Actuarial Notes

Solvency II Technical Provisions for General Insurers

By Susan Dreksler, Christopher Allen, Ayuk Akoh-Arrey, Jeffrey A. Courchene, Basit Junaid, Jerome Kirk, William Lowe, Shane O’Dea, Jonathan Piper, Meera Shah, Gemma Shaw, David Storman, Seema Thaper, Lucy Thomas, Matthew Wheatley and Matthew Wilson · Institute and Faculty of Actuaries · 2013

Study guide: Exam 6C

A working-party paper explaining the Solvency II requirements for general insurers' technical provisions and suggesting how they may be implemented. Dated August 2013, it brings together the work of the Institute & Faculty of Actuaries General Insurance Reserving Oversight Committee's working party on Solvency II technical provisions, formed in 2009, and aims to help those new to the requirements, fuel debate among experienced practitioners and promote best practice. It was presented to the Institute and Faculty of Actuaries on 25 November 2013 and published in the British Actuarial Journal, Vol. 20, part 1.

On the syllabus

  • Exam 6C — objective C4; Sections 6.4 and 6.5.

1 Introduction

2 Solvency II requirements for technical provisions in brief

3 Best estimate: claims and premium provision

4 Reinsurance

5 Expenses

6 ENID (Binary Events)

  • 6.1 Terminology
  • 6.2 Introduction
  • 6.3 The guidance
    • 6.3.1 Solvency II Directive - Article 77 (2)
    • 6.3.2 Groupe Consultatif - Valuation of Best Estimate under Solvency II for Non-life Insurance Interim Report
    • 6.3.3 CEIOPS Advice - CEIOPS DOC 21/09 CEIOPS Advice for Level 2 Implementing Measures on Solvency II: Technical Provisions: Elements of Actuarial and Statistical Methodologies to Calculate the Best Estimate
    • 6.3.4 LTGA and QIS5
    • 6.3.5 Lloyd's Guidance (March 2011)
  • 6.4 What are ENID (binary events)?
    • Binary events are often taken to mean high-severity, low-probability loss events that are not represented in the historical data used for reserving and may be unforeseeable.
    • Going back to the original wording of the Solvency II Directive, the working party defines ENID (Events Not In Data) as "the balancing amount required to bring the best estimate before ENID up to an amount allowing for all possible future outcomes".
    • ENID loadings therefore vary not only with the nature of the risks underwritten but also with the insurer's reserving policy.
    • A loading need not increase reserves: it allows for positive outcomes not already allowed for too — a successful new claims process, a court award or a change in legislation in the insurer's favour.
  • 6.5 General considerations in estimating a loading for ENID
    • 6.5.1 The starting point
      • First determine which exposures and risks the current best estimate includes; where an Actuarial Best Estimate plus a management adjustment is booked, specific events behind the adjustment can move into the ENID bucket, without double counting, and an adjustment tied to no specific event is likely removed as margin.
    • 6.5.2 Identifying ENID
      • Underwriters, claims managers, reserving and pricing actuaries and reinsurance managers can brainstorm future events affecting settlements on past claims and on the exposure remaining at the valuation date.
      • The exposure period is limited to business the (re)insurer is obligated to at the valuation date — 13 months for an insurer writing annual policies that accepts business within a month of cover starting.
      • Candidates include catastrophe exposure, large one-off claims, legislative change, court awards, accumulations, and changes in policy terms or claims processing; consistency is considered with reverse stress testing, the risk register, pricing models, catastrophe modelling and the internal capital model.
      • Estimation is subjective, and minutes of discussions and process documentation can evidence the decisions and assumptions made.
    • 6.5.3 Is it necessary to identify potential ENID?
      • It is not necessary for calculating a loading, and identifying all potential outcomes is arguably impossible, but the exercise can underpin a probability/severity loading, check a truncated distribution method, and raise awareness of the risks underlying the business.
  • 6.6 Methodology
  • 6.7 Benchmarking
    • 6.7.1 Can we benchmark our ENID loading?
    • 6.7.2 Available benchmarks

7 Segmentation

8 Risk Margin

9 Balance sheet considerations

10 Validation

11 Reporting

12 Communication

Appendix 1 Glossary of terms

Appendix 2 References and further reading

Sources