12.5 Emerging risks and challenges in actuarial practice
13 min read•august 20, 2024
Emerging risks and challenges are reshaping actuarial practice. From technological advancements to climate change, these new risks require actuaries to adapt their methods and models. Identifying and understanding these risks is crucial for effective assessment and management.
Actuaries face unique modeling challenges with emerging risks due to limited data and complex interactions. They must develop innovative approaches to quantify and communicate these risks, while balancing stakeholder interests and maintaining professional ethics. This evolving landscape presents opportunities for actuarial innovation and expanded influence.
Identification of emerging risks
- Emerging risks are new or evolving risks that have the potential to significantly impact the insurance industry and the work of actuaries
- Identifying and understanding these risks is crucial for actuaries to effectively assess and manage them in their practice
- Actuaries need to stay informed about developments across various domains that could give rise to new risks or alter existing risk profiles
Technological advancements
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- Rapid technological progress introduces new risks related to cyber security, data privacy, and the ethical use of artificial intelligence
- Advancements in areas such as autonomous vehicles, telemedicine, and the Internet of Things (IoT) can disrupt traditional insurance models and risk assessments
- Example: The increasing prevalence of self-driving cars may require actuaries to reassess automobile insurance pricing and liability considerations
- Example: The growing reliance on digital platforms and remote work arrangements exposes insurers to heightened cyber risks and data breaches
Demographic shifts
- Changing population demographics, such as aging societies and increasing life expectancies, can significantly impact insurance demand and risk profiles
- Shifts in family structures, migration patterns, and workforce participation rates can alter the assumptions underlying actuarial models
- Example: The rising prevalence of chronic diseases among aging populations may require actuaries to adjust morbidity assumptions in health insurance pricing
- Example: Increasing global mobility and the rise of multi-generational households can affect mortality and long-term care insurance projections
Climate change impacts
- The escalating frequency and severity of extreme weather events due to climate change pose significant challenges for property and casualty insurers
- Actuaries need to incorporate the potential impacts of climate change on natural catastrophes, agricultural risks, and health outcomes into their risk assessments
- Example: More frequent and intense hurricanes may require actuaries to update catastrophe models and reinsurance strategies for property insurance
- Example: Changing weather patterns and rising temperatures can affect the spread of infectious diseases, impacting health insurance claims and mortality assumptions
Geopolitical instability
- Political uncertainties, social unrest, and geopolitical tensions can introduce new risks or exacerbate existing ones for insurers operating in affected regions
- Actuaries need to consider the potential impact of events such as trade disputes, economic sanctions, and civil unrest on insurance markets and risk exposures
- Example: Political instability in a region may lead to currency fluctuations and inflation, affecting the assumptions used in pricing and reserving for insurance products
- Example: The risk of terrorism or armed conflicts can impact the demand for and pricing of various insurance coverages, such as property damage and business interruption
Evolving regulatory landscape
- Changes in regulations, accounting standards, and supervisory requirements can significantly impact actuarial practice and the insurance industry as a whole
- Actuaries need to stay abreast of regulatory developments and adapt their work to ensure compliance with new requirements
- Example: The implementation of IFRS 17, a new international financial reporting standard for insurance contracts, requires actuaries to modify their valuation and reporting processes
- Example: Evolving data privacy regulations, such as the General Data Protection Regulation (GDPR) in the European Union, can affect how actuaries collect, use, and protect policyholder data
Modeling challenges for emerging risks
- Emerging risks pose unique challenges for actuarial modeling due to their novel and dynamic nature
- Actuaries need to adapt traditional modeling approaches and develop new techniques to effectively capture and quantify these risks
- Addressing modeling challenges is crucial for actuaries to provide reliable risk assessments and support informed decision-making
Limited historical data
- Emerging risks often lack extensive historical data, making it difficult to estimate their frequency, severity, and potential impact using traditional actuarial methods
- Actuaries may need to rely on alternative data sources, such as expert judgment, , or external data sets, to supplement limited historical information
- Example: Modeling the impact of a newly discovered infectious disease may require actuaries to use epidemiological models and real-time data from public health agencies
- Example: Assessing the risk of cyber attacks may involve using data from security firms, industry consortia, or simulated attack scenarios to estimate potential losses
Complexity of risk interactions
- Emerging risks often involve complex interactions and dependencies with other risks, making it challenging to model their combined impact
- Actuaries need to consider the potential for risk accumulation, contagion effects, and non-linear relationships when modeling emerging risks
- Example: The interconnectedness of global supply chains can amplify the impact of localized events, such as natural disasters or political unrest, on multiple lines of insurance
