In a shifting landscape where risks are continually expanding and multiplying, insurers must manage their risk exposure and meet future insurance obligations and regulatory capital adequacy requirements while also making the best use of available capital.
Moody’s comprehensive suite of enterprise risk solutions helps insurers manage a wide range of finance and risk data as well as produce risk and solvency analytics to support risk-based decision-making, helping them make efficient use of capital and respond to emerging risks.
We help insurers meet their enterprise risk management needs with a suite of risk modeling, analytical, and reporting tools that take advantage of detailed economic and market scenarios to provide a consistent view of risk.
Learn more about Moody’s Climate Pathways solution — a specialized scenario modeling solution that helps insurers, asset managers, and pensions funds efficiently assess the financial impact of transition risks and overlay physical risk impacts by integrating physical damage assessments into the broader analysis.
Insurers can address their capital and enterprise risk management needs using our RiskIntegrity™ suite of solutions. Our comprehensive, modular solutions help insurers manage:
Moody’s Scenario Generation solutions are a suite of leading-edge stochastic models, software modules, and services that allow insurers and other financial institutions to undertake a wide range of risk management activities.
Customers can use our solutions to assess group-wide economic and regulatory capital, develop capital management strategies, and price complex embedded guarantees and options. Moody’s Scenario Generation solutions are fully transparent, integrated with the leading asset-liability management software, and supported by a range of services.
Moody’s Climate Pathways solution offers specialized scenario modeling for insurers, asset managers, and pensions funds. Assess the financial impact of transition risks and overlay physical risk impacts by integrating physical damage assessments into the broader analysis.
The Risk-Integrated Credit Solution (RICS) captures granular credit and market risks in projections of portfolio dynamics. RICS brings together our market-leading credit correlation model and award-winning Scenario Generator.
Moody's supports catastrophe modeling and exposure management by providing industry-leading science, an innovative technology platform, and a commitment to help each customer create and curate their own view of risk.
Our award-winning models cover natural risks including earthquakes, hurricanes, windstorms, flooding and wildfires in addition to emerging risks like cyberattacks, terrorism, pandemics, and more.
For property and casualty firms, earnings risk is inherently tied to loss volatility, with natural catastrophe risk being one of the main drivers. To navigate this, Moody’s combines data, innovative catastrophe modeling, and robust modeling infrastructure to deliver insights that go beyond catastrophe events to uncover the hidden drivers of volatility and risk correlations at higher levels of granularity.
With Moody’s insights, insurers can better understand the factors affecting their profitability and stability, helping them make informed decisions with confidence.
In this paper we demonstrate the importance of granular portfolio risk-integrated modeling framework through two case studies.
This article explores how insurers can integrate bottom-up and top-down approaches to assess broader systemic risks in ORSA, strategic asset allocation, and TCFD reporting.
Moody's RMS took the title following a landmark 12 months that saw it welcome its 100th active client to use applications and services on its Intelligent Risk Platform™.
This article discusses how secondary perils like floods and wildfires are increasingly impacting insurers' earnings. Moody’s employs high-definition modeling to provide better risk assessments for these frequent events, offering insurers more control over managing earnings volatility.
A key part of insurance asset and liability management is the choice of assets to support the long-dated liabilities. This paper uses the example of direct cashflow matching to demonstrate the importance of granular credit modeling in determining the efficacy of these asset selection strategies.
In this paper we show the importance of jointly modeling market an credit risks for analyzing asset portfolio dynamics.
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