The insurance industry in 2025 faces challenges that build on the difficulties of recent years. Economic pressures, escalating claims costs, and the increasing frequency of extreme weather events are putting brokers, agents and insurance companies in uncharted territory. With homeowners' premiums projected to rise by more than 15% in high-risk regions and auto premiums set to climb 5%, all of us in the industry are forced to reassess our strategies and client engagement.

To address this shift, VIU by HUB's Outlook and Personal Insurance Market Rate Report has identified three pivotal trends shaping the landscape.

1. Extreme Weather Is Now a Constant Threat

We're no longer dealing with seasonal risks – natural disasters are happening year-round. In 2024, the U.S. experienced $62 billion in insured losses - 70% above the 10-year average. Hurricanes, floods and wildfires are becoming more frequent, pushing carriers to reconsider their exposure. Some are even exiting high-risk markets entirely, leaving clients to scramble for limited and often costlier coverage options.

For brokers and agents, this means playing a more advisory role. Clients are not just looking for policies; they need guidance on how to protect what matters most. Helping them navigate shrinking coverage options and rising costs is now part of the job description.

2. Rising Costs Are Reshaping Consumer Expectations

Soaring costs for labor, materials and other expenses are driving premiums higher across all coverage lines. In some regions, the cost of homeowners insurance has become prohibitive, with 8.5% of mortgage holders opting to go uninsured. This affordability crisis not only affects consumers but also poses risks for lenders and real estate professionals as potential home sales falter due to insurance hurdles.

As trusted advisers, we need to help clients find smart, affordable coverage solutions and take care of them throughout their protection life cycle. Embedding full-service digital insurance brokerage platforms, such as online comparison tools that offer end-to-end insurance solutions, can empower clients with more choices and price transparency while streamlining the purchasing process. Companies across industries, including relocation service providers, employee benefits solutions and financial institutions, are adopting this approach to create a seamless, integrated experience that keeps clients protected.

3. Strategic Partnerships Are Key to Industry Resilience

In fact, 45% of companies are planning to form new alliances within the next two years. Even more so, embedding insurance solutions into customer-facing platforms is proving to be a game-changer.

Take a mortgage servicing company, for example, which integrates home insurance into the mortgage application process. This approach not only simplifies coverage access for homeowners in disaster-prone areas but also strengthens customer satisfaction and can create revenue streams for the mortgage provider.

Plus, it is a two-way street. Brokers and agents can leverage partnerships to enhance their value propositions with their clients. Offering integrated solutions builds trust and long-term relationships while addressing the evolving needs of the modern consumer.

What This Means for Brokers, Agents, and Insurance Companies

Adapting to these trends requires a combination of strategy, flexibility and innovation. Here are some key ways to stay ahead and better serve clients:

1. Prioritize Education and Transparency:

Clear, actionable insights build trust. Help clients understand their risks and coverage options.

2. Leverage Technology to Provide Tailored Solutions:

Digital tools can streamline the insurance quoting process, tailor recommendations and provide more value, enhancing the client experience and improving retention.

3. Embrace Strategic Partnerships:

Collaborate with organizations that help you deliver embedded insurance solutions when and where clients need them most.

4. Address Affordability Concerns:

Clients will appreciate your ability to find cost-saving strategies, such as bundling policies or adjusting deductibles without sacrificing protection.

5. Stay Ahead of Climate-Driven Risks:

Inform and help clients prepare for increasing weather-related perils by clearly communicating potential risks and recommending relevant coverages—like flood insurance—even when they are not mandated but still pose a significant threat.

The challenges of today's landscape are immense, but they also present opportunities. By planning in advance, employing technology, and prioritizing meaningful client relationships, brokers, agents and insurance companies alike can thrive in this rapidly changing environment.

According to McKinsey's Global Insurance Report 2025, "the world's insurers are enduring a particularly volatile age." 

The insurance industry is at a crossroads in terms of public perception. Recent tragic events highlight this reality, from the cancellation of policies just prior to the LA fires and the subsequent request by carriers for rate increases to the dire situation in Florida, where carriers are leaving the state en masse as property insurance costs spiked 72% in the last five years.

While some insurers have made strides in terms of their communication with policyholders, far too many are lagging behind, waiting to see what the others will do. This leaves a void that the public is filling with stories of abandonment, greed, profit over people, and a host of other negative descriptors.

What the insurance industry needs now, more than ever, is to realize that things must change. Immediately.

Given the current chaos, insurers should be a trusted beacon that promises to be there in insureds' darkest hour. That starts with greater transparency and increased communication with constituents.

I remember the days when meeting with your insurance agent was the norm, When disaster struck, they were just a phone call away. Too often today, a question or complaint results in an automated response that doesn't even acknowledge what the person receiving the communication is going through.

For all of the benefits and convenience that technology has provided—from easy access to information online to streamlined claims and AI chatbots—it has also weakened the personal connection between insurers and their insureds. While we can't return to those days, there are ways for insurers to be more transparent, make those critical connections and rebuild trust.

One approach is to hold regular opportunities for insureds to ask questions, discuss concerns, and even air grievances before they boil over and create a pervasive sense of mistrust. Right now, many consumers feel there is no path to having a substantive dialogue with what should be a trusted adviser. While such events must be well-managed, it is critical that they be done live and with real people.

Insurers also need to act as a true partner and resource, beyond just processing claims. This means sharing with policyholders where they can turn to for immediate assistance and providing regular status updates, so they are informed and know what is actually being done.

It is also more important than ever for insurance leaders to be highly visible on the frontlines with information on how they are responding to consumer crises as well as addressing the very real challenges the industry is facing. If mistakes were made, address them. By the same token, when there is misinformation about what insurers are doing, correct them. While consumers are unlikely to feel sympathy for the industry, they should understand the financial straits that have insurers at the risk of failure.