- Example: The adoption of new technologies, such as artificial intelligence, can introduce complex interactions between operational, reputational, and liability risks for insurers
Uncertainty in risk parameters
- The parameters used to model emerging risks, such as frequency, severity, and correlation, are often subject to high levels of uncertainty due to limited data and evolving risk factors
- Actuaries need to incorporate uncertainty analysis and sensitivity testing into their models to assess the robustness of their assumptions and quantify the potential range of outcomes
- Example: Modeling the long-term impacts of climate change on property insurance requires considering uncertainties in future greenhouse gas emissions, climate sensitivity, and adaptation measures
- Example: Estimating the potential losses from a large-scale cyber attack involves uncertainties in the attacker's capabilities, the effectiveness of defense mechanisms, and the potential for cascading effects
Adapting traditional actuarial models
- Traditional actuarial models, such as those based on historical claims experience or mortality tables, may not adequately capture the unique characteristics of emerging risks
- Actuaries need to modify existing models or develop new modeling frameworks that can incorporate the dynamic nature, interdependencies, and uncertainties associated with emerging risks
- Example: Pricing long-term care insurance may require incorporating stochastic models that capture the impact of future medical advances, changes in family support structures, and evolving policyholder behaviors
- Example: Modeling the impact of autonomous vehicles on automobile insurance may involve integrating data from telematics devices, traffic simulations, and accident reconstruction analyses to assess changes in risk exposure
Impact on actuarial assumptions
- Emerging risks can significantly impact the assumptions underlying actuarial work, requiring actuaries to reassess and update their assumptions to maintain the accuracy and reliability of their analyses
- Actuaries need to continuously monitor and incorporate changes in demographic, economic, and behavioral factors that can influence the assumptions used in pricing, reserving, and risk management
Mortality and longevity projections
- Advancements in medical technology, changes in lifestyle factors, and the emergence of new health risks can impact mortality and longevity assumptions used in life insurance and pension valuations
- Actuaries need to consider the potential for future improvements or deteriorations in mortality rates, as well as the impact of specific risk factors on different population subgroups
- Example: The increasing prevalence of obesity and related health conditions may require actuaries to adjust mortality assumptions for certain age groups or underwriting classes
- Example: The potential impact of gene therapies or personalized medicine on life expectancies may need to be incorporated into long-term mortality projections
Morbidity and health trends
- Changes in disease patterns, healthcare utilization, and medical treatment outcomes can affect morbidity assumptions used in health insurance pricing and reserving
- Actuaries need to monitor and incorporate emerging health trends, such as the rise of chronic conditions, mental health issues, or newly identified medical risks, into their assumptions
- Example: The increasing use of telemedicine and remote monitoring devices may impact healthcare utilization patterns and claims experience for health insurers
- Example: The long-term health consequences of exposure to environmental pollutants or occupational hazards may need to be considered in morbidity assumptions for certain populations
Economic and financial assumptions
- Emerging risks can impact the economic and financial assumptions used in actuarial work, such as interest rates, inflation, and investment returns
- Actuaries need to assess the potential impact of changing economic conditions, market volatility, and new financial instruments on the assumptions underlying insurance pricing, reserving, and asset-liability management
- Example: The prolonged low-interest rate environment may require actuaries to adjust discount rate assumptions used in long-term insurance liabilities and pension valuations
- Example: The increasing use of alternative investments, such as private equity or real estate, may impact the assumed investment returns and risk profiles for insurance company portfolios
Behavioral patterns of policyholders
- Emerging risks can influence policyholder behaviors, such as lapse rates, claim frequencies, or benefit utilization, which are important assumptions in actuarial modeling
- Actuaries need to consider how changes in consumer preferences, risk perceptions, and socio-economic factors can impact policyholder behavior and adjust their assumptions accordingly
- Example: The increasing availability of online insurance comparison tools may impact price sensitivity and lapse rates for certain insurance products
- Example: The growing awareness of climate change risks may influence property insurance purchasing decisions and claims behavior in high-risk areas
Risk mitigation strategies
- Actuaries play a crucial role in developing and implementing risk mitigation strategies to manage the potential impact of emerging risks on insurance companies and policyholders
- Effective risk mitigation strategies involve a combination of quantitative analysis, scenario planning, and collaboration with other risk management professionals
Scenario planning and stress testing
- Scenario planning involves developing and analyzing alternative future scenarios to assess the potential impact of emerging risks on insurance operations and financial performance
- is a technique used to evaluate the resilience of insurance portfolios and risk management strategies under extreme but plausible adverse scenarios
