Solvency II Insight

This paper is the first in a series of short whitepapers where Brian Heale examines the major challenges and issues insurers face for report production, data management, and SCR calculation for Solvency II. The series of papers also examines the approaches insurers have taken in their Solvency II projects to date.

Author: Brian Heale
Date: June 6, 2016
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In this paper, we look at the changes that have occurred in interest rate markets since the financial crisis. We consider how insurers can address the challenge of low and (more recently) negative yield curves as central banks have responded to challenging economic conditions with a range of unconventional monetary policies.

Author: Nick Jessop
Date: February 23, 2016
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In this paper we explore many of the practical issues which can be encountered when developing and implementing a process to generate proxy functions using either the Curve Fitting or Least Squares Monte Carlo (LSMC) techniques.

Author: Martin Eilliot
Date: February 16, 2016
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This article explains how Moody’s Analytics can help insurers with their solvency monitoring, reporting and stress-testing requirements in Solvency II.

Published in InsuranceERM
Date: January 19, 2016
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In this paper, we look at the latest developments in the Quantitative Reporting Templates. We consider how insurers can address the challenge of maintaining Solvency II reporting systems to keep pace with the changing and emerging regulatory requirements


Author: Brian Heale
Date: September 1, 2015
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In this whitepaper we look at how Moody’s Analytics EDF™ (Expected Default Frequency) probability of default measures can help pension plan sponsors and their advisors.

Author: David W. Munves
Date: February 18, 2015
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We look at the challenges that insurers, fund managers and market data providers face in providing and aggregating the asset data required for the completion of the QRT templates and the SCR calculation.

Author: Brian Heale
Date: December 15, 2014
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This Whitepaper explores how the Solvency II Solvency Capital Requirement (SCR) calculation process can be automated to facilitate efficient and timely regulatory reporting. The SCR
calculation process is complex, requiring significant data consolidation, cleansing and transformation to produce accurate and consistent results.

Author: Brian Heale
Date: July 21, 2014
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This whitepaper discusses how the Chancellor of the Exchequer's budget statement, "Freedom and Choice in Pensions" will impact U.K. life insurance industry.

Author: Phil Mowbray
Date: June 16, 2014
As the deadline for Solvency II approaches, many insurers are assessing the best approach to delivering the Pillar III reports required by EIOPA. Watch the Moody's Analytics Pillar III Reporting Webinar to learn the common implementation challenges of Pillar III reporting, the three step best-practice framework that will help deliver Pillar III reports, and how to avoid the pitfalls of implementing Pillar III reporting.

Presenter: Brian Heale
Date: June 16, 2014
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This publication addresses the full spectrum of data challenges: data governance, data quality, tactical and strategic reporting, and data needed for informed decision making around Solvency II.

Author: Brian Heale
date: May 25, 2014
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If the banking experience is anything to go by, insurance SIFIs are going to face major challenges in preparing for and implementing the Fed stress testing. This presentation identifies and proposes solutions to these challenges, referencing our experience of working with the banks to address their stress testing needs and putting this in the specific context of an insurance operation.

Presenter: Tony Dardis
Date: May 12, 2014
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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. He also addresses how this can be integrated with the Own Risk Solvency Assessment (ORSA) and Use Test processes.

Author: Brian Heale
Date: November 22, 2013
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Moody's Analytics propose d''adopter une approche plus globale pour répondre à l’ensemble des réglementations en vigueur dans le secteur plutôt que de les appréhender individuellement pourrait s’avérer une meilleure stratégie, d’autant plus pertinente que les données sont déjà largement utilisées par les assureurs, tant à des fins réglementaires qu’en matière de prise de décision.

Auteur: Brian Heale
Date: October 10, 2013
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Insurers face considerable challenges complying with Solvency II’s Pillar III. In this paper, Brian Heale assesses both tactical and strategic approaches for addressing the Pillar III requirements, and proposes a hybrid approach that both satisfies immediate needs and can grow into a strategic solution over time.

Author: Brian Heale
Date: September 16, 2013
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With the Solvency II deadline approaching – full introduction of the regime is expected on 1 January 2016 and interim measures proposed by the European Insurance and Occupational Pensions Authority (EIOPA) are likely to be enforced one year earlier (i.e., in 2015) – we believe this is a timely moment to assess the progress made by industry participants toward achieving compliance and to analyze the approaches adopted by the industry to address the regulation. Despite good progress by some sections of the industry, our research indicates that some insurers still have substantial work to do in order to attain compliance.

