{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T13:35:48Z","timestamp":1773840948924,"version":"3.50.1"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031638022","type":"print"},{"value":"9783031638039","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"content-version":"vor","delay-in-days":191,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>With the proliferation of artificial intelligence (AI) in decision-making processes and impending European Union (EU) legislation aiming to safeguard citizens from potential harm, this paper investigates the determinants impacting individual drivers\u2019 car insurance costs. The fundamental principle guiding insurance premiums is the assessment of policyholders\u2019 perceived risk. However, the specific elements informing this assessment remain opaque. To take a deeper look inside the model, our study developed an automated process to collect quote data, considering diverse factors including gender, age (as a proxy for driving experience), geographical location, occupation, and driving history. By conducting an audit of pricing algorithms utilised by insurance companies in the Irish car insurance sector, we gathered quotes from online platforms available in Ireland. Our research provides valuable insights into the multifaceted factors influencing car insurance premiums in Ireland, shedding light on the complexities underlying the algorithmic calculations of insurance quotations. While acknowledging the intricacy of the industry, our analysis reveals evidence of several potentially problematic issues. Notably, we identify that place of residence and occupation exert a direct and substantial impact on the prices quoted to drivers. This study contributes to a deeper understanding of the determinants shaping car insurance premiums, emphasising the need for transparency and fairness within the insurance industry. The findings underscore the significance of addressing systemic disparities and biases in insurance pricing practices to ensure equitable treatment for all drivers.<\/jats:p>","DOI":"10.1007\/978-3-031-63803-9_17","type":"book-chapter","created":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T23:03:55Z","timestamp":1720566235000},"page":"315-330","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Pricing Risk: An XAI Analysis of Irish Car Insurance Premiums"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4887-2572","authenticated-orcid":false,"given":"Adrian","family":"Byrne","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,10]]},"reference":[{"issue":"2","key":"17_CR1","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1002\/pam.10025","volume":"21","author":"PM Ong","year":"2002","unstructured":"Ong, P.M.: Car ownership and welfare-to-work. J. Policy Anal. Manag. 21(2), 239\u2013252 (2002)","journal-title":"J. Policy Anal. Manag."},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Smart, M.J., Klein, N.J.: Disentangling the role of cars and transit in employment and labor earnings. Transportation 47(3), 1275\u20131309 (2020)","DOI":"10.1007\/s11116-018-9959-3"},{"key":"17_CR3","first-page":"1","volume":"2019","author":"S Frezal","year":"2019","unstructured":"Frezal, S., Barry, L.: Fairness in uncertainty: some limits and misinterpretations of actuarial fairness. J. Bus. Ethics 2019, 1\u201310 (2019)","journal-title":"J. Bus. Ethics"},{"key":"17_CR4","unstructured":"Chapados, N., et al.: Estimating car insurance premia: a case study in high-dimensional data inference. In: Proceedings of the 14th International Conference on Neural Information Processing Systems: Natural and Synthetic, Vancouver, British Columbia, Canada (NIPS 2001), pp. 1369\u20131376. MIT Press, Cambridge (2001)"},{"issue":"2020","key":"17_CR5","doi-asserted-by":"publisher","first-page":"160762","DOI":"10.1109\/ACCESS.2020.3021062","volume":"8","author":"C Yan","year":"2020","unstructured":"Yan, C., Wang, X., Liu, X., Liu, W., Liu, J.: Research on the UBI car insurance rate determination model based on the CNN-HVSVM algorithm. IEEE Access 8(2020), 160762\u2013160773 (2020)","journal-title":"IEEE Access"},{"key":"17_CR6","doi-asserted-by":"publisher","unstructured":"Fabris, A., et al.: Algorithmic audit of Italian car insurance: evidence of unfairness in access and pricing. In: Proceedings of the 2021 AAAI\/ACM Conference on AI, Ethics, and Society (AIES 2021), 19\u201321 May 2021, Virtual Event, USA, p. 13. ACM, New York (2021). https:\/\/doi.org\/10.1145\/3461702.3462569","DOI":"10.1145\/3461702.3462569"},{"key":"17_CR7","unstructured":"Cook, T., Greenall, A., Sheehy, E.: Discriminatory pricing: exploring the \u2018ethnicity penalty\u2019 in the insurance market. Citizens Advice (2022)"},{"key":"17_CR8","unstructured":"EC - European Commission. Guidelines on the application of Council Directive 2004\/113\/EC to insurance, in the light of the judgment of the Court of Justice of the European Union in Case C-236\/09 (Test-Achats) C-11\/1 (2012). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX:52012XC0113(01)"},{"key":"17_CR9","unstructured":"ECJ - European Court of Justice. Association belge des Consommateurs Test-Achats ASBL v Conseil des ministres (2011) C-236\/09 (2011). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/ALL\/?uri=CELEX:62009CJ0236"},{"key":"17_CR10","unstructured":"EU - European Union. Charter of Fundamental Rights of the European Union C-364\/01 (2000). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX%3A32000X1218%2801%29"},{"key":"17_CR11","unstructured":"EU - European Union. Charter of Fundamental Rights of the European Union C-326\/391 (2012). