As part of a holistic digital transformation, insurance and reinsurance companies can enhance their businesses by adopting cloud services. With that scope in mind, the European Insurance and Occupational Pensions Authority (EIOPA) recently published a consultation paper providing guidelines for insurers outsourcing to cloud service providers. These guidelines will affect all outsourcing arrangements entered into or amended on or after 1 July 2020.
In the paper “EIOPA’s guidance on cloud outsourcing,” Milliman consultants explore the implications for firms and discuss some relevant information technology (IT) considerations. The paper also provides a checklist of the steps firms need to consider before, during, and after engaging in an agreement with a cloud service provider.
Milliman has announced the second quarter (Q2) 2019 results of the Milliman Mortgage Default Index (MMDI), which shows the latest monthly estimate of the lifetime default risk of U.S.-backed mortgages. The goal of the MMDI is to provide a benchmark to understand trends in U.S. mortgage risk.
As of July 1, 2019, the MMDI for government-sponsored enterprise (GSE) acquisitions (purchased and refinanced loans backed by Freddie Mac and Fannie Mae) decreased to an estimated average default rate of 1.99%, down from 2.01% in Q1. This means that, for the average Freddie or Fannie mortgage that originated in Q2 2019, there is a 1.99% probability the loan will become 180 days delinquent or worse. To put that in context, equivalent research from Freddie Mac shows the actual to-date default rate of GSE mortgages originated in 2007 (shortly before the financial crisis) was 13.8%.
interest rates in Q2 spurred more borrowers to refinance, which typically
reduces credit risk for underlying mortgages,” says Jonathan Glowacki,
principal and consulting actuary at Milliman and co-author of the MMDI. “But
while the default rated dipped slightly in the second quarter of this year,
we’re also starting to see increased economic risk from slower home price
growth, which may elevate mortgage default risk in the future.”
For Ginnie Mae loans, the Q2 2019 MMDI rate increased from 8.09% in Q1 to 8.15% in Q2. This uptick is consistent with the overall trend for these loans, as default risk for Ginnie Mae acquisitions has been rising since 2014. Default risk is driven by various factors, including the risk of a borrower taking on too much debt, underwriting risk such as certain mortgage features, and economic risk such as a recession, which can put pressure on home prices.
For more information on the MMDI, click here.
As a new wildfire season in California is ablaze, answers to
questions about insurers’ pricing, underwriting, and exposure management
functions resulting from the 2017 and 2018 seasons are still taking shape.
According to Milliman estimates, the 2017 wildfire season alone wiped out just
over 10 years of underwriting profits for California homeowners insurers. Moreover,
the combined 2017 and 2018 wildfire seasons wiped out about twice the combined
underwriting profits for the past 26 years, leaving the insurance industry with
an aggregate underwriting loss of over $10 billion for the California homeowners
line of business since 1991.
A historically profitable line of business has recently
become an unprofitable line exposed to a severe peril that is neither easily
measured nor fully understood. As a result, wildfire risk has become a key
focus of Californians, and their property insurers.
Catastrophe simulation models, or “CAT models,” have been
developed for a variety of catastrophic perils, such as hurricanes, floods,
winter storms, earthquakes, and wildfires, to provide insurers with scientific
techniques to quantify and assess their exposure to catastrophic risk. Recognizing
the growing importance of this peril, a number of firms have been working to
apply the latest techniques in catastrophe modeling to wildfires.
In their article “Wildfire catastrophe models could spark the changes California needs,” Milliman’s Eric Xu, Cody Webb, and David D. Evans explain how enhanced quantification and understanding of wildfire risk represents one of the most important challenges for property insurers writing business in the Western United States, and how innovations in the field of catastrophe modeling may assist them with this task.
While the insurance sector in Greece has been adversely affected by the country’s economic decline, several issues within the sector, which predate the economy’s downturn, have hurt it too. The industry has made some improvements the last couple of years and now has good profitability, though volumes are still nearly 30% below the peak level reached in 2009. Although the situation looks more promising, a number of challenges remain. Milliman’s Demosthenis Demosthenous and Ed Morgan provide more perspective in their paper “The Greek insurance sector: Recovering like the rest of the economy but with its own challenges.”
In September, the European
Insurance and Occupational Pensions Authority (EIOPA) published a report analysing
cyber risk from both the perspective of insurers providing cyber coverage and
the perspective that insurers are susceptible to cyber threats themselves.
EIOPA’s report examines data gathered from 41 European insurance and
This paper by Milliman consultants Claire Booth and Emma Hutchinson highlights the key findings of EIOPA’s report relating to cyber risk as an element of an insurer’s own operational risk profile. They offer perspective based on their experience working with firms in this area.
The recent increase in the amount of data generated, stored and analysed by insurers to establish their pricing and underwriting policies has led to the emergence of new needs both from a regulatory point of view, with the recent implementation of the European framework of the General Data Protection Regulation (GDPR) and with a view to offering new services on the market (cyber risk).
Milliman consultant Thomas Poinsignon recently explore the development and analysis of actuarial methods within the default security framework—a principle of the GDPR imposed on companies using personal data.
The objective is to extend the elementary mathematical concepts and models used when developing classic non-life insurance pricing models (simple linear regression and generalised linear models) to their use on secure data in accordance with regulatory requirements.
To learn more, read Thomas’s paper, entitled ‘Research on non-life pricing procedures on encrypted and anonymous data under the GDPR.’