Data Profiling and Insurance Law

The winner of the 2020 British Insurance Law Association Book Prize, this timely, expertly written book looks at the legal impact that the use of ‘Big Data’ will have on the provision – and substantive law – of insurance. Insurance companies are set to become some of the biggest consumers of big data which will enable them to profile prospective individual insureds at an increasingly granular level. More particularly, the book explores how: (i) insurers gain access to information relevant to assessing risk and/or the pricing of premiums; (ii) the impact which that increased information will have on substantive insurance law (and in particular duties of good faith disclosure and fair presentation of risk); and (iii) the impact that insurers’ new knowledge may have on individual and group access to insurance. This raises several consequential legal questions: (i) To what extent is the use of big data analytics to profile risk compatible (at least in the EU) with the General Data Protection Regulation? (ii) Does insurers’ ability to parse vast quantities of individual data about insureds invert the information asymmetry that has historically existed between insured and insurer such as to breathe life into insurers’ duty of good faith disclosure? And (iii) by what means might legal challenges be brought against insurers both in relation to the use of big data and the consequences it may have on access to cover? Written by a leading expert in the field, this book will both stimulate further debate and operate as a reference text for academics and practitioners who are faced with emerging legal problems arising from the increasing opportunities that big data offers to the insurance industry.

Table of Contents:
Introduction I. Scope and Structure of the Book II. Big Data’s Impact on Insurance III. Information Asymmetries and Principles of Insurance Law IV. Remedies for Insurers’ Misuse of Big Data V. Relationship between Social Change and Legal Principle PART I BIG DATA’S IMPACT ON THE PROVISION AND REGULATION OF INSURANCE 1. Big Data and Predictive Analytics I. Big Data: Definition and Techniques II. The Nature, Collection, Sources and Aggregation of Data III. How Big Data is Transforming Insurance Business IV. Conclusions 2. Regulatory Assessment of the Use of Big Data by Insurers I. Regulatory Assessment by UK Regulators II. Regulatory Assessment by EU Regulators III. Conclusions 3. Emerging Themes and Issues I. Transparency and Privacy Concerns II. Information Asymmetries, Adverse Selection and Segmentation of Risk Pools III. Access to Insurance IV. Conclusions PART II BIG DATA AND THE PRINCIPLES OF INSURANCE LAW 4. Big Data and the Permissible Constraints on the Scope of Cover I. Terms of Insurance Contracts II. General Constraints on Policy Terms III. Constraints in Relation to Specific Classes of Risk IV. Conclusions 5. Good Faith and Duties of Disclosure in Insurance Law I. Duties of Disclosure in English Contract Law II. The Good Faith Duty of Disclosure in Insurance Law III. Legislative Reform IV. Conclusions PART III THE IMPACT OF REGULATORY LAW ON INSURANCE LAW 6. Regulatory Constraints on the Collection and Use of Data I. Financial Services Regulation II. Regulation of Insurance – The Insurance Distribution Directive III. Data Protection Regulation IV. Conclusions 7. Impact of Regulatory Duties on the Content of the Duty of Good Faith I. Deficiencies in the Good Faith Duty of Disclosure II. Does the GDPR’s Application to Insurers Address the Common Law’s Deficiencies? III. Can the Good Faith Duty of Disclosure Evolve by Analogy with the GDPR? IV. The Evolution of the Common Law Duty of Disclosure on Insurers V. Conclusions PART IV REMEDIES 8. Remedies for Insurers’ Misuse of Data I. Financial Services Remedies II. Consumer Law Remedies III. Equality and Anti-Discrimination Remedies IV. Competition Law Remedies V. Data Law Remedies VI. Insurance Law Remedies at Common Law PART V CONCLUSIONS 9. Conclusions I. Summary of the Argument II. Detailed Conclusions III. The Future of Insurance in the Big Data Age