
Day 4 – Actionable Tools of RBS
  • Setting objectives and risk focus for supervisory authorities
  • Identifying, Mapping, and Weighting Risks
  • Resource Allocation Decision based on risk assessment
  • Quality Assurance
  • Maximizing the value of scarce resources
  • Foreseeing problems timely
  • Challenges in Pension Fund RBS implementation
Day 5 – Managing and Mitigating Risks
  • Operation and structure of internal risk governance processes
  • Considering Risk-Based approach in organizational structure
  • Management Controls and Compliance
  • Setting Appropriate Procedures and Controls
  • Designing and Adopting Risk Management Systems
  • Independent Reviews
  • Sponsors and Financial Support.

Program Methodology

An action-oriented, highly participative approach will be employed throughout the course, with particular attention paid to sharing the international experience with a view to adaptation and practical application. To enhance participant understanding the presenter will focus on numerous practical exercises, scenario imitations, and open discussions. Furthermore, Delegate Knowledge will be reinforced through Q&A Sessions, quizzes, virtual simulations, and integrative case studies. Each day will be finalized with attendee feedback to improve the performance of the coming sessions and support the unique requirements of each participant.

Registration Information

Program Name: Risk-Based Pension Funds Supervision and Effective Governance Training Course in Amsterdam, Netherlands

Program Code: PFS021

Program Dates: 22 - 26 March 2021

Registration Closes on: 31 January 2021 

Venue: Fletcher Hotel Amsterdam

Program Fee: $4950

Fee Covers: Visa Assistance (complementary), Participant Assessment, Airport Pickup, Accommodation, Wi-Fi, Breakfast, Workshop Kit, Interactive workshop, Program Materials, Local Expert, Practical Activities, Lunch, Refreshments, City Map, Field Visit, Certificate & Entertaining Tour.

Register Online  

Online Payment via PayPal


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