Post forward features list

Insurance Post writers are working on the features listed below.


You may contact the journalists directly to offer interviews and comments.

Please make sure they have all relevant material several days before the deadline.

 

Topic: How can post-accident investigation be supported by telematics data?
Author: Veronica Cowan
Contact: [email protected]

Deadline: 20 September 

In a recent case reported in the press, the policyholder’s unusual movements – driving around and reversing back and forth were analysed by telematics data. This showed there had been no incident to support his several accident claims.

Black boxes in cars assist insurers curtail fraudulent claims, since their data is a reliable record of the driver’s actions seconds before accidents. It is also important evidence in the absence of independent witnesses.

- How are motor accident investigations supported by telematics data?
- What are the benefits to insurers and customers using telematics data?
- What kinds of specific information can be gleaned from such devices?
- How has the quality of the data improved the reliability of such information in recent years? Are there new – or improved – methods in the pipeline?
- Do accident investigators need to supplement the search for potential causes and explanations for a crash beyond this technology?
- What – if any - errors can skew telematics interpretation?
- Do Dashcams - which are becoming more mainstream - also play a part?
- Do insurers envisage telematics devices becoming compulsory in the future?
- Is the roll out of 5G technology expected to increase the penetration of telematics, and how do phones compare with GPS for this?
- Are there any data protection and security issues from the exponential growth of the storage of such data?


Topic: How far has the insurance industry evolved to respond to natural catastrophes?
Author: Harry Curtis 

Contact: [email protected] 
Deadline: 27 September 

Recent research conducted by UBS suggests Hurricane Dorian could cost insurers more than $25 billion, with total losses of $40 billion. Climate change continues to pose a threat to insurers and reinsurers as natural disasters have grown more common and insurance losses have risen. 

- How are insurers dealing with claims following these events?
- What lessons have been learned following natural disasters over the past decade?
- How have insurers wording policies changed so policyholders can have a better understanding of what their policy includes?
- How has mapping and early warning systems helped?
- What impact will the latest weather incidents have on the market – is it well prepared for these claims so soon after claims in previous years?
 

Topic: Is the adoption of electric vehicles an opportunity for insurance companies?
Author: Pamela Kokoszka 
Contact: [email protected]
Deadline: 27 September 

 

More and more people are switching to using electric vehicles. Zoom has launched the UK’s first car insurance aimed at electric vehicle owners. It offers specific coverage for electric vehicles and is delivered by a specialist team offering benefits geared towards the EV driver.

- Do electric vehicles pose challenges for insurers compared to non-electric cars (electric car insurance is more expensive than conventional insurance,      due to the need for specialist parts and servicing).
- Which insurers offer tailored policies for electric cars? What is different from standard policies?
- What is the current insurance framework around electric vehicles?


Topic: How are businesses and insurers tackling the challenges of cyber modelling?
Author: Tim Evershed
Contact: [email protected]

Deadline: 11 October

The development of cyber risk models has lagged behind the rapid increase in the size and complexity of perils that businesses and insurers both face. This year has seen advances though with RMS and AIR Worldwide both releasing models that cover the risk while Lloyd’s is also doing valuable work in this area.

- How does a cyber risk model differ from a more conventional catastrophe model?
- Given the lack of historical data on cyber losses how have the modellers built these models?
- Which loss scenarios are the models covering?
- How can insurers be confident of the modelled loss estimates? How quickly can these adapt as new threats come to the market?

 

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