- Example: Actuaries may develop scenarios to assess the potential impact of a major cyber attack on an insurer's claims experience and capital adequacy
- Example: Stress testing can help identify the vulnerability of an insurance company's investment portfolio to sudden changes in market conditions or credit defaults
Reinsurance and risk transfer
- Reinsurance is a risk management tool that allows insurers to transfer a portion of their risk exposure to other insurance companies or specialized reinsurers
- Actuaries help design and price reinsurance programs that optimize risk transfer while considering the cost, capacity, and counterparty risk of reinsurance arrangements
- Example: Insurers may use catastrophe bonds or other insurance-linked securities to transfer the risk of extreme weather events to capital market investors
- Example: Actuaries can help structure quota share or excess-of-loss reinsurance treaties to mitigate the impact of large losses or accumulations of risk in specific lines of business
Diversification of risk portfolio
- Diversification involves spreading risk across different geographic regions, lines of business, or customer segments to reduce the overall impact of adverse events on an insurer's portfolio
- Actuaries can help identify opportunities for diversification and assess the effectiveness of diversification strategies in mitigating emerging risks
- Example: An insurer may expand into new geographic markets or product lines to reduce its concentration risk in a particular region or sector
- Example: Actuaries can use portfolio optimization techniques to determine the optimal mix of risks that minimizes the overall volatility of an insurer's underwriting results
Monitoring and early warning systems
- Monitoring involves continuously tracking key risk indicators and market developments to identify potential threats or opportunities related to emerging risks
- Early warning systems are designed to detect and alert insurers to significant changes in risk exposure or market conditions that may require prompt action
- Example: Actuaries can develop dashboards or risk scorecards that monitor changes in claims frequency, severity, or policyholder behavior for specific emerging risks
- Example: Insurers may use algorithms to analyze social media data or news feeds to detect early signs of emerging risks or changes in public sentiment towards specific risk factors
Actuarial communication and reporting
- Effective communication and reporting are essential for actuaries to convey the results of their analyses and the implications of emerging risks to various stakeholders, including management, regulators, and policyholders
- Actuaries need to adapt their communication strategies and reporting practices to ensure that the complex and uncertain nature of emerging risks is clearly and transparently presented
Conveying uncertainty to stakeholders
- Communicating the uncertainty associated with emerging risks is crucial to help stakeholders understand the potential range of outcomes and make informed decisions
- Actuaries can use techniques such as sensitivity analysis, scenario testing, or confidence intervals to illustrate the variability and potential impact of emerging risks
- Example: When presenting the results of a assessment, actuaries may use a range of scenarios to show the potential impact on claims costs under different climate trajectories
- Example: Actuaries can use visual aids, such as heat maps or tornado diagrams, to communicate the relative importance and uncertainty of different risk factors in their models
Transparent disclosure of assumptions
- Transparency in disclosing the assumptions, methodologies, and limitations underlying actuarial analyses is essential to build trust and credibility with stakeholders
- Actuaries should provide clear and concise explanations of the key assumptions used in their models, as well as the rationale behind any changes or updates to these assumptions
- Example: When reporting on the impact of emerging technologies on insurance risks, actuaries should disclose the sources of data, the assumptions made about technology adoption rates, and any limitations in their analysis
- Example: Actuaries can use sensitivity tables or scenario matrices to demonstrate how changes in key assumptions, such as interest rates or mortality rates, can impact the results of their valuations
Collaboration with other professionals
- Addressing emerging risks often requires collaboration between actuaries and other professionals, such as data scientists, risk managers, and subject matter experts
- Actuaries need to effectively communicate and collaborate with professionals from different disciplines to ensure a comprehensive and integrated approach to managing emerging risks
- Example: Actuaries may work with cybersecurity experts to develop scenarios and models for assessing the potential impact of cyber risks on insurance portfolios
- Example: Collaborating with medical professionals and epidemiologists can help actuaries incorporate the latest scientific evidence and expert opinions into their morbidity and mortality assumptions
Adapting to new reporting standards
- As the regulatory and accounting landscape evolves to address emerging risks, actuaries need to adapt their reporting practices to comply with new standards and requirements
- Actuaries should stay informed about changes in reporting standards, such as those related to climate risk disclosures or the treatment of complex insurance products, and update their reporting processes accordingly
- Example: The Task Force on Climate-related Financial Disclosures (TCFD) provides a framework for companies to report on their climate risk exposures and management strategies, which may require actuaries to enhance their climate risk reporting
- Example: The implementation of IFRS 17, a new international financial reporting standard for insurance contracts, requires actuaries to modify their valuation and reporting processes to ensure compliance with the new requirements
Professional responsibilities and ethics
