Insurtech (a.k.a Digital Insurance) refers to the convergence of insurance + new technologies. In the field of Insurtech "digital insurers" apply technology innovations to their business and operating models in order to reduce costs, improve the customer experience and enhance the agility of their operations.

In this instructor-led training, participants will gain an understanding of the technologies, methods and mindset needed to bring about a digital transformation within their organizations and in the industry at large. The training is aimed at managers who need to gain a big picture understanding, break down the hype and jargon, and take the first steps in establishing an Insurtech strategy.

By the end of this training, participants will be able to:

• Discuss Insurtech and all its component parts intelligently and systematically
• Identify and demystify the role of each key technology within Insurtech.
• Draft a general strategy for implementing Insurtech within their organization

Audience

• Insurers
• Technologists within the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• Part lecture, part discussion, exercises and case study group activities

In this instructor-led, live training in the US, participants will gain an understanding of the technologies, methods and mindset needed to implement a Fintech strategy.

This training is aimed at managers who need to gain a "big picture" understanding of Fintech, break down the hype and jargon, and take tangible first steps towards the adoption of new technologies applicable to financial business and services.

By the end of this training, participants will be able to

• Present viable Fintech strategies for their organization.
• Understand and explain the role and functionality of key technologies.
• Draft an action plan for introducing new technologies in step-by-step fashion.

Prescriptive analytics is a branch of business analytics, together with descriptive and predictive analytics. It uses predictive models to suggest actions to take for optimal outcomes, relying on optimization and rules-based techniques as a basis for decision making.

In this instructor-led, live training, participants will learn how to use Matlab to carry out prescriptive analytics on a set of sample data.

By the end of this training, participants will be able to:

• Understand the key concepts and frameworks used in prescriptive analytics
• Use MATLAB and its toolboxes to acquire, clean and explore data
• Use rules-based techniques including inference engines, scorecards, and decision trees to make decisions based on different business scenarios
• Use Monte Carlo simulation to analyze uncertainties and ensure sound decision making
• Deploy predictive and prescriptive models to enterprise systems

Audience

• Business analysts
• Operations planners
• Functional managers
• BI (Business Intelligence) team members

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Model Based Development (MBD) is a software development methodology that enables faster, more cost-effective development of dynamic systems such as control systems, signal processing and communication systems. It relies on graphic modeling rather than the traditional text based programming.

In this instructor-led, live training participants will learn how to apply MBD methodologies to reduce development costs and accelerate the time to market of their embedded software products.

By the end of this training, participants will be able to

• Select and utilize the right tools for implementing MBD.
• Use MBD to carry out rapid development in the early stages of their embedded software project.
• Shorten the release of their embedded software into the market.

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

This instructor-led, live training in the US (online or onsite) is aimed at persons who wish to understand requirements analysis and conduct requirements analysis efficiently and accurately using analysis techniques for their projects.

By the end of this training, participants will be able to:

• identify different types of requirements.
• understand the overall concepts of, and activities within, requirements analysis.
• be familiar with the requirements analysis methodology.
• use different requirements analysis techniques to their advantage.
• structure requirements in order to communicate efficiently with architects and developers through an iterative requirement gathering process.

This course demonstrates through hands-on practice the fundamentals and applications of software engineering, requirements engineering and testing.

Process mining, or Automated Business Process Discovery (ABPD), is a technique that applies algorithms to event logs for the purpose of analyzing business processes. Process mining goes beyond data storage and data analysis; it bridges data with processes and provides insights into the trends and patterns that affect process efficiency. 

Format of the Course

• The course starts with an overview of the most commonly used techniques for process mining. We discuss the various process discovery algorithms and tools used for discovering and modeling processes based on raw event data. Real-life case studies are examined and data sets are analyzed using the ProM open-source framework.

Excel is a versatile tool that has been widely used in various areas, from data analysis to project management. Its flexibility and ease of use make it a popular tool for working with data and analysis in many fields. Excel allows you to create spreadsheets in which you can enter data, calculate formulas, analyze data and present results in the form of tables, charts or reports. It has a rich set of built-in mathematical, statistical and financial functions that facilitate calculations and data analysis. It allows you to generate various types of charts (e.g. bar, line, pie) based on data from the spreadsheet, which helps you visualize and present data. Excel offers tools for sorting, filtering, grouping data, as well as creating pivot tables and preliminary data analysis. It is used in business for budgeting, planning, tracking expenses, analyzing sales, creating financial reports, etc. It can be used to create schedules, project plans, manage tasks, and track progress.

Business analysis is the process of examining, understanding, and defining business needs in order to develop solutions that meet those needs. Jest a key element in the process of managing changes in the organization and designing new business solutions. Business analysis aims to ensure that technological, process or organizational solutions meet business goals and needs. Jest a key element in ensuring the effectiveness of projects and changes in the organization, by ensuring that the solutions introduced are accurate, feasible and fully meet business requirements.