Recent months have tested the resilience of this sector like no other in recent memory. But I believe in the future of the insurance industry and its ability to grow and improve despite these unpredictable times. By offering greater transparency and delivering communications that fulfill promises to insureds, I believe the insurance industry can once again reclaim their position as a trusted partner.

In an industry as dynamic and tightly regulated as insurance, maintaining compliance has always been a critical necessity and logistical challenge. Compliance has only become more important over the past few years, with the regulatory landscape having gone through a dynamic shift, fueled by evolving legislation, consumer demands, and the complexities of a globalized marketplace. As we look ahead in 2025, the confluence of automation technology, artificial intelligence (AI), and generative artificial intelligence (GenAI) looks poised to redefine how insurers approach compliance—turning it from a reactive cost center into a proactive driver of efficiency, accuracy, and trust.

The Challenge: Keeping Pace With Complexity

Insurance compliance has always been intricate, requiring insurers to navigate diverse requirements across jurisdictions. In recent years, this complexity has been exacerbated by digital transformation, global economic pressures, and increasing scrutiny from regulators.

To address these issues, insurance companies are keen to adopt GenAI to improve business processes and derive valuable insights. However, successful adoption depends on change management practices and data readiness. For this, insurance companies must focus on building internal tools to foster a productive culture of AI adoption and enhance efficiency. This would include implementing data governance frameworks, creating analytics-ready data sets, and organizing data effectively across departments.

Currently, several insurance organizations still maintain records on paper that have not been scanned and further, may not have protocols in place for data use and compliance. Ensuring that proper data management frameworks are laid down can enable improved compliance, better decision-making capabilities, and insights. However, what is clear is that the adoption of AI requires companies to evaluate its benefits and challenges continuously. As the technology evolves, industries must stay on top of the changes and re-evaluate strategies to achieve desired results. Adopting AI does require a fundamental shift in business operations and culture, but it can unleash innumerable benefits for the insurance industry.

The AI & Automation Advantage

Let us take a closer look at some use cases of these technologies to see what they are able to rethread, improve, and transform.

Fraud detection: At the end of the day, compliance isn't just about adhering to regulations; it's also about safeguarding against fraud. AI algorithms can identify patterns that elude traditional rule-based systems, helping companies identify fraudulent activities before they result in large financial losses. For example, a large, U.S.-based property and auto owner insurance provider deploys a fraud detection system that uses machine learning to analyze transaction data, thereby reducing false positives in fraud alerts.

Personalization and protection for customers' data: By leveraging customer data, AI can be used by insurers to develop personalized products and services that better meet individual customer needs. Automation, meanwhile, can help monitor data usage, flagging unauthorized access or breaches to maintain trust and avoid reputational damage.

Smart audits: Within the AI ecosystem, GenAI has multiple uses in auditing: from knowledge management and enhanced productivity to more effective process flows. It can parse vast amounts of information, create diagrams, and communicate with humans in several ways, making it a valuable tool for auditors.

However, as with any new technology, there are concerns about GenAI. Audit firms must weigh the benefits and challenges of GenAI thoughtfully. Although it is free and accessible, innovative uses are emerging rapidly, meaning that constant evaluation is necessary to ensure effective use of the technology while avoiding potential misuse.

Legacy system solutions: AI can also extract data from legacy systems while using application programming interfaces (APIs) to feed the data into AI solutions. Regulatory technology (regtech) solutions, powered by AI, are in this sense indispensable. These tools aggregate and interpret regulatory updates, automating and ensuring that policies and procedures remain current. For insurers operating across multiple geographies, this is a game changer. Tools like BeInformed, ComplyAdvantage, and RegTech for Regulators Accelerator (R2A) automate regulatory monitoring, helping insurers remain compliant and agile in a shifting landscape.

Faster claims processing: AI can automate routine customer inquiries and claims processing, allowing insurers to provide more efficient and quicker service to their customers.

Ethical Concerns

Ethical and responsible usage concerns persist around bias, accountability, and data integrity. To alleviate these concerns, proposed regulations are emerging, including trusted AI umbrellas.

Recent developments, such as the use of deepfakes, are fueling legislative and regulatory debates focused on accountability around AI usage and enhanced consumer protection. The future of AI in the insurance industry is promising, but businesses need to take crucial steps before realizing the benefits. Establishing proper frameworks, planning for data usage, and laying down a clear road map for internal adoption will be crucial to take full and safe advantage of the technology's potential.

Preparing for 2025 and Beyond

Looking ahead, I foresee several emerging trends set to make a significant impact on compliance in insurance. The industry is progressing from GenAI pilots to full-scale production. Advancements in intelligent document processing (IDP) will accelerate key insurance operations, from agent onboarding to claims processing. Insurers are also embracing agentic AI and digital workers, which automate complex workflows and enhance operational efficiency.

One of the most important trends will be the rise of explainable AI (XAI), which ensures that decisions made by AI systems—whether in pricing, underwriting, or claims handling—are transparent, fair, and auditable. This is critical not only for regulatory compliance but also for building trust with customers.

Privacy-enhancing technologies (PETs) and improved data governance will allow insurers to comply with stringent privacy regulations like General Data Protection Regulation (GDPR) while enabling secure data sharing across various entities. Real-time risk assessment models will provide compliance risk scores, allowing compliance teams to better monitor emerging risks and prevent non-compliance incidents.