- As trusted professionals, actuaries have a responsibility to maintain high standards of integrity, competence, and ethical conduct when dealing with emerging risks
- Actuaries must navigate the ethical challenges posed by emerging risks, such as balancing the interests of different stakeholders, managing conflicts of interest, and ensuring the appropriate use of data and models
Maintaining competence in emerging areas
- Actuaries have a professional obligation to maintain and enhance their knowledge and skills in areas relevant to their practice, including emerging risks
- Continuing professional development activities, such as attending conferences, participating in research projects, or pursuing additional education, can help actuaries stay current with the latest developments in emerging risk areas
- Example: Actuaries may attend workshops or seminars on topics such as data privacy, blockchain technology, or climate risk modeling to expand their knowledge and expertise
- Example: Participating in industry working groups or research committees focused on emerging risks can provide actuaries with opportunities to collaborate with peers and contribute to the development of best practices
Adhering to actuarial standards of practice
- Actuarial standards of practice (ASOPs) provide guidance on the appropriate techniques, considerations, and disclosures for actuarial work in various areas
- Actuaries must adhere to relevant ASOPs when dealing with emerging risks, ensuring that their work is performed with the necessary skill, care, and objectivity
- Example: ASOP No. 46, "Risk Evaluation in Enterprise Risk Management," provides guidance on the actuarial aspects of enterprise risk management, including the identification and assessment of emerging risks
- Example: ASOP No. 54, "Pricing of Life Insurance and Annuity Products," requires actuaries to consider the impact of emerging risks, such as changes in underwriting practices or policyholder behavior, when setting prices for these products
Balancing stakeholder interests
- Emerging risks can create conflicts between the interests of different stakeholders, such as policyholders, shareholders, and regulators
- Actuaries must strive to balance these competing interests and provide objective and impartial advice that promotes the long-term sustainability and fairness of the insurance system
- Example: When advising on the pricing of insurance products exposed to climate risks, actuaries must balance the need for risk-based pricing with considerations of affordability and availability for policyholders
- Example: Actuaries may face pressure from management to adjust assumptions or models to achieve desired financial outcomes, but they must maintain their independence and integrity in providing professional opinions
Recognizing limitations of expertise
- Emerging risks often involve complex and multidisciplinary issues that may extend beyond the traditional scope of actuarial expertise
- Actuaries must recognize the limitations of their knowledge and skills and seek input from other experts or professionals when necessary to ensure the accuracy and reliability of their work
- Example: When assessing the potential impact of a new medical technology on health insurance claims, actuaries may need to consult with medical professionals or biostatisticians to understand the clinical aspects and potential adoption rates of the technology
- Example: Actuaries should be transparent about the limitations and uncertainties associated with their models and avoid making definitive statements or predictions beyond the scope of their expertise
Opportunities for actuarial innovation
- While emerging risks pose challenges for actuaries, they also present opportunities for innovation and the expansion of actuarial skills and influence
- Actuaries can leverage their analytical expertise and problem-solving abilities to develop new solutions and contribute to the management of emerging risks in various domains
Developing new insurance products
- Emerging risks create demand for new insurance products and risk transfer solutions that address the evolving needs of policyholders and society
- Actuaries can play a key role in designing and pricing innovative insurance products, such as parametric insurance, usage-based insurance, or products tailored to specific emerging risk exposures
- Example: Actuaries may develop index-based insurance products that provide coverage for losses related to climate risks, such as droughts or floods, based on objective weather parameters
- Example: The increasing adoption
Key Terms to Review (16)
Big data analytics: Big data analytics refers to the complex process of examining large and varied datasets to uncover hidden patterns, correlations, and insights that can drive better decision-making. This process involves using advanced analytic techniques, such as machine learning and statistical analysis, to analyze vast amounts of structured and unstructured data generated from various sources. In the context of emerging risks and challenges, big data analytics can help actuaries identify trends and risks that traditional methods might miss.
CAS Standards: CAS Standards refer to the set of guidelines and best practices established by the Casualty Actuarial Society (CAS) for actuarial work, focusing on ensuring professionalism, ethical conduct, and quality in actuarial practice. These standards are particularly important as they help actuaries navigate the complexities of emerging risks and challenges in their field, allowing for informed decision-making and responsible risk assessment.
Climate change risk: Climate change risk refers to the potential negative impacts and uncertainties associated with the changing climate, including extreme weather events, sea-level rise, and shifts in ecosystems. This risk poses significant challenges for various sectors, including insurance and finance, as it affects asset values, liability exposures, and overall economic stability.
