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Today’s Regulatory Landscape: Complying with Multiple Regulations Simultaneously
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• Regulates the amount of capital that EU insurance companies must hold to reduce
the risk of insolvency. Also regulates governance and risk management processes.
• Encompasses all insurance and reinsurance firms with gross premium income
exceeding €5m or gross technical provisions in excess of €25m within the EU and
their subsidiaries outside of the EU. Also applies to European subsidiaries of global
insurance companies.
• EIOPA (the European Insurance and Occupational Pensions Authority) issues
Solvency II guidelines and recommendations and developed draft regulatory and
implementing technical standards
• Came into effect on January 1st, 2016
What Is Solvency II?
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• Insurers must hold capital against a range of risks, not just insurance risks
• Insurers are required to identify, measure and proactively manage risks; all risks and
their interactions must be considered
• Supervisory review process
• Greater public disclosure and reporting to regulators (QRTs, FSR, SFCR, ORSA, and
National Specific Templates)
• 2016 reporting timelines:
− Insurers with December 31st, year-ends must file their first quarterly reports by May 26th, 2016
− The first annual reports are due May 20th, 2016 (based on 2015 data)
− Reporting deadlines in the first year are longer and then reduce every year for three years.
− Some smaller firms can apply for certain reporting exemptions.
What Does Solvency II Involve?
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Solvency II compliance requires a wide range of information, from instrument and entity
reference data to pricing data, funds look-through, and security ratings
• Each Solvency II pillar involves specific data requirements:
• Data requirements can broadly be grouped into five categories:
1. Identifiers: Security codes, counterparty and issuer identifiers, fund IDs, etc.
2. Entity and Instrument Characteristics: External ratings, durations, LGDs, etc.
3. Categorisations: CIC Codes, industry sectors, asset categories, collateral type, etc.
4. Transaction data: Trade date, gains/losses, premium paid/received, etc.
5. Position data: Quantity, notional amount, accrued interest, etc.
Solvency II Data Requirements
Pillar 1
Capital Requirements
Requires asset and
liabilities data, reference
data, issuer data, credit-
related data and
pricing/valuations data
Pillar 2
Governance
and Supervision
Requires data
consistency, auditability,
transparency and history
Pillar 3
Transparency
and Reporting
Requires high-quality
multi-asset class and
entity-level data
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Solvency II And The Data Quality Challenge
• The data reported needs to be not only accurate, but also consistent with that used by
insurers for their Solvency Capital Requirement (SCR) and Minimum Capital Requirement
(MCR) calculations
• Solvency II requires asset data to be ‘complete’, ‘accurate’ and ‘appropriate’; data quality
assurance processes will be monitored by insurers and their supervisors
• Data has to meet the same quality standards irrespective of whether it is sourced internally
or externally. Insurers will want to be sure that the data obtained from their asset
managers, fund administrators and data vendors meets the required standards
• Data consistency may be challenging to achieve because different market data sources
can return different values for the same data field (although each can be accurate in its
own way)
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Source:“CEIOPS’ Advice for Level 2 Implementing Measures on Solvency II: Technical Provisions – Article 86 f, Standards for Data Quality”, CEIOPS, October 2009.
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IFRS 9
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Overview of IFRS 9
• IFRS 9 is a new accounting standard (replacing IAS 39) that will apply throughout
approximately 100 countries, including across the EU
• The goal is for institutions to set aside sufficient provisions to deal with potential future
credit losses
• From January 1st, 2018, IFRS 9 will require banks and listed companies to measure credit
loss impairment based on a forward-looking Expected Credit Loss (ECL) approach. These
will be recorded in their P&L as loss provisions
• IFRS 9 will have a significant impact on financial statements – the greatest impact will be
from credit impairment calculations (expected to increase provisions by >40% compared to
IAS 39). Financial institutions in particular will be significantly impacted
• IFRS 9 will have an impact on regulatory capital, potentially leading to a need to raise equity
• A vast number of institutions are currently unprepared for these new requirements
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IFRS 9 Requirements
• Institutions will need to monitor changes in credit quality and to calculate specific forward-
looking credit risk measures (“Point-in-Time” PDs and LGDs)
• These measures will need to be calculated for two key time horizons: Over the next twelve
months and over the lifetime of instruments, depending on how instruments are classified
into “performing”, “underperforming” or “non-performing”
• This will lead to the following needs:
− The ability to monitor credit quality on an ongoing basis
− Sourcing historical default information and other data required for credit quality assessments
− The ability to simulate realistic forward-looking scenarios
− Integrating the use of new data, models and analytics into accounting processes
− Large banks are likely already to have the required data, models and systems in place, though not
necessarily the required methodologies or analytics
• In the US, the Financial Accounting Standards Board (FASB) is currently developing a
similar proposal to require the calculation of “Current Expected Credit Losses” (CECL)
under US GAAP accounting rules
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Issues For Banks Implementing IFRS 9
Banks will need to adjust their Basel Internal Ratings-Based Models to comply with
IFRS 9. There are a number of differences between the two modelling approaches:
*From Standard & Poor’s Global Ratings. S&P Global Market Intelligence, as well as its products and services are analytically and editorially separate and independent from other analytical areas at S&P,
including S&P Global Ratings. For illustrative purposes only.
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Credit And Market Risk Assessments
S&P Global Market Intelligence deliver key data and analytics which help banks comply with requirements
related to credit and market risk on multi-asset classes.
• For trading books, market risk data is required to estimate volatility and VaR-based risk statistics
• For Banking books, historical fundamental data, estimates, ratings, and probability of default models
are required to comply with the Internal Ratings-Based (IRB) approach and the new IFRS 9 accounting
principle
• Credit default swap spreads are needed to calculate the new Credit Value Adjustment (CVA) capital
charge formulas for ITC derivatives
Credit And Market Risk Assessments
Ratings Credit Analytics and PD and LGD
Credit Assessment Scorecards Fundamental Data
• Credit ratings
• Credit research
• Low latency ratings alerts
• Ratings press releases
• Default, transition and recovery data
• PD Model Fundamental for public and
private companies
• CreditModel 2.6
• PD Model Market Signals (equity-
based)
• CDS-based signals for entities
• PD and LGD credit Assessment
Scorecards for low-default portfolios
• Standardised global company data
• Extended global fundamentals
• Ratings fundamentals (CreditStats
Direct)
• Industry sector classifications
• Internal Ratings Development
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• LEI: Legal Entity identifier used to identify counterparties, issuers and ultimate parent entities (to
monitor concentration risk) - S&P Global Market Intelligence’s Business Entity Cross Reference Service
includes LEI codes and mappings to ultimate parent entities
• NACE: European Standard Industry Classification - S&P Global Market Intelligence’s Industry Sector
Cross-Referencing Services offerings include multiple standard industry classification schemes (e.g.,
NACE and GICS)
• CIC: Complementary Identification Code for asset classification - S&P Global Market Intelligence’s
offerings also include core data required to construct CIC codes (whose determination can involve
subjective elements)
• Instrument characteristics and risk-related metrics including multi-level pricing and valuations
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