As we can see, the next frontier in insurance compliance lies in these intelligent technologies that not only streamline operations but make them smarter and more responsive to emerging regulatory challenges. Insurers must approach AI adoption strategically, investing in scalable infrastructure, as these tools require robust data ecosystems. Insurers should also prioritize building secure, interoperable systems capable of supporting both AI and automation. Facilitating collaboration between compliance, IT, and business units will be essential to avoid silos, ensuring seamless implementation and organizational buy-in.

The cost of healthcare continues to escalate, placing a significant financial burden on all stakeholders in the self-insurance ecosystem – from employers and insurers to third-party administrators (TPAs) and stop-loss carriers. With healthcare costs projected to increase 5.8% in 2025 – the third consecutive year exceeding 5% growth – managing expenses while maintaining plan effectiveness is becoming increasingly challenging to plan sponsors and fiduciaries.

Several factors contribute to rising costs, including specialty drug prices, high-cost medical claims and billing inefficiencies. Specialty drugs, while only a small fraction of total prescriptions, now account for over 54% of prescription drug spending. Additionally, overuse of medical services, excessive hospital stays and administrative complexities drive up costs without necessarily improving patient outcomes.

To mitigate financial strain, employers and payors must adopt cost-containment measures that ensure financial sustainability without compromising care quality. Three effective strategies include claims negotiation, repricing by preferred provider organization (PPO) networks and line-item bill review – each playing a critical role in reducing waste, improving billing accuracy and resolving disputes efficiently.

Challenges in Managing Healthcare Costs and Plan Performance

The financial impact of inaccurate or excessive medical billing is substantial, with studies estimating that billing errors, duplicate charges and incorrect coding account for 7-10% of all healthcare payments. These errors result in significant overpayments, making it essential for payors to implement rigorous review processes to ensure that medical bills accurately reflect services rendered.

High-cost medical claims are another major concern, particularly as multimillion-dollar claims become more common. Recent reports indicate that claims exceeding $1 million have surged 45% over the past five years, primarily due to:

• Expensive specialty drug treatments for chronic conditions and rare diseases.
• Extended hospitalizations and complex surgical procedures.
• High-cost therapies, such as cancer treatments and cardiovascular interventions.

In addition to high-cost claims, the administrative burden of resolving disputes adds another layer of complexity. The No Surprises Act, designed to protect patients from unexpected medical bills, introduced an Independent Dispute Resolution (IDR) process to resolve payment disagreements between insurers and providers.

However, the system has been overwhelmed – nearly 490,000 disputes were submitted between April 2022 and June 2023, with 61% remaining unresolved. These delays can lead to prolonged financial uncertainty for payors and providers alike.

Without an effective strategy in place, these challenges threaten the financial stability of employer-sponsored health plans, leading to higher premiums, increased cost-sharing for employees and constrained budgets for businesses.

How to Reduce Spending and Improve Plan Performance

Claims Negotiation: Lowering Costs on High-Expense Claims

Claims negotiation helps employers and payors secure lower reimbursement rates for out-of-network claims and high-cost medical treatments. By working directly with providers, negotiators can identify billing errors, leverage benchmark pricing data and reach mutually beneficial agreements that align with industry standards. Experienced professionals with negotiating expertise can achieve significant savings. Strong relationships with providers help ensure rapid resolution of issues or billing disputes.

Providers often bill more than is appropriate for the services they deliver, leading to excessive costs. When this occurs, self-insured clients rely on expert negotiators to secure discounts on out-of-network claims and when permitted, larger in-network claims.

The process begins with a careful review of each claim to identify errors or inconsistencies. Using published databases and proprietary historical data, negotiators establish a fair payment amount as the basis for discussions. Armed with this data, negotiators can engage providers directly to secure a signed agreement, ensuring the negotiated payment is accepted in full.

By integrating structured negotiation strategies into claims management, employers and payors can reduce financial waste, prevent excessive overpayments and achieve sustainable cost savings while maintaining objective and reasonable provider compensation.

Repricing PPO Networks: Lowering Costs on All Size Claims

Many providers have agreements with PPOs to accept discounts on their out-of-network claims. When negotiators are unable to secure agreements for discounts on large claims, payors access these PPOs to achieve reductions in the amount to pay the providers. Payors do the same for smaller claims. 

Line-Item Bill Review: Identifying and Preventing Billing Errors

A comprehensive line-item bill review enhances accuracy, detects errors and minimizes unnecessary expenses. While most medical bills are accurate, errors in claims processing—such as data entry mistakes, incorrect billing codes and charges exceeding usual and customary (U&C) rates—can inflate costs and result in overpayments.

For large out-of-network claims and select in-network claims, employers and payors can request Line-Item Bill Reviews (LIR) to verify billing accuracy and ensure appropriate reimbursement rates. This process safeguards against financial waste by identifying errors and inconsistencies before payments are finalized.

LIRs are detailed audits conducted by experienced nurse coders and billing experts to detect:

• Duplicate charges for the same procedure.
• Improper modifiers that increase reimbursement rates incorrectly.
• Inflated medication or treatment costs due to incorrect quantities.
• Unbundled services billed separately instead of as a single package.

By flagging discrepancies, this review ensures fair and accurate provider payments while preventing unnecessary employer and payor expenses.

For out-of-network claims, bill reviews validate whether charges align with U&C rates for similar services in the same geographic area. Through detailed audits, payors can:

• Ensure charges reflect industry standards and prevent inflated costs.
• Identify unnecessary procedures that lack clinical justification.
• Support appeals and provider negotiations to correct billing errors before payment is finalized.

With healthcare claim costs rising, LIR offers a proven, data-driven method to eliminate waste, enhance financial oversight and ensure fair reimbursement practices. Integrating this process into claims management workflows helps reduce errors and improve plan performance.

