2020 Foresight: Trends in Life Insurance Underwriting

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MarketResearch.com announces the addition of a new market research report in Financial Services to their product offering: 2020 Foresight: Trends in Life Insurance Underwriting (http://www.marketresearch.com/land/product.asp?productid=7738891&progid=85735).

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2020 Foresight: Trends in Life Insurance Underwriting

The life insurance segment is characterized by underwriting losses in some developed nations, and underwriting profits in important emerging economies such as China, India, Brazil and Russia. The life insurance segments in developed nations will record a rise in premium rates due to gradual recovery in their economies, meaning that life insurers will need to protect their margins. In the case of emerging economies, the life segment is moving towards a situation that is neither hard nor soft, due to factors such as the highly under-penetrated markets in these countries, increased competition among life insurers and rising disposable incomes. Globally, the life segment is in a state of flux due to far-reaching regulations such as Solvency II in Europe. These regulations essentially link the amount of capital held by life insurers with the risks they underwrite and the investments they make.

The report provides industry and geographic analysis, information and insights into the performance of life insurance segments in some of the important economies across the world. It also provides an in-depth analysis of the impact of important regulations on underwriting and the technological developments in life insurance underwriting.

Key Highlights:

-The life insurance segments in the developed nations of the world have been under pressure because of the economic downturn. On the other hand, the life insurance segments in some of the emerging economies of the world have been thriving due to robust economic growth rates.

-Life insurance regulators across the world have been taking a risk-based capital approach wherein the type of risks that they insure and the type of investments made by them are determined by the capital held by them.

-Given the previously subdued premium rates in the key developed economies of the world, the prices are expected to increase in the future as the life insurers are intent on protecting their margins. The key emerging economies will also witness a gradual hardening of interest rates.

-The citizens of the developed nations, because of the reduction in their disposable incomes, have increasingly been selecting insurance products that provide basic life cover over hybrid or exotic products.

-Technological trends such as automation of the underwriting processes, scanning of social media of potential policyholders to gauge the risk that they represent and application of predictive modeling trends have been mainly impacting the underwriting practices of life insurance companies.

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2020 Foresight: Trends in Life Insurance Underwriting

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2020 Foresight: Trends in Life Insurance Underwriting – Table of Contents:

1 Executive Summary
2 Global Snapshot: Assessment of Life Underwriting Market Dynamics
2.1 Gross Written Premium Global Trends and Drivers
2.2 Analysis of Key Performance Indicators Impacting Underwriting
2.2.1 Underwriting profit and loss trends
2.2.2 Loss ratios
2.2.3 Expense ratios
2.2.4 Combined ratios
3 The Effect of Regulation on Life Insurance Underwriting
3.1 Impact on Life Insurance Product Offering
3.2 Impact on Key Functional and Operational Elements
3.3 Impact on Investment Strategy by Asset Class
3.3.1 Equities
3.3.2 Property
3.3.3 Bonds
3.3.4 Alternative assets
3.3.5 Derivatives
3.4 EU Ruling on Gender-Neutral Insurance to Affect Underwriting
4 Market Dynamics Related to Economic Risk
4.1 Market Dynamics during 2008–2012
4.2 Relationship between GDP and Gross Written Premium Growth
4.3 Relationship between GDP and Underwriting Results
5 Technological Trends in Underwriting
5.1 Creating a Customer Profile
5.2 Automation
5.2.1 Case Study: Bharti Axa’s use of CRM software to speed up claims processing
5.3 Social Media
5.3.1 Social media and underwriting
5.3.2 Case Study: Manulife used social media for investigation in claims processing
5.3.3 Case Study: Rigi Capital Partners used social media to decide on policy purchases
5.4 Big Data
5.4.1 Underwriting and premium determination decision
5.4.2 Case Study: Health Care Service Corp.’s use of predictive modeling techniques
5.4.3 Case Study: Westpac Life’s use of big data to understand customer payment payments
5.4.4 Case Study: Lincoln Financial Group’s use of predictive modeling
6 Appendix
6.1 Methodology
6.2 Contact Us
6.3 About Timetric
6.4 Disclaimer
List of Tables
Table 1: Impact of Tightening Regulations on Asset Classes
Table 2: Capital Charges for Equity Investment
Table 3: Impact of Gender-Neutral Pricing on Life Insurance Products
Table 4: Impact of Gender-Neutral Pricing on Life Insurance Processes
Table 5: Relationships Between GDP Growth Rates and Underwriting Profit/Loss, 2008–2012
List of Figures
Figure 1: Leading Life Insurance Segments, Gross Written Premium (US$) – Global, 2012
Figure 2: Leading Life Insurance Segments – Underwriting Profit or Loss (US$ Billion) and Loss Ratios (%), 2012 and 2016
Figure 3: Leading Life Insurance Segments – Loss Ratios (%), 2012 and 2016
Figure 4: Leading Life Insurance Segments – Expense Ratios (%), 2012 and 2016
Figure 5: Leading Life Insurance Segments – Combined Ratios (%), 2012 and 2016
Figure 6: Regulatory Trends Affecting Life Insurance Underwriting
Figure 7: Impact of Regulations on Life Insurance Business Models
Figure 8: GDP and GWP Compound Annual Growth Rates (2008–2012)
Figure 9: Risk Assessment and Customer Profiling by Life Insurers
Figure 10: Benefits of Automating Life Insurance Processes
Figure 11: Bharti Axa Life Insurance’s Differentiation Strategy
Figure 12: Use of Social Media by Life Insurance Companies in Claim Processing
Figure 13: Use of Big Data Technologies in Life Insurance
Figure 14: Health Care Service Corporation’s Employment of Predictive Modeling Techniques
Figure 15: Westpac Life New Zealand’s Use of Big Data
Figure 16: Lincoln Financial Group’s Use of Predictive Modeling

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