Concirrus Quest Marine's Insurance Business Model: The Role of AI and Big Data

26 Pages Posted: 11 Mar 2021 Last revised: 23 Mar 2021

See all articles by Paul D. Timms

Paul D. Timms

Loughborough University

Christopher P. Holland

Loughborough University

Andrew Yeoman

Royal Gwent Hospital; Concirrus

Date Written: March 10, 2021

Abstract

The size of the global marine insurance market in 2018 was approximately $30 billion, but low levels of profitability are common due to intense competition and complex risk assessment problems. Concirrus, an Insurance Technology (InsurTech) disruptor, is transforming the assessment of marine risk through the novel use of Artificial Intelligence (AI) and big data analytics, to develop behavioural risk models. This is part of a broader market trend in insurance, in which traditional underwriting is being replaced by new modes of risk analysis, often based on behavioural risk. In the marine insurance market, the vessel Automatic Identification System can be used as an Internet-connected data source, to provide real-time telematic information regarding the activity of insured vessels. For example, this data includes vessel identification codes, positional information, course, speed and heading, target destination, estimated time of arrival, navigation status, and off-ship calculations. Other market information such as weather data, shipping route data, geographic knowledge, vessel records and insurance records can also be incorporated into sophisticated data analytics to model and better understand risk at a highly granular level. This rich digital and data ecosystem makes it possible to dynamically build and test novel, statistical approaches to model risk and develop new analytics that can be used to mitigate risk by pro-actively influencing business customers. Concirrus is an established marine and automotive InsurTech firm that was founded to capitalise on new behavioural risk modelling techniques and apply them in insurance markets. InsurTech companies disrupt markets by implementing new business models that exploit advances in Artificial Intelligence (AI), high-performance digital technology accessed through cloud computing at relatively low cost, and big data analytics capabilities. Concirrus is an example of an Insurance technology leader, who are taking a digital first approach that avoids legacy system issues such as high maintenance costs, lack of integration and siloed business processes. This case study focuses on Concirrus’ business model and describes the operations of its Quest Marine Insurance Product. The Quest insurance product is an insurance risk analytics platform that combines a wealth of data sets, including complex, longitudinal, and behavioural data so that marine insurers can gain a much more nuanced and detailed understanding of a fleet’s risk profile and can offer connected policies that encourage and reward safer behaviour, which results in lower risk of loss and damage to ships, their contents and crew members. A detailed description and analysis of Concirrus’ value creation process is presented, which is based on Abassi’s model of big data value chains. The business model description identifies several areas of information and analytical competitive advantages, which create business benefits for each of the stakeholders involved in marine insurance: fleet operators; insurance brokers; insurers and reinsurers. More generally, the case study is an exemplar of a technology leader that is disrupting a market through the novel application of AI and digital transformation. The implementation challenges and future trajectory of behavioural insurance are outlined.

Keywords: Behavioural Analytics, Marine Insurance, Business Model, Case Study, Artificial Intelligence, Big Data, Digital Transformation

JEL Classification: M13, M15, O31, O32, G22, C45

Suggested Citation

Timms, Paul D. and Holland, Christopher P. and Yeoman, Andrew and Yeoman, Andrew, Concirrus Quest Marine's Insurance Business Model: The Role of AI and Big Data (March 10, 2021). Available at SSRN: https://ssrn.com/abstract=3801555 or http://dx.doi.org/10.2139/ssrn.3801555

Paul D. Timms (Contact Author)

Loughborough University ( email )

The Wolfson School of Mechanical, Electrical
and Manufacturing Engineering - Loughborough Uni
Loughborough, Leicestershire LE11 3TU
United Kingdom

Christopher P. Holland

Loughborough University ( email )

Epinal Way
Leics LE11 3TU
Leicestershire
United Kingdom

HOME PAGE: http://https://www.lboro.ac.uk/departments/sbe/staff/holland-chris/

Andrew Yeoman

Royal Gwent Hospital

United Kingdom

Concirrus ( email )

New City Court
20 St Thomas Street
London, SE1 9RS
United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
122
Abstract Views
657
rank
308,765
PlumX Metrics