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Digitalization’s Big Promise and Peril: The Personalization of Insurance Contracts and Its Legal Consequences

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Law and Economics of the Digital Transformation (ILEC 2023)

Part of the book series: Economic Analysis of Law in European Legal Scholarship ((EALELS,volume 15))

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Abstract

This chapter analyzes the application of digital tools used to personalize consumer insurance contracts. First, a proper meaning of “personalization” is proposed, and its function in the insurance context is discussed. Subsequently, the paper illustrates the most important scenarios of incorrect personalization from the perspective of consumer insurance buyers. This enables an analysis of what legal remedies under contract and consumer law may be applied to protect the interests of consumer insurance buyers. The chapter’s conclusion identifies a preferred and feasible solution from the perspective of insurance consumers themselves.

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Notes

  1. 1.

    Mik (2016), p. 19.

  2. 2.

    Fourberg et al. (2021), pp. 30–31; Townley et al. (2017), pp. 689–690.

  3. 3.

    This can already be observed in the legal literature, see e.g.: Thouvenin et al. (2019); Infantino (2022). Sceptically: Helberger et al. (2021), p. 102; Personalization mechanisms frequently rely on predictive analytics using Big data sets—information fuelling the personalization process is not only derived from the data on this individual person but also from other data sets on “similar consumers” and statistical data. Mik (2016), p. 20. In fact, the better the latter proxies are, the less information is needed about the actual preferences of an individual. Consequently, it can be argued that during the process of tailoring the information the point of reference is not a particular individual. The benchmark is the “alter ego” of that individual, their digital representation construed within the digital environment, mostly for commercial purposes. This creates a problem which can be referred to as de-personalization by personalization tools: Helberger et al. (2021), pp. 103–104; Infantino (2022).

  4. 4.

    Infantino (2022).

  5. 5.

    Under Art. 5 1(b) GDPR such a general manner of describing the aims of data processing may be considered insufficient, therefore, as a rule, more information in this regard is expected to be given. Zuiderveen Borgesius and Poort (2017), p. 359; Steppe (2017), p. 778. It is recommended that examples and descriptions of general terms such as “personalized advertising” are given when specifying the purposes of data processing. Pałka (2020), p. 632.

  6. 6.

    Mik (2016), p. 20.

  7. 7.

    Inter alias: Namysłowska and Jabłonowska (2020); Południak-Gierz (2019); Wagner and Eidenmüller (2019); Zuiderveen Borgesius and Poort (2017); Mik (2016); Infantino (2022).

  8. 8.

    On personalizing different branches of law, see e.g.: Denno (2019) (criminal law); Busch (2019); Ben-Shahar and Porat (2019) (contract law); Burk (2019); Libson and Parchomovsky (2019) (copyright law); Mora, “Personalized Law: Using Information from Previous Proceedings” available at www.studocu.com/it/document/universita-degli-studi-di-milano/diritto-internazionale/saggio/fulltext-dirittoprivatoedanni/2666055/view; Kugler and Strahilevitz (2019) (procedural law).

  9. 9.

    On the reasons behind mispersonalization in the context of consumer insurance: Tereszkiewicz, Południak-Gierz (2021).

  10. 10.

    Loacker (2015).

  11. 11.

    On the applications of Big Data, see: International Association Of Insurance Supervisors (IAIS) (2020), pp. 14–30. Borselli (2020) pp. 101, 107–108. On the opposing legal response towards the use of personalization mechanisms in insurance, see: Thouvenin et al. (2019), p. 210; Infantino (2022).

  12. 12.

    Tereszkiewicz and Południak-Gierz (2021).

  13. 13.

    Basedow et al. (2015).

  14. 14.

    McFall et al. (2020), pp. 3–4.

  15. 15.

    Krikler et al. (2004) p. 71.

  16. 16.

    Prices for new customers are lower than renewal prices for risk-equivalent insured. Thomas (2012), p. 27. Inertia pricing, upgraded with the Big Data analysis application, is still common. McFall et al. (2020), p. 4.