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX:12012P\/TXT"},{"key":"17_CR12","unstructured":"Council of the EU. Implementing the principle of equal treatment between men and women in the access to and supply of goods and services L-373-37 (2004). https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=celex:32004L0113"},{"key":"17_CR13","unstructured":"https:\/\/lovin.ie\/uncategorized\/study-reveals-the-irish-counties-that-pay-the-most-for-car-insurance. Accessed 12 Mar 2024"},{"key":"17_CR14","unstructured":"https:\/\/consumerfed.org\/wp-content\/uploads\/2015\/11\/151118_insuranceinpredominantlyafricanamericancommunities_CFA.pdf. Accessed 12 Mar 2024"},{"key":"17_CR15","unstructured":"https:\/\/www.thompsons.law\/media\/1839\/ethnic-penalties.pdf. Accessed 12 Mar 2024"},{"key":"17_CR16","unstructured":"https:\/\/www.which.co.uk\/news\/article\/insurers-in-breach-of-equality-law-says-which-451531-a9nwn0t8kGcY. Accessed 12 Mar 2024"},{"key":"17_CR17","unstructured":"Angwin, J., Larson, J., Kirchner, L., Mattu, S.: Minority neighborhoods pay higher car insurance premiums than white areas with the same risk. Machine Bias. ProPublica, New York (2017). https:\/\/www.propublica.org\/article\/minority-neighborhoods-higher-carinsurance-premiums-white-areas-same-risk"},{"key":"17_CR18","unstructured":"https:\/\/www.bbc.co.uk\/programmes\/b09qb0nf. Accessed 12 Mar 2024"},{"key":"17_CR19","unstructured":"https:\/\/www.fca.org.uk\/publication\/thematic-reviews\/tr18-4.pdf. Accessed 12 Mar 2024"},{"key":"17_CR20","unstructured":"https:\/\/fairbydesign.com\/wp-content\/uploads\/2021\/09\/IFoA_Hidden_Risks_of_Being_Poor_Aug_21_v09.pdf. Accessed 12 Mar 2024"},{"key":"17_CR21","unstructured":"https:\/\/www.gov.uk\/government\/publications\/cdei-publishes-review-into-bias-in-algorithmic-decision-making. Accessed 12 Mar 2024"},{"key":"17_CR22","doi-asserted-by":"crossref","unstructured":"Hannak, A., et al.: Measuring personalization of web search. In: Proceedings of the 22nd International Conference on World Wide Web, Rio de Janeiro, Brazil, WWW 2013, pp. 527\u2013538. Association for Computing Machinery, New York (2013)","DOI":"10.1145\/2488388.2488435"},{"key":"17_CR23","doi-asserted-by":"crossref","unstructured":"Hannak, A., Soeller, G., Lazer, D., Mislove, A., Wilson, C.: Measuring price discrimination and steering on E-commerce web sites. In: Proceedings of the 2014 Conference on Internet Measurement Conference, Vancouver, BC, Canada (IMC 2014), 305\u2013318. Association for Computing Machinery, New York (2014)","DOI":"10.1145\/2663716.2663744"},{"key":"17_CR24","doi-asserted-by":"crossref","unstructured":"Skeem, J.L., Lowenkamp, C.T.: Risk, race, and recidivism: predictive bias and disparate impact. Criminology 54(4), 680\u2013712 (2016)","DOI":"10.1111\/1745-9125.12123"},{"key":"17_CR25","doi-asserted-by":"crossref","unstructured":"Kulshrestha, J., et al.: Quantifying search bias: investigating sources of bias for political searches in social media. In: Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, Portland, Oregon, USA (CSCW 2017), pp. 417\u2013432. Association for Computing Machinery, New York (2017)","DOI":"10.1145\/2998181.2998321"},{"key":"17_CR26","unstructured":"Buolamwini, J., Gebru, T.: Gender shades: intersectional accuracy disparities in commercial gender classification. In: Conference on Fairness, Accountability, and Transparency, pp. 77\u201391. PMLR, New York (2018)"},{"key":"17_CR27","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.H., Ottoni, R., West, R., Almeida, V.A.F., Meira, W.: Auditing radicalization pathways on youtube. In: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, Barcelona, Spain, FAT* \u201920, PP. 131\u2013141. Association for Computing Machinery, New York (2020)","DOI":"10.1145\/3351095.3372879"},{"key":"17_CR28","doi-asserted-by":"crossref","unstructured":"Harrington, S.E., Niehaus, G.: Race, redlining, and automobile insurance prices. J. Bus. 71(3), 439\u2013469 (1998)","DOI":"10.1086\/209751"},{"key":"17_CR29","doi-asserted-by":"crossref","unstructured":"Ong, P.M., Stoll, M.A.: Redlining or risk? a spatial analysis of auto insurance rates in Los Angeles. J. Policy Anal. Manag. 26(4), 811\u2013830 (2007)","DOI":"10.1002\/pam.20287"},{"key":"17_CR30","unstructured":"Larson, J., et al.: How We Examined Racial Discrimination in Auto Insurance Prices. Machine Bias. ProPublica, New York (2017). https:\/\/www.propublica.org\/article\/minorityneighborhoods-higher-car-insurance-premiums-methodology"},{"key":"17_CR31","unstructured":"https:\/\/assets.publishing.service.gov.uk\/government\/uploads\/system\/uploads\/attachment_data\/file\/954331\/Algorithms_++.pdf. Accessed 12 Mar 2024"},{"key":"17_CR32","unstructured":"https:\/\/shap.readthedocs.io\/en\/latest\/. Accessed 12 Mar 2024"},{"key":"17_CR33","doi-asserted-by":"crossref","unstructured":"Altman, D.G., Bland, J.M.: How to obtain the P value from a confidence interval. Bmj 343 (2011)","DOI":"10.1136\/bmj.d2304"}],"container-title":["Communications in Computer and Information Science","Explainable Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-63803-9_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,9]],"date-time":"2024-07-09T23:22:20Z","timestamp":1720567340000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-63803-9_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031638022","9783031638039"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-63803-9_17","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"10 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"xAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"World Conference on Explainable Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Valletta","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Malta","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"xai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/xaiworldconference.com\/2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}