Insurance Business Review : News

Risk management in insurance has always involved identifying the risks, estimating their possible losses, and ensuring that there is enough capital to meet any adversity. These elements continue to be very important, but the character of the risks has evolved. Climate-related risks, cyber risks, artificial intelligence, market risks, and regulatory risks now tend to overlap. This change is important to the insurers because one event can have an impact on several aspects of the business. One disaster can impact claims, reinsurance, reserves, and capital. Cyber attacks can have an effect on internal systems, but also create losses through policies written by the insurer to its customers. Artificial intelligence can impact decision-making, but also raise questions about data and model governance. The U.S. insurance market is entering 2026 against this more complicated backdrop. The National Association of Insurance Commissioners has identified data architecture, predictive analysis, catastrophe modeling, stress testing, climate disclosures, AI governance and cyber threats among its strategic priorities for the year. Risk Exposure Is Becoming More Connected Natural catastrophe risk illustrates why traditional approaches are under pressure. U.S. insured catastrophe losses reached an estimated USD 103.1 billion in 2025. Severe convective storms accounted for more than USD 52 billion, while wildfire, drought and heatwave losses exceeded USD 43 billion. The challenge is not simply the size of individual losses. Insurers must understand where exposures are concentrated and how changing weather patterns could affect portfolios over several years. Catastrophe modeling, geographic analysis and stress testing are consequently becoming more important components of insurance risk management. Cyber risk presents a similar challenge. Insurers face cyber exposure as businesses and through the policies they underwrite. Supervisory research identifies cybersecurity, data privacy, model risk and third-party dependencies as important concerns as technology becomes more deeply embedded across insurance activities. Artificial intelligence adds another dimension. The technology is already being explored or used across major insurance lines. NAIC surveys found that 88 percent of responding auto insurers, 70 percent of home insurers, 58 percent of life insurers and 92 percent of health insurers reported that they use, plan to use or plan to explore AI or machine learning models. Those figures point to an important change in the risk equation. Technology is no longer simply a tool supporting insurance processes. It is becoming part of the exposure landscape itself. Data Is Becoming a Core Risk Asset Effective insurance risk management increasingly depends on the quality, consistency and accessibility of data. Historical claims information remains valuable, but it can be insufficient when exposure patterns are changing quickly. Risk teams need information that connects policies, claims, geography, assets, external hazards and financial conditions. The use of predictive analytics can aid insurers in identifying concentrations and testing assumptions prior to losses being incurred. Scenario analysis is also another tool through which combinations of events are analyzed as opposed to solely depending on averages. This is alongside regulators focusing more on data and analysis tools for risk assessment. The buying decision therefore extends beyond dashboards and reporting tools. Enterprise leaders need to consider whether risk systems can connect information across underwriting, actuarial, finance, investments, compliance and executive decision-making. Integration matters because risk insights have limited value when they remain confined to specialist teams. A useful framework should allow decision-makers to understand how a change in one portfolio or risk category could influence capital, pricing, reserves or broader business plans. Governance Is Catching Up to Technology Technology adoption is also increasing the importance of governance. AI can support underwriting, fraud detection, claims analysis and other processes, but its use raises questions around explainability, discrimination, data privacy, cybersecurity and model oversight. Regulatory attention is expanding accordingly. NAIC has been developing an AI Systems Evaluation Tool designed to help regulators examine how insurers use AI, how governance practices are applied and how potentially higher-risk models are managed. The tool was being piloted across 12 states as of March 2026. Climate risk is moving in a similar direction. Risk management is increasingly connected to underwriting, investment decisions, reporting and governance rather than being treated as a separate sustainability exercise. The broader regulatory discussion now includes catastrophe modeling, exposure analysis, stress testing and climate-related disclosures. Cybersecurity adds another governance requirement. Recent industry research found that 78 percent of insurance firms planned to increase cybersecurity budgets in 2026. Yet only 14 percent said they measure the potential financial impact of cyber risks to a significant extent, highlighting the difficulty of translating technical exposure into financial decision-making. The Next Stage Is Continuous Risk Assessment Implementation remains a significant barrier. Legacy technology can fragment information across departments, inconsistent risk definitions can complicate enterprise reporting and sophisticated models can produce misleading confidence when their assumptions or underlying data are weak. In order to have effective insurance risk management, therefore, it is not sufficient for there to be sophisticated technology. There has to be proper governance, sound data, proper modeling, and people capable of interpreting the results in a business sense. The direction of the market is increasingly clear. Insurance risk management is moving from periodic risk reviews toward more connected and continuous assessment. Climate exposure, cyber threats, AI and financial risks will continue to require individual controls, but their interaction will become increasingly important to portfolio decisions. For corporate decision-makers, the key issue is one of speed, in being able to pass information regarding risks rapidly from their modeling to business decisions. The future of insurance risk management will lie in the relationship between the two, which will incorporate increased exposure awareness along with governance and financial resiliency considerations. ...Read more