Author: Maria Concepcion Canamero
Date: July 25, 2013
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There is little doubt that analytical data is a foundation, not only for Solvency II and IFRS programs, but also better informed capital/risk decision making. In the second in a series of papers focusing 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.  

Authors: Brian Heale
Date: July 17, 2013
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In this podcast, Brian Heale discusses the Moody's Analytics Solvency II Survey. Topics include issues and trends uncovered by the survey, why data is an important issue for insurers, and ways insurers can address the data challenge.

Interview with Brian Heale
Date: June 30, 2013
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This presentation offers an overview of ORSA and the quantitative modelling requirements needed. Download this presentation to learn more about the Least Squares Monte Carlo (LSMC) approach, which is an important component of a firm’s ORSA in the context of solvency capital projection. In addition,  multi-year proxy function applications based on stochastic projections, reverse stress testing and scenario testing are examined. This presentation was hold at the Nordics life and Pension event in Stockholm, May 24th.  

Authors: Gavin Conn
Date: May 24, 2013
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Insurers need a modelling capability that meets two key requirements. The first is the ability to determine appropriate multi-year scenarios (deterministic stress tests or stochastic) in which to project the insurer’s business. The second is the ability to accurately assess the capital requirements that would be created within these scenarios. In this report we provide you with an overview of the fundamental challenges of ORSA and practical guidance on the approach you might take.  

Authors: Craig Turnbull, Andy Frepp
Date: June 7, 2013
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In the first in a series of four papers, 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 in preparation of Solvency II, and for other regulatory regimes such as ORSA. 

Author: Brian Heale
Date: April 25, 2013
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Solvency II and similar regulations are creating a fundamental shift in the way insurers companies qualify and quantify risk. Download this paper to get an overview of this impact and learn how insurers are coping with it. This article was featured in the Asia Insurance Review in March 2012. 


Author: Mark Irwin
Date: March 2012

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Solvency II for DB Pensions Funds: The Holistic Balance Sheet Using Risk-Neutral Simulation to Value the Sponsor Covenant Holistic Balance Sheet: From Technical Provisions to Capital

Author: Craig Turnball
Date: February 13,2012

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The average insurance company is unprepared for the data quality requirements of the new regulation. This presentation goes through the challenges insurances companies face: the actuarial function judgment for the calculation of best estimates, the accumulation of non-essential data for many decades, and the duplication of data and inconsistency of values. Data Quality Assessment is the core requirement for Insurance companies to face those challenges.

Author: Massimiliano Neri
Date: November 17, 2011
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(German translation) Best Practices in Solvency II Implementation: Ökonomische Szenariogenerierung, from Moody's Analytics Solvency II Roundtable, Cologne, 17 November 2011.

Author: Christian Thun
Date: November 17, 2011

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David Munves presented these slides at the Moody’s Analytics Munich Market Signals Event, 27 Sept 2011. The document covers the distinction between Point-in-Time Risk Measures and Through-the-Cycle Risk Measures, followed with a technical description of the Through-the-Cycle EDF model methodology, and a conclusion on the degree of stability achieved of forward looking default prediction power.

Author: David Munves
Date: September 27, 2011
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The paper demonstrates that managing Pillar 3 in isolation is not recommended and insurers should be taking a holistic approach to Pillar 3 implementation. By building a disclosure strategy, which coordinates implementation of the reporting requirements with the Pillar 1 data management and capital requirements, insurers can create an efficient, effective and robust regulatory risk platform for stronger operational effectiveness and risk-based decision making.

Author: Christophe Burckbuchler
Date: August 31, 2011

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The Solvency II Directive introduces strict requirements for data quality. This paper outlines the main data quality requirements and provides best practices for data quality assessment and management, including types of data quality checks and processes, and audit and checking capabilities. It also demonstrates that a centralised approach to data quality management that leverages technology to automate the process should help insurance companies go beyond greater operational effectiveness and stronger risk-based decision making.

Author: Max Neri
Date: May 1, 2011

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Insurance regulations are currently dominated or influenced by the EU-based regulatory framework, Solvency II. With Solvency II, regulators aim to improve both risk measurement and capital planning in the insurance industry which hasn’t undergone regulatory reform since 2006 when Solvency I was implemented. The regulation consists of three pillars: quantitative requirements, supervisory review and market disclosure. This presentation looks at the two approaches insurance firms can take to meet their minimal capital requirements and the wider resourcing and data gathering challenges they face.

Date: March 1, 2011

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