  17. 17.

    In consumer e-commerce a trend was spotted to set higher price for those prospective clients who were accessing the website using an Apple device. Diganan (2012).

  18. 18.

    Zuiderveen Borgesius and Poort (2017) pp. 352–353.

  19. 19.

    Townley et al. (2017), pp. 683–684.

  20. 20.

    See Bar-Gill (2019), pp. 246–249. On the risk profile and willingness to pay as the points of reference during the individualization of an insurance product offer, see: Thouvenin et al. (2019), p. 210.

  21. 21.

    On personalized and on-demand insurance products, see: https://www.capgemini.com/2018/11/advanced-analytics-enable-insurers-to-predict-customer-needs-and-personalize-services/ (last access 13 October 2022).

  22. 22.

    International Association of Insurance Supervisors, Insurance Core Principles (2019), pp. 222–225; OECD, Regulatory and Supervisory Framework for Insurance Intermediation (2020), p. 29.

  23. 23.

    Tereszkiewicz (2019), pp. 131–132; Tereszkiewicz and Południak-Gierz (2021).

  24. 24.

    Tereszkiewicz and Południak-Gierz (2021).

  25. 25.

    Tereszkiewicz and Południak-Gierz (2021).

  26. 26.

    See Gordley (1981); Thouvenin et al. (2019), p. 215.

  27. 27.

    For instance, under Polish law the exploited party may demand a reduction of its performance or an increase of the performance due to this, and if both are excessively difficult it may demand that the contract be declared null and void. See: Tereszkiewicz and Południak-Gierz (2023) and Południak-Gierz (2023). On difficulties in establishing whether misrepresentation, mistake, duress, undue influence apply, see e.g. Mik (2016), pp. 25–31.

  28. 28.

    Mik (2016), p. 20 (on the false sense of familiarity triggered by personalization); Południak-Gierz (2020), pp. 1015–1017.

  29. 29.

    For instance in the context of Polish law, see: Tereszkiewicz (2015), pp. 443–444; Judgment of the Court of Appeal (Sąd Apelacyjny) in Warsaw of 14 March 2014, case number VI ACa 1183/13, LEX No. 1515319.

  30. 30.

    For instance, under Polish law it would be required to demonstrate that the error concerned the contents of an act in law and if the declarant had not acted under the influence of the error and had judged the case reasonably they would not have made such a declaration of intent. However, if the declaration of intent was made to another person, the evasion of its legal effects is admissible only if that error was caused by that person, or if they were aware of the error or could have easily noticed it. Art. 84 Polish Civil Code. Tereszkiewicz and Południak-Gierz (2023).

  31. 31.

    On when a personalization of price can be viewed as an unfair commercial practice, see e.g., OECD, Personalised Pricing in the Digital Era, Background Note by the Secretariat, 28 November 2018, pp. 34–35, available at https://one.oecd.org/document/DAF/COMP(2018)13/en/pdf (last access 13 October 2022).

  32. 32.

    Mik (2016), p. 9.

  33. 33.

    Introduced by Art. 3 point 5 Directive 2019/2161.

  34. 34.

    Cousy (2012), pp. 125–126. Under Art. 2:102 (1) of the PEICL the insurer shall be entitled to propose a reasonable variation of the contract or to terminate the contract.

  35. 35.

    Cousy (2012), pp. 123–131; Tereszkiewicz (2013b), pp. 473–506; Merkin and Gurses (2015), pp. 1004–1027.

  36. 36.

    Borselli (2020), pp. 115, 131; Alkistis and Chatzara (2020), pp. 49–82, 60.

  37. 37.

    The Civil Code of 23 April 1964, [1964] Official Journal No. 16, Pos. 93 with subsequent amendments.

  38. 38.

    Gutowski (2017) Chap. II, Sect. 2.

  39. 39.