By integrating negotiation strategies and data-driven decision-making, employers and payors can minimize disputes, reduce arbitration reliance and promote equitable payment resolutions – ultimately enhancing financial stability and operational efficiency.

Moving Forward: Strategies for Sustainable Cost Management

As healthcare costs continue to rise, claims negotiation, LIR and IDR have become essential tools for employers and payors looking to control expenses while maintaining financial stability. Implementing these strategies allows organizations to negotiate fair provider payments, reduce overcharges and eliminate unnecessary spending.

Billing accuracy through comprehensive audits helps prevent overpayments, ensuring that only valid claims are processed. Additionally, efficient dispute resolution mechanisms minimize delays and reduce financial uncertainty, allowing payors to manage complex claims with greater confidence.

A data-driven approach to claims management enables employers and payors to protect financial resources, maintain plan performance and promote equitable healthcare reimbursement. By leveraging expert negotiation, rigorous auditing and structured dispute resolution, organizations can navigate the challenges of rising healthcare costs while ensuring a cost-effective and sustainable approach to health plan management.

The insurance industry is simmering under intense pressure. Rising regulations, relentless litigation, and the accelerating demands for technology are turning up the heat. As costs climb, both insurers and policyholders are feeling the burn.

The Simmering Regulatory Pressures

New regulations are like the first bubbles forming at the bottom of the pot - early warnings of a boiling point ahead. Insurance regulation isn't new, but an increasing number of proposed bills are reshaping the industry. Texas’ Senate Bill 1246, for example, could create a state-run auto insurance program, while Washington’s proposed legislation would mandate that insurers pay restitution directly to policyholders for violations.

While these policies aim to protect consumers, they come at a cost. Insurers must invest more in compliance––hiring staff, retaining legal counsel, upgrading technology, and restructuring workflows to meet stricter reporting requirements. What sounds like a win for affordability could, in reality, push premiums even higher.

Litigation: Turning Up the Heat

If regulation is the slow boil, litigation is the roaring fire underneath. The surge in high-stakes class actions, tort cases, and escalating legal disputes has driven litigation costs to records. The top 50 carriers in the U.S. now spend an average of $500 million annually on legal expenses.

A major accelerant? Third-party litigation funding, a $17 billion industry that fuels more lawsuits by financing plaintiffs in exchange for a cut of potential settlements. While this practice aims to help individuals pursue justice, it has also contributed to skyrocketing legal costs and increasingly aggressive litigation strategies. Every new lawsuit forces insurers to allocate vast reserves for potential payouts - funds that could otherwise fuel innovation or enhance customer service.

The National Association of Insurance Commissioners (NAIC) reported that these legal expenses are creating a domino effect where rising costs are passed on to consumers. For example, average personal injury verdicts alone surged by 319% over the past decade, from $39,300 in 2010 to $125,300 in 2020. As litigation grows more aggressive, the pressure inside the industry's boiling pot continues to rise.

The Technological and Cybersecurity Pressures: A Rapid Boil

Beyond regulation and litigation, the insurance industry faces another unavoidable expense: technology investment. AI, machine learning, and automation promise efficiency but bring with them the costs for integration, upgrades and staff training.

Meanwhile, cyber threats are adding another layer of financial strain, with premiums for cyber insurance rising 26% in 2021 - the highest increase across all insurance lines. Stricter regulations further drive up expenses, forcing insurers to manage costs to stay ahead of an evolving risk landscape. The pot isn't just boiling—it's threatening to spill over.

The Spillover Effect

When the heat becomes too much, something has to give. Insurers are tightening their underwriting standards, limiting coverage options and raising premiums to offset rising costs. The ripple effect is hitting consumers and businesses hard.

Take auto insurance. The national average for full coverage is expected to reach $2,638 in 2025—pricing more families and businesses out of adequate protection. The industry, weighed down by compliance, litigation and increasing risk exposure, is at a breaking point.

Lowering the Temperature: A Smarter Approach

The industry doesn't have to let this pot boil over. Insurers can reimagine their operations with smarter, more efficient systems. By leveraging automation to reduce administrative overhead, implementing AI-driven underwriting models, and improving transparency in claims processing to enhance customer service, insurers can relieve some of the pressure.

Cost efficiency isn't just about trimming expenses—it's about managing the heat. Insurers that invest wisely can keep the pot from boiling over, finding ways to relieve pressure without scalding their bottom line. Those who ignore the rising temperature? They'll be the ones left scrambling when things start to spill over.

In an industry where 70% of digital transformations fail to meet their objectives, it's time to fundamentally rethink how we structure, deliver, and measure professional services in insurance.

For decades, the professional services model has remained largely unchanged: Assemble subject matter experts, bill by the hour, and measure success by project completion rather than value creation. This model has become increasingly misaligned with the realities of today's technology landscape.

The Value-Based Pivot

Consider this scenario: An insurer faces a $50,000 problem—perhaps streamlining underwriting workflows or reducing claims leakage. Traditionally, this would translate into a statement of work detailing X consultants at Y hourly rate for Z weeks.

But in the AI-cloud era, this equation no longer computes.

If technology can solve in hours what once took weeks, why should clients pay for the historical time commitment rather than the value delivered? More importantly, if a solution generates $250,000 in value against a $50,000 problem, shouldn't the compensation model reflect this outcome rather than the inputs?

Insurance Transformation: The Data Reality

Our industry research reveals a sobering truth: 84% of insurance transformation initiatives exceed budgets while only 28% deliver their promised value. This disconnect isn't merely a failure of execution—it's a failure of our fundamental approach.

The most successful transformations in our benchmark data share a trait: They define success in terms of concrete business outcomes (reduced combined ratios, improved customer retention, decreased time-to-quote) rather than technology implementation milestones.

