Solvency II

Solvency II

With the implementation date set for January 2014, Solvency II is fast approaching and bringing with it a number of challenges. Many insurance companies are already preparing market consistent balance sheets and using economic capital to manage their business, but Solvency II will introduce a new level of rigour. Our products and services already help insurance companies demonstrate adequate financial resources and will be used to support Pillar 1 principals including:

  • Technical Provisions (TP)
  • Solvency Capital Requirements (SCR)
  • Internal Models
  •  Own Risk and Solvency Assessment (ORSA).

Our economic scenario generator, calibration services, and consultancy will be used as the foundation of many insurers’ Solvency II processes. Our focus on the capital and risk management needs of the insurance industry means we can offer a broad range of services to support the technical challenges that insurers face in implementing Solvency II. If you are interested in finding out how we can help you, please contact us.

Read our Research:

  • EIOPA 2014 Insurance Stress Test

    On 30 April 2014, EIOPA launched the 2014 stress tests, which will be applied to the balance sheet as of 31 December 2013. Results are due by 11 July 2014. This short paper contains our observations on the exercise.

  • Illiquid Assets and Capital-Driven

    The risk-based nature of Solvency II creates an opportunity for asset managers to play a more strategic role in insurance asset management — capital-driven investment could be for the insurance industry what liability-driven investment has been for pension funds. Low interest rates have motivated insurance firms to redouble efforts to find extra yield, particularly where it can be achieved through improved illiquidity matching of liabilities rather than via significant increases in market or credit risk exposures. In this paper we look at how to measure the illiquidity premiums on offer across the increasingly diverse range of asset classes that a long-term illiquid liability writer such as a fixed annuity business can consider investing in. We also include a case study which demonstrates how these capital-driven metrics are optimized by strategic asset allocation choices.

  • Making the Most of Analytical Data in Decision Making

    In this paper, Brian Heale discusses the many ways in which insurers can use analytical data to support their strategic risk and capital decision-making processes and how this can be integrated with the Own Risk Solvency Assessment (ORSA) and Use Test processes.

  • Proxy Function Fitting: Some Implementation Topics

    In this case study we consider two of the practical challenges faced by insurers in implementing proxy functions: incorporating demographic risk factors and yield curve mapping. We demonstrate the approaches that can be adopted to resolve both issues.

  • Analytical Data How Insurers can Improve Quality

    In the second in a series of papers, which focus on key data topics, Brian Heale gives his view on the types of analytical data required for Solvency II and capital/risk decision making with a particular focus on the techniques for improving quality. This paper has been written for risk, capital and finance practitioners within an insurance organization and aims to demystify how IT techniques can be used to improve data quality.
    Download this paper

  • Data governance best practice: smoothing the way to Solvency II

    In the first in a series of papers, which focus on key data topics, Brian Heale gives his view on the obstacles that insurers have to clear in order to get their data management and governance house in order.

  • Yield curve extrapolation: work in progress

    In this report we provide a highly accessible overview of the current state of play of the technically challenging and increasingly contentious topic of yield curve extrapolation.

  • Adjusting 1-year risk factor scenarios when using instantaneous stresses

    In this paper we address a technical issue that arises when a 1-year VaR economic capital measure is calculated using instantaneous balance sheet stresses. Specifically, the paper shows how 1-year risk factor probability distributions should be adjusted for application to ‘time-0’ balance sheet re-valuations in order to produce the intended 1-year VaR capital estimate.

  • Scenario reweighting: a practical study

    This paper provides an introduction to scenario reweighting techniques which can be used to generate custom economic scenario sets reflecting specific views on one or more economic factors. The advantages and limitations of such methods are described using two case studies relevant to the insurance industry: In the first case study, an economic scenario set reflecting a future inflationary environment is produced, while in the second case study, a scenario set corresponding to a prolonged low-yield environment is considered. Despite a few caveats to keep in mind, scenario reweighting can be a very useful method allowing users to overlay their views on an economic scenario set.

  • Bursting into the cloud

    Cost savings and efficiencies can certainly be achieved by embracing cloud computing. In his second article on the subject, Matt Little outlines the practical applications of using this technology and the reasons for giving it serious consideration.

  • Alternative views on extrapolated yield curves: A fundamental question remains unanswered

    As a consequence of the move towards a market-based approach to valuation which underpins both the Solvency II regulations and the IFRS/FASB rules, the estimation and extrapolation of market yield curves has captured the attention of insurance firms, accountants and regulators. However, as John Hibbert explains, there is more than one approach to extrapolation.

  • The challenges of building yield curve stress scenarios for solvency capital assessment

     A summary of Barrie & Hibbert's high-level approach to modelling extreme movements in yield curves for the purposes of settings solvency capital within a VaR framework.

  • ESG and Solvency II in the Cloud

    Is it realistic and cost-effective to build a Solvency II platform on the cloud? Head of Development Matt Little investigates how insurers could use cloud computing to reduce costs when they need large computational power. 

  • Solvency II Schizophrenia

    When it comes to Solvency II, John Hibbert believes that regulators are allowing an extraordinary opportunity to slip away. But, he says, the vision of the whole project may yet be realised if only regulators would grit their teeth and develop a technically sound rulebook instead of just muddling through.

    In his article, John Hibbert examines the fundamental tensions of the current Solvency II framework and sheds light on some of its inerent contradictions.

  • Solvency II Fudges

    The process of transforming Solvency II from a set of high-level principles into a workable regulatory system now appear to have resulted in compromises in the emerging methodology. Craig Turnbull discusses.

  • Risk aggregation: generalising dependency in the Barrie & Hibbert ESG

    In the first of our Global insurance risk management reports, we describe a relatively straightforward way of changing dependency in Barrie & Hibbert’s ESG. This report looks at how dependency arises in the ESG, in particular how we can change dependency through changing the distribution of the random shocks used to drive the ESG models.

  • Solvency II for DB pension funds

    Could a suitably adapted Solvency II create a risk-based regulatory framework for DB schemes? Andrew Barrie discusses the issues.

  • 1-year VaR assessment and dynamic management actions

    In this note, an illustrative case study is used to demonstrate the materiality of this effect in the context of dynamic management actions in with-profit business.

  • Nested Simulation for Economic Capital

    A common definition of an insurer‟s economic capital requirements is based around a 1-year Value at Risk (VaR) metric. This defines capital requirements in terms of some tail percentile (typically the 99.5th percentile) of the market-consistent value of the insurer‟s balance sheet in 1 year‟s time. The problem of estimating such a metric naturally leads to the concept of nested simulation.

  • Real-world Modelling for Solvency II SCR Internal Models: ‘Point-in-Time’ v ‘Through-the-Cycle’

    In this Insights we discuss the aim of our real-world projection: are we aiming to generate a forward-looking projection relevant to the coming year, or a projection that represents a typical year? This decision can have a significant impact on the size of the SCR and also the viability of any hedging and risk management strategies

  • Solvency II: Preparing your ESG for Internal Model Approval

  • Understanding the ESG requirements for Solvency II

  • CP39-42: the key implications

  • Market-Consistent Valuation: Judging the market

    Recent market turmoil has further highlighted the challenge the insurance industry faces when valuing their liabilities. Like the CRO Forum1, we believe the principal of market-consistent valuation is the right basis for this job. Whilst financial economics and mathematical models provide the intellectual technology for market-consistent valuation, its application to insurance liabilities can require significant judgement which must be applied within a good governance structure.

    In this note we consider how the need for judgement in the market-consistent valuation process arises and what it means for risk managers.