by Underwriting is the process of reviewing and selecting risks that an insurer might accept, under what terms, and assigning those an expected cost and level of riskiness.
- Some underwriting processes are driven by statistics. A few insurers who developed a highly statistical approach to underwriting personal auto coverages have experienced high degree of success. With a careful mining of the data from their own claims experience, these insurers have been able to carefully subdivide rating classes into many finer classes with reliable claims expectations at different levels. This allows them to concentrate their business on the better risks in each of the larger classes of their competitors while the competitors end up with a concentration of below average drivers in each larger class. This statistical underwriting process is becoming a required tool to survive in personal auto and is being copied in other insurance lines.
- Many underwriting processes are highly reliant on judgment of an experienced underwriter. Especially commercial business or other types of coverage where there is very little close commonality between one case and another. Many insurers consider underwriting expertise to be their key corporate competency.
Usually the underwriting process concludes with a decision on whether to make an offer to accept a risk under certain terms and at a determined price
How underwriting can go wrong:
- Insurers are often asked to “give away the pen” and allow third parties to underwrite risks on their paper. Sometimes a very sad ending to this.
- Statistical underwriting can spin out of control due to antiselection if not overseen by experienced people. The bubble of US home mortgage securities can be seen as an extreme example of statistical underwriting gone bad. Statistics from prior periods suggested that sub prime mortgages would default at a certain low rate. Over time, the US mortgage market went from one with a high degree of underwriting of applicants by skilled and experienced reviewers to a process dictated by scores on credit reports and eventually the collection of data to perform underwriting stopped entirely with the no doc loans. The theory was that the interest rate charged for the mortgages could be adjusted upwards to the point where extra interest collected could pay for the excess default claims from low credit borrowers.
- Volume incentives can work against the primary goals of underwriting.
- Insurance can be easily undone by underwriting decisions that are good risks, but much too large for the pool of other risks held by the insurer.
To get Underwriting right you need to:
- Have a clear idea of the risks that you are willing to accept, your risk preferences. And be clear that you are going to be saying NO to risks that are outside of those preferences.
- Not let the pen get entirely out of the hand of an experienced underwriter that is trustable to make decisions in the interest of the firm, either to a computer or to a third party.
- Oversight of underwriting decisions needs to be an expectation at all levels. The primary objective of this oversight should be to continually perfect the underwriting process and knowledge base.
- Underwriters need to be fully aware of the results of their prior decisions by regular communication with claims and reserving people.
Value
- Alignment of the pricing market strategy and reinsurance arrangements to the organisation’s risk appetite as well as optimising the goals of the organisation
- Assist clients to recognise risk events and changes to claim rates earlier, so as to move towards a more market responsive, risk-based pricing approach which ensures the efficient deployment of capital and a reduction in extreme risk event losses.
- Enhance the feedback mechanism from claims function to underwriting and product development processes to improve the performance and profitability of these processes.
Work Undertaken
- Assessment, design and implementation of Insurance Strategies
- Assessment, design, implementation of Insurance Risk Frameworks
- Assessment, design and implementation of insurance risk related risk portfolios and assessment methodologies
- Assessment, design and implementation of Insurance Risk Appetite Statements
- Claims Function KPI design
- Commodity Sector Strategy Input
- Insurance Product Pricing
- Underwriting Function KPI design
- Reinsurance Program Design
Work Undertaken
- Insurance Risk Analysis: Trend analysis
- Insurance Risk Analysis: Exposure Measurement
- Insurance Risk Exposure Management
- Risk capital Reserving
- Claims Result Analysis
- Reinsurance Effectiveness
- Insurance Risk Aggregation and concentration risk measurement and management
- Peer review Actuarial Services
- Audit review of liabilities, capital etc
- Insurance Needs Assessment and/or Insurance Selection recommendations for non-insurance clients
- Risk Management Software Systems: Insurance Risk Underwriting Software Design, Specifications, Testing, Review
- Mergers and Acquisitions assistance