The Path Forward

For insurers and service providers alike, three shifts are essential:

1. Value-based contracting: Define compensation structures tied directly to measurable business outcomes, not hours worked.
2. Solution-agnostic delivery: Free providers to leverage the optimal mix of human expertise, AI capabilities, and cloud technologies without artificial incentives to maximize billable hours.
3. Outcome measurement: Develop sophisticated metrics that track value creation rather than activity completion.

A Real Conversation Happening Now

Currently, discussions with a Top 10 property and casualty insurer revolve around a claims optimization challenge they estimate at $2.3 million annually. The traditional approach would involve a 12-month road map with a team of eight to 10 specialists billing hourly.

Instead, a different approach is possible: a value-based arrangement creating an AI-powered claims triage solution with compensation directly tied to demonstrable reductions in leakage. The projected delivery would be 14 weeks rather than 52, with a smaller team supplemented by purpose-built AI models.

Analysis suggests this approach could deliver a 23% reduction in claims handling costs and 14% improvement in customer satisfaction scores. The insurer's leadership is genuinely intrigued—they've never procured services this way, but the risk/reward profile is compelling.

What's particularly revealing about these discussions is the organizational friction around measurement. The procurement team wants hourly rates; the business leaders want outcomes.

The Imperative for Change

As insurance leaders, we must ask ourselves: Are we still buying and selling professional services based on how business operated in 2000, or are we aligned with the value-creation possibilities of 2025?

The insurance industry has long discussed becoming more agile, innovative, and customer-centric. Perhaps the most profound step toward that future isn't a technology implementation but rather a fundamental reshaping of how we structure the relationships between those who need transformation and those who enable it.

What's your perspective? Is your organization still procuring based on hours or on outcomes?

In an era where digital transformation is reshaping industries, insurance companies are under mounting pressure to modernize their IT infrastructure and build greater agility while maintaining stringent regulatory compliance and ensuring operational resilience. One of the most effective solutions for facilitating this shift is the Cloud Landing Zone—a structured, pre-configured cloud environment that enables insurers to securely and efficiently migrate to the cloud.

Cloud adoption in the insurance industry has accelerated significantly, with 85% of P&C insurers leveraging cloud infrastructure now compared with under 30% in 2020. However, while many insurers have embraced cloud technology, the transition of core operations such as underwriting, claims, and billing remains a work in progress, with more than half of insurers having only partially migrated core functions. The industry is expected to continue this shift, with cloud services and applications investment projected to grow at a 23% clip through 2028.

For many insurance executives, cloud adoption is no longer a question of "if" but "how." The industry is increasingly recognizing that traditional IT systems cannot keep pace with evolving customer expectations, digital opportunities, regulatory demands, and the competitive landscape.

Moving to the cloud can be a complex endeavor, especially for major migrations, which require meticulous planning, strong governance, and robust security measures. This is where Cloud Landing Zones provide significant value to insurance companies, offering a structured and secure framework for cloud adoption.

Understanding Cloud Landing Zones

A Cloud Landing Zone is essentially a blueprint for cloud adoption. It provides insurance companies with a predefined, secure, and scalable environment in which to deploy cloud-based workloads. Designed to ensure consistency across an organization's cloud infrastructure, a Landing Zone includes critical elements such as account structure, networking, security, identity management, and compliance controls.

Instead of starting from scratch with each cloud migration strategy or application, insurance firms can leverage a Cloud Landing Zone to streamline the process. This approach not only reduces onboarding time but also ensures that security and compliance frameworks are integrated from the outset, rather than being retrofitted later—a crucial factor for an industry where regulatory compliance is paramount.

Leading technology providers offer Cloud Landing Zone solutions to help organizations efficiently move to the cloud era. Amazon Web Services (AWS) provides the AWS Control Tower as an accelerator; Microsoft Azure offers the Azure Landing Zones architecture as part of its Cloud Adoption Framework and implementation accelerators; and Google Cloud Platform (GCP) provides structured guidance for designing and implementing landing zones, with a focus on identity management, resource organization, and security policies. These frameworks streamline cloud adoption while ensuring best practices in security, compliance, and operational efficiency. However, their predefined approaches may require adjustments to fully align with your company's specific needs.

Guidewire provides core systems solutions for the P&C insurance industry through its Guidewire Cloud, a platform hosted on Amazon Web Services (AWS) that enables insurers to manage underwriting, policy administration, billing, and claims. While Guidewire Cloud serves insurance operations, Cloud Landing Zones can complement this by offering a framework for integrating additional third-party cloud-hosted applications and services.

Why Insurance Companies Are Turning to Cloud Landing Zones

The insurance industry is increasingly adopting Cloud Landing Zones for a number of compelling reasons. First and foremost, security and compliance. Insurance companies handle vast amounts of sensitive customer data, from personally identifiable information (PII) to financial records. Ensuring that this data is stored and managed securely while complying with strict industry regulations such as the California Consumer Privacy Act (CCPA), the Gramm-Leach-Bliley Act (GLBA), GDPR, and NAIC guidelines, and state insurance solvency requirements is a formidable challenge. Cloud Landing Zones address this by embedding security best practices and regulatory requirements into the infrastructure from the start.

Additionally, scalability and operational efficiency are key drivers. Traditional IT environments often struggle to support the rapid scalability required to meet fluctuating demands. With a Cloud Landing Zone, insurers can dynamically scale their operations, ensuring they have the necessary infrastructure in place to handle peak loads, such as during natural disasters when claims processing spikes.

