F ICU/vents - hospitals: An algorithm to enable hospitals to make most efficient use hospital resources
Code: DataSci1
Lead: Asif John
Detail: Build an algorithm to enable hospitals to efficiently deploy existing resources and help determine any additional resources / machinery required.
Outputs: pending
Media review - NLP so that they can review media, etc to see if there is any predictive/causal linkages
Code: DataSci2
Lead: Melanie Zhang, John Ng
Detail: Does Twitter activity on COVID-19 contain any early signals on predicting COVID-19 trends on infections and deaths? Consider sources such as Google mobility reports google mobility reports.
Outputs: Webinar 24 July 2020 - Slide pack presented
The aim of this webinar was to provide an overview of research undertaken within the Data Science Working Party on applying machine learning methods for sentiment analysis and opinion mining of UK Twitter data relating to COVID-19.
Establish which data sources are credible for our use
Code: DataSci3
Lead: John Ng
Detail: Sourcing best value data for fast-moving developments in the data that already interested actuaries as well as new material data needs.
Outputs: pending
Contract wording and validity of exclusions for catastrophes
Code: GI4
Lead: Kevin Wenzel / John Charles (TBC)
Detail: Coronavirus and insurance have already made it to the news, with the regulator suggesting it will challenge insurance companies where they believe coverage for the effects of coronavirus on insured events was present.
This is a time of great uncertainty in exposure to risk and reserves on affected lines. How might insurance organisations monitor and assess their exposure to risk to wording uncertainty?
With the current threat possibly being a new fact of life for the near future, and pandemics occurring periodically, what could be done to help the insurance industry meet the needs for coverage in the future?
Outputs: pending
Consumer awareness and contract transparency
Code: GI4A
Lead: Kevin Wenzel / John Charles (TBC)
Detail: The lack of clarity or ambiguous nature of some policy wordings has caused uncertainty with respect to policy cover for consumers. This has the potential to give rise to regulatory and/or political responses and there are historical parallels which may provide an indication as to what might happen. This workstream will create an inventory with a simple classification of what is being agreed as clearly covers COVID-19, what clearly excludes it and then the rest which are uncertain/disputed. This may extend to a comparison of the key tools/controls used by underwriters to manage exposures (e.g. use of standard policy forms such as ISO, LMA vs bespoke wordings)
There is potential for a second workstream to consider consumer awareness. This could consider the following questions: How does the distributor address the requirement to understand and meet customer needs? Is there a gap between what customers expect is rightly covered and what underwriters have sought to cover? Are there differences between SME/sole traders and larger businesses e.g. in terms of sophistication in this insurance purchase decision? Will the impact of COVID-19 lead to broadening or tightening of terms and conditions going forward?
Outputs: pending
Claims inflation and development
Code: GI5
Lead: Keith Brown / Sameer Keshani (TBC)
Detail: Social distancing, illness and economic disruption will have profound effects on general insurance companies claims development, which is used by reserving actuaries to estimate reserves - a vital job to ensure insurance companies can pay liabilities as they fall due.
There will be direct impacts on delays in the supply chain and inflationary pressures. There will be secondary impacts too, for example what will be the effects of the availability of loss adjusters to review claims and then will tradespeople be around to fix them? Furthermore, the external environment has also changed with recorded falls in traffic since lock-down began: will there be fewer car accidents? Consider the qualitative impacts to help reserving actuaries sense check and adjust their models, as well as work to commence on quantitative analysis when and where possible.
Outputs:
Impact of Covid-19 on Marine and Aviation Insurance
As part of the IFoA's Covid-19 Action Task Force, a group of General Insurance actuaries have been studying the impact of Covid-19 and pandemic induced lockdowns on GI claims inflation and development. This blog discusses the changes in exposure and claims experience in Marine and Aviation insurance.
Impact of Covid-19 on health insurance in India
A group of GI actuaries, part of the IFoA's Covid-19 Action Task Force, have been trying to identify changes in exposures and claims experience and their potential impact on reserving. This blog looks at the impact on the health insurance market in India.