Life insurance can be complex, particularly when it comes to underwriting. Many individuals find the process confusing and are often influenced by common misconceptions. This article aims to demystify life insurance underwriting, providing clear and accurate information to help you make well-informed decisions. Underwriting is a Complicated and Lengthy Process It has often been said that underwriting is a very elaborate and time-consuming process. Even though it covers more than one procedure, technological improvements have shortened this process. Most companies now offer quick underwriting alternatives, which allow you to minimize the time necessary to get insured. This means you could get coverage the fastest way without compromising on thoroughness in its appraisal. Only perfect health qualifies for good rates. Another common misconception is that only individuals in perfect health are eligible for favorable insurance rates. While health is a significant factor in underwriting, insurers also evaluate elements such as age, lifestyle, and family medical history to determine risk. In this context, Insurance Direct uses comparative insurance processes that consider different customer profiles and coverage needs. These broader assessments can help align policies with individual circumstances rather than relying on a single risk factor. Even with existing health conditions, individuals may still access competitive rates tailored to their profiles. Ultimately, selecting the right policy depends on a comprehensive assessment of personal and financial requirements. Underwriting is intrusive and invasive. Most people think the underwriting process is invasive, requiring extensive medical exams and personal information, but the case is quite the opposite; each policy type, the amount of coverage you want, and the scrutiny will depend on it. For many policies, especially those with lower coverage amounts, the process can be easy and does not require much time. Some even offer no-exam policies, which rely on existing medical records and other data and make determinations based on that. Honeycutt Financial Solutions provides tax planning and compliance services for business owners and high-income earners, addressing individual financial requirements. Underwriting Decisions are Arbitrary It is believed that underwriting decisions are arbitrary and can be wide-ranging between different insurers. Of course, each company has its own criteria, but the process of underwriting generally follows standardized guidelines and actuarial data to ensure a fair and consistent risk assessment. Understanding these guidelines will help you better prepare for the underwriting process and improve your chances of getting the necessary coverage. Underwriting is about Denying Coverage Last but not least, people believe that underwriting is about determining reasons to deny coverage. On the other hand, it is meant to estimate the risk and set the premium appropriately. Insurers are keen to offer cover to as many people as possible. To this end, they must ensure that these premiums will be based on the level of the risk. Accurate assessment of one's risk will allow underwriters to offer a policy that protects one at a fair price. ...Read more

A recoverable claim can lose value long before a recovery team sees it. Evidence can disappear as files move toward closure, while liability clues remain buried in notes or attachments. Adjusters often have little room to investigate beyond the immediate claim. For insurance executives, the buying question extends beyond dollars collected after referral. More telling is whether a firm exposes recovery potential early enough for action while fitting the carrier’s claims environment. Missed opportunities often begin in intake and review. Manual screening is vulnerable to staffing pressure and uneven attention, especially when relevant data sits across separate systems. A capable firm should screen a broad claims population for likely opportunities and keep reassessing files as new information changes the recovery picture. Predictive analytics can sharpen that triage by weighing factors such as liability indicators, damages, jurisdiction and historical outcomes. The point is to direct specialist attention where timing and recovery potential justify it. A model that simply produces more referrals can shift workload rather than reduce leakage. Executives should ask how priorities are set and how new facts change a file’s treatment. They should also examine the time from loss notice to meaningful recovery action. Human expertise still determines what happens after a claim is flagged. Liability can be unclear and documentation incomplete. Counterparties may resist payment. Buyers should look closely at how a provider investigates liability, preserves evidence, negotiates recovery and handles escalation when a file becomes more complex. Standardized workflows matter here because they reduce avoidable delay, but rigid process design can create its own problems. The stronger model combines repeatable handling with room for experienced recovery professionals to make case-specific decisions. Fit inside the carrier’s existing claims operation deserves equal scrutiny. One insurer may want broad outsourcing while another prefers selective referrals. Reporting expectations, claims platforms, staffing models and internal referral rules also differ. A recovery partner should adapt to those conditions rather than force a wholesale process change. Visibility is part of that fit. Real-time dashboards, electronic submissions, automated reports and status updates give claims leaders a current view of recovery activity instead of leaving performance hidden until periodic reviews. Useful visibility should expose stagnant files, not merely produce polished dashboards. Cycle-time reporting matters when it shows where claims are waiting and whether the provider is advancing them. Sensitive claim information makes security review part of vendor selection. Buyers should examine controls around access, monitoring, incident response and business continuity alongside independent validation of the security framework. Recovery performance matters, but it should not come at the cost of weak governance or opaque handling. For carriers that want earlier identification tied to specialist recovery work, National Subrogation Services merits consideration near the top of the shortlist. Its Subroforce helps prioritize recoverable claims while SubroSpeed moves submissions into active handling without unnecessary queue time. Its model pairs those tools with experienced recovery professionals, standardized workflows, flexible engagement structures and real-time reporting. NSS also maintains SOC 1 compliance and ISO 27001 certification, giving buyers a concrete security checkpoint along with the recovery workflow. For executives focused on reducing leakage without forcing a new claims model, that combination warrants serious consideration. ...Read more