Another crucial factor is governance and cost control. Cloud Landing Zones provide built-in guardrails that help organizations manage their cloud resources efficiently, preventing cost overruns and optimizing cloud spending. Insurance executives are well aware of the financial implications of cloud mismanagement, where unchecked resource provisioning can lead to unnecessary expenditures. With a Landing Zone, usage policies and budget constraints can be predefined to align with financial goals.

The Role of Automation and Standardization

Cloud Landing Zones streamline cloud deployment by automating security, compliance, and operational tasks. Automation reduces human error, a major cause of security risks and compliance breaches, while standardizing configurations across cloud environments ensures consistency and efficiency.

A well-structured Cloud Landing Zone includes multi-account architecture for segregating business functions, security and compliance controls with predefined policies, network configuration using virtual private networks (VPNs) and firewalls for workload isolation, and centralized monitoring to track activities and ensure compliance.

By automating these processes, insurers can improve efficiency, lower costs, and focus on innovation rather than IT maintenance.

Real-World Impact: How Insurers Are Benefiting

For insurance companies that have already adopted Cloud Landing Zones, the benefits are tangible. Firms that previously struggled with slow deployment cycles now find themselves able to launch products and services faster. The ability to integrate advanced analytics, artificial intelligence, and machine learning tools into cloud environments has further enhanced insurers' ability to assess risk, improve customer experiences, and streamline claims processing.

Take, for example, a multinational insurance provider that moved its operations to the cloud using a Cloud Landing Zone. Before the migration, the company faced challenges with siloed data, inconsistent security policies, and high infrastructure costs. By implementing a Cloud Landing Zone, they established a unified, secure, and scalable environment, reducing deployment times from weeks to days and achieving a 30% reduction in operational costs.

Moreover, as insurers expand into digital ecosystems, partnerships with insurtech firms, third-party data providers, and cloud-based service vendors are becoming more common. Cloud Landing Zones provide the structured foundation necessary for seamless integration with these partners, enabling insurers to rapidly innovate and adapt to market changes.

Looking Ahead: The Future of Cloud in Insurance

The adoption of Cloud Landing Zones is not just a passing trend—it is a strategic imperative for insurers seeking to remain competitive in a rapidly evolving landscape.

According to a recent survey on AI from Sollers Consulting, as insurers continue their cloud transformation, AI will play an increasingly central role in underwriting, claims processing, and compliance. However, many insurers struggle with adapting AI to existing IT landscapes, workflows, and user interfaces. Without robust planning, complexity can spiral, leading to higher costs and inefficiencies. Cloud Landing Zones provide a structured foundation to integrate AI-driven capabilities more effectively, ensuring that insurers can innovate without disrupting core operations or incurring unnecessary expenses. As artificial intelligence, big data analytics, and digital customer experiences continue to shape the industry, cloud infrastructure will play a central role in enabling these advancements.

For insurance executives, the decision to implement a Cloud Landing Zone is a forward-looking investment in agility, security, and long-term sustainability. By embracing this structured approach to cloud adoption and maintenance, insurers can future-proof their operations, mitigate risk, and unlock opportunities for innovation.

In the commercial insurance industry, business can be segmented into two distinct archetypes – complex and flow – which require different methodologies for underwriting and processing insurance policies. As middle market business becomes increasingly consolidated in the broker space and sought after in the large carrier space, approaching each risk across the complexity spectrum with the appropriate operating model will be critical to competing effectively and maintaining a healthy expense ratio. Getting this right will be a ticket to growth.

Complex business refers to insurance that undergoes desk underwriting, where an underwriter plays an active role in risk assessment, form selection, and pricing. The underwriters manage specialized risks with complex wording and coverages, navigate across multiple jurisdictions, and handle large limits and capacity. Complex business is typically commercial business distributed through brokers via individual submissions.

Flow business is characterized by automation and technology-enabled processes, with underwriting done primarily through proprietary platforms, portals, or out-of-the-box SaaS solutions. Underwriting operations and decisions are surfaced with little to no support from human underwriters, as the end-to-end process is fully automated for straight-through processing (STP). Industry-leading flow platforms efficiently handle large volumes of submissions via application programming interfaces (APIs) and portals and provide responsive quote turnaround times, while still delivering bespoke customer interactions. Flow business can be distributed to customers through various channels, including brokers, agents, alternative distribution channels, partner organizations, or direct-to-consumer (DTC).

Challenges in the Insurance Flow Segment

The flow segment of the insurance industry represents a $350 billion global market, which is primarily composed of small to medium enterprises (SMEs). This segment of the industry has historically been underserved by large carriers due to the high cost of booking this business manually and technology constraints preventing them from leveraging STP. As a result, SMEs face limited insurance offerings despite accounting for approximately 90% of businesses worldwide.

Low-touch carriers, such as Hiscox and The Hartford, have established themselves as leaders within the SME business segment. As new entrants in the market, small carriers and insurtech firms were able to build technology stacks from the ground up geared toward serving the SME segment of the market. These low-touch carriers typically provide coverage for lines such as commercial property, general liability, and professional liability, which involve relatively standard risks and straightforward underwriting criteria. These lines may also have higher transaction volumes but lower individual premiums, making them less attractive for larger carriers with higher operational costs.

Established insurance carriers have the expertise to understand the underlying risks and process policies in this segment, but they lack the IT infrastructure to do so efficiently. Studying the blueprint laid out by new entrants can provide valuable insights for larger carriers. By understanding the needs of the flow segment and strategically investing in flow-enabling technology, large carriers can efficiently serve this market.

While flow business strategies prove highly effective in certain lines of business such as SME, they may be less applicable or successful in other lines. Specialty, complex commercial risks, and high-net-worth personal lines often require more nuanced underwriting, personalized risk assessment, and specialized coverage solutions that cannot be easily standardized or automated. Therefore, carriers operating in these segments should strike a balance between automation and personalized service to meet the unique needs of their customers.