A group of general insurance actuaries working as part of the IFoA Covid-19 Action Task Force have been studying the impact of Covid-19. This blog discusses the changes in social inflation caused by pandemic.
The road ahead to motor insurance reserving
Harshitta Malakar, from the IFoA’s COVID-19 ICAT General Insurance Claims Inflation group, looks at the impact of the pandemic on the frequency and severity of motor claims and the issues which reserving actuaries should consider.
Effects of a changing risk profile base on the pricing and availability of insurance products
Code: GI7
Lead: Amerjit Grewal
Detail: Due to COVID-19 there will be immediate as well as longer term impacts on (re)insurers and the wider market from the changing risk profile of policyholders. This may result in demand for new products and/or for existing products to be adapted. As a result, pricing actuaries will need to consider a wide range of factors including regulatory, reputational and commercial considerations.
This workstream will deep dive into the key personal and commercial lines of business affected by COVID-19 from a pricing perspective, and in addition provide a general framework of considerations for GI pricing actuaries when looking at COVID-19 exposures.
Output: For the latest updates and content please refer to the workstreams LinkedIn page at https://www.linkedin.com/company/ifoa-covid-19-action-taskforce-impact-on-gi-pricing
Case Study: Impact on Directors and Officers
Case Study: Personal and Commerical Lines Motor
Stay at home impacts on general insurers
Code: G18
Lead: Keith Brown / Sameer Keshani (TBC)
Detail: Life before lock-down seems further away than merely a few months ago. We have stayed at home to protect the NHS and save lives, and this has changed life as we know it. The uncertainty around the exit plan due to the novel nature of coronavirus means the future is also likely to be different. All this means the speed and value of claims settlement from March 2019 and beyond is likely to be materially different from past data, which is the key assumption of most reserving methods. Are the industry standard "chain-ladder-based" reserving models fit for purpose to cover COVID-19's effects so far and into the future? The workstream should consider the adequacy of current methods, what pragmatic changes could be made and work with existing working parties (maybe for example the Machine Learning in Reserving working party) to help reserving actuaries respond to this challenge and establish reserves which are adequate to meet claims at this difficult time.
Outputs: pending
Insurer and consumer behaviour and unintended bias
Code: G19
Lead: Catherine Drummond (TBC)
Detail: There are a range of considerations when it comes to human behaviour and how COVID-19 may affect this in relation to insurance.
Over confidence bias: firms that fared well during COVID-19 may be complacent about their resilience to future issues / risks – this may also lead to normalcy bias
Herd mentality: following the market during COVID-19 may do policyholders a disservice, or insurers or may mean opportunities are missed
Anchoring bias may mean that parameterisation going forwards may not be representative of the actual risk, due to the recent experience overly driving expectations of the future
Pessimism biases meaning that insurer pricing may not be properly reflective of the real risk – meaning that future policyholders are disadvantaged
Status quo biases – may mean that firms are not properly considering changes in their risk profile as a result of COVID-19 and therefore not responding accordingly
Behavioural research has been a huge growth area in the last 10 years and it’s not something that the IFoA has extensively investigated - this workstream could be expanded into a cross practice working party to investigate any changes that have been brought about by COVID-19.
Outputs: Covid-19, outcome bias and the impact on actuarial analysis
In the first of a series of six blogs, Gordon Woo, catastrophist at RMS, Will Davies, chief actuary at Insurem, Matt Attard, senior analyst at Marsh analytic solutions and Sophie Weisenberger, senior consultant at RPC Tyche, consider outcome bias and its impact on actuarial analysis in the context of COVID-19. They are part of G19, one of the workstreams of the IFoA’s Covid-19 Action Taskforce.
Other outputs
Simple Covid Statistics are Not Always Simple, Chris Smerald
Actuarial Futurism Hidden in Plain Sight, Chris Smerald
Events calendar
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