Cyber risk: Cyber risk refers to the potential for loss or harm related to technology infrastructure and the use of technology in a business context. It includes threats from cyber attacks, data breaches, and system failures that can lead to financial loss, reputational damage, and legal consequences. This risk has become increasingly important as more organizations rely on digital systems and data management, resulting in a complex landscape for risk assessment and management.
Data privacy issues: Data privacy issues refer to the challenges and concerns related to the collection, storage, and use of personal information by organizations. These issues encompass various aspects such as consent, security, and the potential for misuse of data, all of which are critical in a world increasingly reliant on data-driven decision-making and technology. As actuaries work with vast amounts of data, understanding these privacy challenges becomes essential for ethical practice and compliance with regulations.
Dynamic Financial Analysis: Dynamic financial analysis is a process that evaluates the financial health and risks of an organization over time, often incorporating various scenarios and forecasts to understand potential future outcomes. This approach allows actuaries and financial analysts to assess the impact of changing market conditions, regulatory environments, and emerging risks on the organization's financial stability and performance.
Enterprise Risk Management (ERM): Enterprise Risk Management (ERM) is a comprehensive framework for identifying, assessing, and managing risks that could impact an organization’s ability to achieve its objectives. It focuses on a holistic approach to risk management across all levels of the organization, considering both internal and external factors that may pose challenges or create opportunities for growth.
Healthcare cost trends: Healthcare cost trends refer to the patterns and changes in healthcare expenses over time, encompassing various factors that influence the cost of medical services, treatments, and insurance. Understanding these trends is crucial as they impact pricing, insurance premiums, and overall access to healthcare, highlighting the ongoing challenges in maintaining affordability and quality in medical care.
IFoA Guidelines: IFoA guidelines are a set of professional standards and best practices established by the Institute and Faculty of Actuaries to guide actuaries in their work and ensure high-quality actuarial practice. These guidelines address emerging risks and challenges in actuarial practice, helping actuaries navigate complex environments, adopt new technologies, and respond to the evolving needs of the financial services industry.
Insurtech impact: Insurtech impact refers to the influence and transformation brought about by technology innovations in the insurance industry, particularly in the way insurance products are developed, distributed, and managed. This impact is significant as it addresses emerging risks and challenges faced by traditional actuarial practices, leading to more efficient processes, improved customer experiences, and novel approaches to risk assessment and management.
Machine Learning: Machine learning is a subset of artificial intelligence that enables computer systems to learn from data and improve their performance over time without being explicitly programmed. This capability is increasingly relevant as actuaries face complex data patterns and emerging risks, enabling predictive analytics that can enhance decision-making processes in various areas such as risk assessment and pricing strategies.
Predictive Modeling: Predictive modeling is a statistical technique used to forecast future outcomes based on historical data and patterns. This method involves using mathematical algorithms and machine learning to analyze past behaviors and trends, allowing actuaries to make informed predictions about potential risks and future events. By identifying relationships within the data, predictive modeling aids in decision-making processes, especially when addressing emerging risks and challenges in the field.
Regulatory Compliance: Regulatory compliance refers to the adherence of organizations and individuals to laws, regulations, guidelines, and specifications relevant to their business processes. It ensures that companies operate within the legal framework established by governing bodies, which is crucial for maintaining trust, transparency, and accountability in financial practices. This compliance is especially vital in sectors like insurance and finance where risks must be managed appropriately.
Risk Management Framework (RMF): A Risk Management Framework (RMF) is a structured approach that organizations use to identify, assess, manage, and monitor risks in order to achieve their objectives. It provides a comprehensive process that enables decision-makers to understand risk exposure and implement strategies to mitigate potential negative impacts, especially in dynamic environments. The RMF is crucial in addressing emerging risks and challenges, allowing actuarial professionals to adapt their practices to evolving circumstances and uncertainties.
Scenario analysis: Scenario analysis is a strategic planning method used to evaluate and understand the potential impact of different future events or situations on an organization or system. It involves creating detailed narratives or models that describe various possible scenarios, enabling decision-makers to assess risks, opportunities, and uncertainties. This approach is crucial for actuarial practice, especially when dealing with emerging risks and challenges that may not have historical precedents.
Stress Testing: Stress testing is a risk management tool used to evaluate the resilience of financial systems and institutions under extreme conditions. It involves simulating adverse scenarios to assess potential impacts on capital, liquidity, and overall financial stability. This technique is crucial for understanding vulnerabilities and ensuring that organizations can withstand severe economic shocks.