A shift in consumer behavior has also driven demand for flow strateges. In today's technology-driven world, people are more likely to purchase insurance online – specifically for smaller risks like property and general liability insurance. To remain competitive and win business, carriers should adopt a lean operating model: a centralized referral underwriting team to handle any complex cases, and standardized product structures that allow for scalability.

Benefits of Adopting a Flow Platform

Automated and streamlined workflows will allow carriers profitability by allowing underwriters to focus primarily on higher-margin, complex business, resulting in lower expense ratios and more gross written premium (GWP) per underwriter. Faster turnarounds produced by the low-touch flow platforms will improve customer satisfaction and engage more brokers with its ease of use. Additionally, technology-enabled operating models have integrated systems and data sources, allowing for increased scalability across all lines of business and geographies.

Implementing the future-state operating model requires heavy investment that poses some challenges and risks for carriers. There are large costs associated with the technological development required to separate flow and complex business, particularly with API and artificial intelligence (AI) integration and developing digital trading solutions. Disjointed systems should be rationalized and integrated with one another, and the carrier will need all the internal systems previously described for the investment to be worthwhile and expand business. The system capabilities should either be built internally or purchased from an insurance-in-a-box platform.

How to Adopt a Flow Platform

Many large carriers are relying on shared service centers and underwriters to assess and triage submissions in a manual, time-intensive process, as well as manually quoting, booking, binding, and issuing policies that are straightforward and low risk. This leads to carriers incurring a high fixed expense basis, which would require low loss ratios to remain profitable and competitive. Instead, underwriters should focus their time on complex business that cannot be conducted through STP and handle requests for flow business through an exception-based referral process. This allows underwriters to use excess capacity to go after more complex business, while maintaining the same fixed expense basis and simultaneously increasing market share in the underserved flow market segment through low-touch STP.

To capture flow business while optimizing efficiency and competitiveness, carriers should develop flow platforms and processes that prioritize simplicity and scalability. Although generative AI is gaining traction in the insurance industry, its high development and maintenance costs may not improve loss ratio enough to bolster the carrier's competitive advantage. Instead, flow solutions should leverage simpler rules engines and decision models, providing a cost-effective way for carriers to enhance automation and take on more of this business with minimal manual intervention. Embracing exceptions within the flow process is crucial, as an optimal model will decrease exceptions over time, thereby enriching and accelerating automation while laying the groundwork for future AI-augmented automation. This approach enables underwriters to direct their focus toward complex business that necessitates their expertise, while efficiently handling flow business through an exception-based referral process. Implementing this type of flow solution can simultaneously reduce operational costs, increase market share in the underserved flow market, and strengthen carriers' competitive position in the evolving insurance landscape.

High operational costs and poor expense ratios for flow business are just two of the hurdles insurers venturing into flow business face today, especially as this sector becomes increasingly commoditized. The expenses associated with transacting flow business and the need to streamline operations to remain competitive make it difficult for carriers to find the value in investing in flow, but the potential for carriers to differentiate themselves by investing in flow remains. Carriers also face fragmented and outdated internal systems that prevent them from embracing technological advancement. These systems may be difficult to rationalize, but modernizing these systems presents an opportunity to improve efficiency and cost management. As the insurance landscape evolves and competition intensifies, carriers must prioritize updating their infrastructure to reduce costs and improve their competitiveness in both the flow and complex markets.

Developing a Flow Solution

To capitalize on the growing SME market and expand into the lower middle market, insurers should build a flow platform that can integrate with an underlying policy admin system, supporting workflow (including referrals), and simplified raters for flow business. Once this has been established, carriers will be able to engage with brokers digitally to underwrite and service business. Brokers expect that carriers will provide immediate turnaround times on simple transactions, with the convenience of obtaining issued policies at any time, not limited by standard business hours. Brokers are turning to carriers that can offer products with agile pricing through digital service distribution, which includes full-service online portals that are user-friendly, as well as API connectivity into in-house broker platforms or trading marketplaces (e.g. Lloyds).

Carriers that are currently excelling in the flow segment of the insurance market have these flow platforms and are heavily investing in digital trading solutions. These solutions offer full-cycle online services (quote, buy, amend, renew), sophisticated pricing models, and integrated AI. Future underwriting operating models will use integrated APIs and AI to auto-populate submission fields and use a rules engine to triage submissions, categorizing as either flow or complex. If the submission is flow, it will be end-to-end processed through a flow platform for STP. If the submission is complex, generative AI will be harnessed to produce an output with pertinent information for underwriters to refer to in their quoting process.

Generative AI (Gen AI) is emerging as a transformative force in property and casualty (P&C) insurance. By producing text, synthetic scenarios, and advanced policy language, Gen AI allows carriers to expedite policy development, automate communications, and refine claims handling. Despite promising pilots, though, many organizations find it challenging to embed Gen AI into their daily workflows. These hurdles arise from a mix of legacy systems, diffuse governance, skill shortages, and strict regulatory obligations. 

This article outlines practical steps for preparing robust training data, validating generative outputs, and aligning team structures so that P&C carriers can fully harness Gen AI's potential.

1. Ensuring Data Quality and Model Reliability

Effective AI implementation relies on high-quality data and robust validation mechanisms.

Data Curation and Preprocessing

High-performing Gen AI models depend on comprehensive datasets that capture the nuances of policy language, claim files, and relevant external materials (e.g., regulatory bulletins). When sources are inconsistent, a generative system can produce flawed or misleading outputs.

