Abstract
Currently, amplified use of the ITC-technologies and digitalization in almost all industries has changed the value and significance of the information. The use of these new technologies offer tremendous opportunities for innovation and development, but at the same time ask for regulation and control policies to ensure appropriate storage and use of information and avoid illicit utilization of data. Moreover, use of innovative technologies such as blockchain-based technology, artificial intelligence, cloud technology, and others has complicated and disrupted the landscape of the financial services providers and their ancillary service providers such as auditors, underwriters, advisors, actuaries, lawyers, and regulators. The insurance services industry as well is substantially influenced by these current developments especially through the intensive adoption of InsurTech and RegTech solutions. With this paper, we aim through a review of the literature, to highlight the challenges in regulation and control in an environment of rapid technological innovation, specifically focusing on InsurTech and RegTech, offering logical solutions to insurance companies. We also provide an analysis of the essence of the main technologies used or potentially used by the insurance services industry as big data, blockchain-based technology, artificial intelligence, and cloud technology, identifying the benefits and risks of these innovative technologies. The analysis results in the proposed strategy to develop and calibrate controls and regulations. To make suggestions for the use of the technological innovative potential in the insurance services industry, we integrate the basic utility model of behavior, as well as the underlying regulatory and control principles as a benchmark. The basic dilemma thereby refers to the control versus innovation dilemma, as all of the strategies for control of innovation due to technology in insurance markets are imperfect. Therefore, the efficiently managed controls are required to be flexible enough to allow for quick recalibration, whenever this is necessary, possibly with Artificial Intelligence or other RegTech solutions.
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Notes
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Craig (2017).
- 2.
Romānova et al. (2018).
- 3.
Kasinow (2017).
- 4.
Marian (2015).
- 5.
Benton and Radziwill (2017).
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Coindesk.com. Available at: https://www.coindesk.com/price/.
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Lee (2017).
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Gupta (2017).
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BlockGeeks (2017).
- 10.
Sirigada (2015).
- 11.
Salam (2012).
- 12.
Ralf (2017).
- 13.
Holder et al. (2016).
- 14.
Chandler (2013).
- 15.
Vaughan (2014).
- 16.
Djankov et al. (2003).
- 17.
Shleifer (2005).
- 18.
Beim and McCurdy (2009).
- 19.
Duff & Phelps (2017).
- 20.
Kahneman and Tversky (1979).
- 21.
Thaler (1980).
- 22.
Simon (1955).
- 23.
Simon (1957).
- 24.
Newell and Simon (1972).
- 25.
Iyengar and Lepper (2000).
- 26.
Ellsberg (1961).
- 27.
Samuelson and Zeckhauser (1988).
- 28.
O’Donoghue and Rabin (1999).
- 29.
Agnew and Szykman (2005).
- 30.
Dambe et al. (2013).
- 31.
Bénabou and Tirole (2006).
- 32.
Ariely et al. (2009).
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Ezell et al. (2016).
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Grima, S., Spiteri, J., Romanova, I. (2020). The Challenges for Regulation and Control in an Environment of Rapid Technological Innovations. In: Marano, P., Noussia, K. (eds) InsurTech: A Legal and Regulatory View. AIDA Europe Research Series on Insurance Law and Regulation, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-27386-6_4
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