    On the nullity of contract as a sanction for breach of an applicant’s duty to inform, see: Cousy (2012), p. 126.

  40. 40.

    Skorupa (2019) Chap. VIII, Sect. 2.

  41. 41.

    Tereszkiewicz (2013a), p. 236.

  42. 42.

    On the personalized advertisement of insurance product from the perspective of insurance law, see: Południak-Gierz and Olechowski (2022).

  43. 43.

    Under Art. 11a added to Directive 2005/29 by Art. 3 point 5 Directive 2019/2161 consumers harmed by unfair commercial practices, shall have access to proportionate and effective remedies, including where relevant, the termination of the contract.

  44. 44.

    Project Group Restatement of European Insurance Contract Law, Principles of European Insurance Contract Law (PEICL) (2009), p. 100.

  45. 45.

    Art. 7 s. 1 Directive (EU) 2019/2161 of the European Parliament and of the Council of 27 November 2019 amending Council Directive 93/13/EEC and Directives 98/6/EC, 2005/29/EC and 2011/83/EU of the European Parliament and of the Council as regards the better enforcement and modernisation of Union consumer protection rules (OJ L 328, pp. 7–28).

  46. 46.

    For instance, in German law Sect. 6 (5) Insurance Contract Act; Tereszkiewicz (2013a), pp. 247–248.

  47. 47.

    Loacker (2015).

  48. 48.

    Under Polish law the doctrine of unfair exploitation (Article 388 Civil Code) would apply: a contract may be adjusted, where one of the parties, exploiting a forced situation or the inefficiency or inexperience of the other party, in exchange for its own performance accepts or stipulates for itself or for a third party a performance, the value of which at the time the contract is executed grossly exceeds the value of its own performance.

  49. 49.

    In the context of German insurance law, see: Tereszkiewicz (2013a), p. 248; in the context of consumer law: Schulze and Zoll (2021), pp. 42–44, 151.

  50. 50.

    Jungermann and Belting (2004).

  51. 51.

    A good illustration of the difference between what is easy and manageable from the perspective of a human and highly challenging from the perspective of AI-based mechanisms is the case where a self-driving shuttle was hit by a lorry driving at slow speed (when the lorry started to approach the shuttle, the latter stopped instead of reversing). Lee (8 November 2017).

  52. 52.

    In particular, processing vast amounts of data enables, first, discovering features of the person who is profiled even if that person is not aware of them, and second, making highly accurate assessments as to the future events, which in contrast, is not possible for a natural person giving the insurance applicant advice as to the choice of products.

  53. 53.

    Południak-Gierz (2021), pp. 267, 270.

  54. 54.

    One should consider the following scenario: after the risk has occurred, the insurer wants to avoid making a payout and challenges the adequacy of personalization claiming that it was defective and the risk at hand should not have been covered by the insurance product. Had this been the case, the insurer would be exempt from liability.

  55. 55.

    Grochowski (2017), pp. 89–93.

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Acknowledgements

This chapter has been written within the framework of the research project of the Narodowe Centrum Nauki, (NCN) [The National Science Centre] in Poland, Grant Number 2018/29/B/HS5/01281.

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  1. Jagiellonian University, Cracow, Poland

    Katarzyna Południak-Gierz & Piotr Tereszkiewicz

  2. University of Leuven, Leuven, Belgium

    Piotr Tereszkiewicz

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  1. Katarzyna Południak-Gierz
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Correspondence to Katarzyna Południak-Gierz .

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    Klaus Mathis

  2. School of Law, University of Notre Dame, Notre Dame, IN, USA

    Avishalom Tor

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Południak-Gierz, K., Tereszkiewicz, P. (2023). Digitalization’s Big Promise and Peril: The Personalization of Insurance Contracts and Its Legal Consequences. In: Mathis, K., Tor, A. (eds) Law and Economics of the Digital Transformation. ILEC 2023. Economic Analysis of Law in European Legal Scholarship, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-031-25059-0_3

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