SHE Level 5
SCQF Credit Points 15.00
ECTS Credit Points 7.50
Module Code MMN225366
Module Leader Madhusudan Acharyya
School School of Computing, Engineering and Built Environment
Subject GCU London
  • A (September start)
  • B (January start)
  • C (May start)

Summary of Content

The aim of this module is to provide both theoretical and practical foundation of insurance and cyber insurance. It deals with the process of digitalising insurance functions and operations. The impact of automation on insurance business are discussed in both opportunity and threat perspective. At a broader level the contents elaborately discuss how digitalisation of insurance business contributes to social welfare which is regarded as the core aim of the insurance business. The use of big data, application of artificial intelligence and blockchain technology in insurance underwriting and claims handling are discussed. In addition, the characteristics issues related to pricing cyber insurance products are covered. The capital charge of cyber risk for potential scenarios are also included in the contents.


-360 1. Institutional theory, IT governance and insurance company business operating model 2. Theoretical framework for financial institutions process design, automation and its impact on insurer efficiency and growth strategies 3. Historical development of insurance digitalisation, digitalisation processes and strategies for insurers' core functions 4. Insurance e-commerce models, applications, strategies and cross-border regulatory issues for the online distribution of insurance products and IT security 5. Design modes and the application of artificial intelligence and blockchain technology in insurance business 6. Development of big data ecosystem and management for insurance analytics 7. Building predictive insurance data analytics models (underwriting, health risk models, claims management, longevity models) 8. Theoretical framework underpinning quality and efficiency oriented insurance business processes and work flow integration of analytics decision making tools and adoption management 9. The role and use of big data analytics in optimising customer interactions and employee behaviour 10. Assessment, quantification and capital charge for insurers IT and Operations Technology Security risk 11. Managing insurers IT and Cyber Security risk within the scope of the enterprise risk management framework 12. Perceptions of Corporate Cyber Risks, Business Continuity Management and Insurance Solutions

Learning Outcomes

Upon successful completion of the module, students should be able to:-1) Evaluate the evolution of ecommerce strategy and digitalisation of insurance business processes [CW1]2) Understanding both theoretical and practical features of advanced analytics and deep machine learning in insurance [CW1]3) Evaluate the role of big data on the human aspects of underwriting complex risks [CW1, CW2]4) Understand the application of artificial intelligence in the field of digital transformation of insurance services and products [CW1]5) Evaluate the insurance perspective of data protection regulations from an international context [CW1, CW2]6) Evaluate the strategic risks arising from technological sophistication and developments [CW1]7) Understand and evaluate the application, challenges and opportunities of blockchain technology in insurance [CW1, CW2]8) Evaluate the characteristics and impact of cyber risk for insurance business [CW2]9) Evaluate insurance solutions for cyber risk and limitations to the insurability of these risks [CW2]10) Evaluate the issues related to pricing cyber risk insurance products [CW2]

Teaching / Learning Strategy

The learning and teaching strategy uses a blended approach of lectures, tutorials, labs and directed learning supported by GCU Learn. Lectures will be used to highlight the key issues in a specific topic and point the way towards relevant journal articles and other appropriate literature. Students are expected to prepare for following week's lectures on each topic by engaging in literature searches, undertaking relevant reading and where necessary, attempt computational questions. Every student will receive a comprehensive study guide in the form of a module handbook. The lectures will adopt a variety of teaching styles including seminar style contributions such as group discussions to enhance intellectual, critical and analytical skills. For more applied topics, students will be required to attempt relevant problem or scenario based questions prior to the lectures, providing the basis for deepening professional skills, knowledge and understanding. The lab sessions will provide the medium for gaining practical skills through the use of spreadsheets to explore the lecture themes in more detail. Spreadsheet solutions and solutions to quantitative questions will be available on GCULearn. All students will be directed to further reading to support the theoretical and practical content of the module.

Indicative Reading

Boobier, T. (2016) Analytics for Insurance: The Real Business of Big Data", Wiley Finance Series, Chichester, West Sussex Nicoletti, B. (2016) "Digital Insurance: Business Innovation in the Post-Crisis Era", Palgrave Macmillan, Basingstoke Naylor, M. (2017) "Insurance Transformed: Technological Disruption", Palgrave Studies in Financial Services Technology Series Marano, P., Rokas, I., and Kochenburger, P. ed., (2016). "The 'Dematerialized' Insurance: Distance Selling and Cyber Risks from an International Perspective", Springer Freund, J. and Jones, J. (2014) "Measuring and Managing Information Risk: A FAIR Approach", Butterworth-Heinemann Newspapers and Magazines: McKinsey at <> Insurance Journal at <> Business Insurance at <> Best's Review at <> Newsweek Global at <javascript:__doLinkPostBack('','target~~URL||||type~~','');> Claims at <javascript:__doLinkPostBack('','target~~URL||||type~~','');> The Journal [official magazine of the Chartered Insurance Institute] Insurance Advocate at <javascript:__doLinkPostBack('','target~~URL||||type~~','');> Risk Management at <javascript:__doLinkPostBack('','target~~URL||||type~~','');> Financial Times at <> The Wall Street Journal at <> The Insurance Times at <> Journals: Journal of Insurance Regulation European Journal of Risk Regulation Geneva Papers on Risk and Insurance - Issues and Practice Asia-Pacific Journal of Risk and Insurance Journal of Risk and Insurance Journal of Risk and Uncertainty Risk Management and Insurance Review Risk Analysis: An International Journal Journal of Insurance Issues British Actuarial Journal Internet sites National Institute of Standard and Technology (NIST) at <> Breach Level Index at <> Ponemon Institute at <> National Cyber Security Centre at <> Geneva Association at <> European Insurance and Occupational Pensions Authority (EIOPA) at <> International Association of Insurance Supervisors (IAIS) at Bank of England at <> Financial Conduct Authority (FCA) <> Association of British Insurers (ABI) at <> Chartered Insurance Institute (CII) <> The Insurance Institute of London at <> Insurance Information Institute at <> CRO Forum <> Database for Research: A M Best Breach Level Index at <> Ponemon Institute at <> Insurance Intelligence Centre GlobalData Thomson Reuters DataStream and EIKON

Transferrable Skills

This module will develop the following skills in a manner that encourages independent initiative and critical thinking: -360b7 Personal and interpersonal skills -360b7 Oral and written communication skills b7 Data gathering, analysis and interpretation b7 Use of Excel and Models for data analysis b7 Problem solving and critical thinking b7 Ability to work independently b7 Research skills in order to complete the courseworks As a part of the broader transferable skills students will be able to demonstrate: -360 1. Advanced knowledge in the subject area. 2. Advanced usage of computers and associated software as a learning tool to explore models, ideas and for problem solving.

Module Structure

Activity Total Hours
Lectures (FT) 24.00
Tutorials (FT) 2.00
Assessment (FT) 40.00
Independent Learning (FT) 72.00
Seminars (FT) 12.00

Assessment Methods

Component Duration Weighting Threshold Description
Course Work 01 n/a 30.00 45% 2 hours MCQ type online Class Test [individual submission both on campus and distance learning students]
Course Work 02 n/a 70.00 45% 3,000 words of written analytical report [individual submission for both on-campus and distance learning students]