• Data Cleansing and Standardization: Removing duplicates, filling gaps, and aligning formats establishes a consistent base for model training. Adopting common taxonomies for coverages, claim types, and underwriting codes helps the system learn domain-specific subtleties.
• Metadata Tracking: Detailed documentation of data provenance and version history is essential for regulatory reviews or internal audits. It clarifies which records influenced the model's text generation and how data were transformed.

Validation and Testing Protocols

Even if the underlying dataset is robust, poor validation can cause the system to violate regulatory or corporate expectations.

• Train/Test Splits and Fine-Tuning: Splitting data into training, validation, and testing cohorts reveals whether a model generalizes well. Fine-tuning steered by experienced underwriters and claims experts refines text outputs and addresses domain quirks.
• Human-in-the-Loop Review: Particularly for endorsements and settlement letters, domain specialists must inspect generated text. Their feedback ensures factual accuracy and compliance, catching issues that a purely algorithmic approach might miss.
• Bias Audits and Fairness Checks: Regularly auditing outputs for skew is critical. If the model references demographic factors or inadvertently discriminates, carriers should re-balance training data or implement more precise prompts.

2. Streamlining Data Integration and Governance

Seamless integration of AI with existing systems ensures consistent and reliable performance.

Fragmented Systems and Legacy Technology

Policy forms, claims notes, and underwriting materials often reside in multiple repositories, complicating the flow of data to Gen AI models.

• Middleware and APIs: Standard APIs or data-exchange layers unify these repositories, giving Gen AI platforms consistent access to forms, manuals, and state-specific directives.
• Centralized Data Lakes: A central repository with version-controlled text corpora and structured reference tables supports timely updates, ensuring that generated outputs keep pace with new mandates and product offerings.

Agile Governance Frameworks

Gen AI evolves rapidly through repeated fine-tuning, necessitating governance that can adapt to frequent model updates.

• Gen AI Oversight Boards: Bringing together compliance officers, data scientists, and product managers, these boards evaluate outputs for alignment with brand standards and regulatory rules, greenlighting new model iterations.
• Adaptable Approval Processes: Narrow pilots (e.g., a single policy line) allow real-world testing of generative capabilities. Swift approval channels then facilitate broader deployment if the pilot proves successful.

3. Navigating Regulatory and Compliance Challenges

Ensuring compliance with regulatory frameworks is crucial for responsible AI adoption.

Explainability and Accountability

While large language models can appear opaque, carriers must document how text is generated and why certain policy clauses appear.

• Traceable Prompting Methods: Storing prompt logs clarifies the chain of reasoning behind each generated document. This traceability becomes vital when auditors question certain terms or phrases.
• Compliance Tags and Anchors: Embedding references to known regulations or internal guidelines in the generative pipeline clarifies how the system aligns with legal and policy frameworks.

Mitigating Bias and Discrimination

Older underwriting manuals or legacy coverage language might inadvertently contain biased terms. Gen AI may replicate or amplify them.

• Content Filters: Automated filters can detect disallowed terms or sensitive phrasing. When flagged, the output is routed to a compliance specialist for manual review.
• Monitoring: Periodic spot-checks of generated drafts reveal emergent biases, whether from newly introduced data or shifts in the model's language patterns.

4. Bridging Skill Gaps and Enhancing Talent Management

Building AI fluency among employees is essential for successful adoption.

Cross-Functional Collaboration

Effective generative models rely on expertise spanning underwriters, actuaries, claims staff, data scientists, and IT engineers. Each group offers insights that enhance the system's relevance and accuracy.

Upskilling and Culture

Adjusters and underwriters need fundamental knowledge of large language models, prompt engineering, and the review process. Workshops and scenario-based training help staff understand how to engage with Gen AI outputs and why their feedback is critical.

5. Implementing Generative AI in Daily Operations

A structured approach ensures seamless AI implementation in daily workflows.

Change Management and Workflow Redesign

Shifting from conventional writing or manual quoting to AI-generated drafts can unsettle employees. Without clear planning, staff may see Gen AI as a threat.

• Defined Objectives and Key Performance Indicators (KPIs): Targets, such as cutting average drafting time or enhancing policy consistency, should guide adoption and help measure progress.
• Phased Rollout: Testing generative solutions in one product line or geographic region yields user feedback. This approach refines the system and builds internal trust before a full-scale launch.

Continuous Model Lifecycle

As new policy endorsements, regulatory edicts, or market conditions emerge, Gen AI requires fine-tuning.

• Version Control: Tracking each model iteration, including training data updates and performance metrics, ensures stability and supports audits.
• Retraining and Retirement: Outdated coverage forms or legislative changes may necessitate retraining. Retiring old models avoids conflicting language that could mislead policyholders.

6. Addressing Ethical and Reputational Considerations

Addressing ethical considerations ensures responsible AI usage and maintains public trust.

Kahneman's Lessons for Generative AI

Daniel Kahneman's "Thinking, Fast and Slow" highlights cognitive biases that can surface in human decisions. These biases may slip into prompts or reflect in historical data, prompting carriers to audit model outputs diligently for skewed or unjust assumptions.

Customer Trust

Clear, accurate communication builds confidence. Demonstrating that humans review critical outputs—especially denials or complex coverage decisions—reassures policyholders that the process is fair and empathetic, rather than purely automated.

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Making It Real: AI-Powered Policy and Claims Automation

A regional P&C carrier introduced a generative platform to automate policy drafts and claim correspondence. The system was trained on curated underwriting manuals, coverage forms, and anonymized customer emails.

Phase One—Policy Drafting

• Underwriters and data scientists created "prompt outlines" that included required clauses and references to state-specific endorsements.
• A brief pilot in auto policies achieved consistent language while minimizing "hallucinated" terms. Human-in-the-loop reviews identified ambiguous outputs, leading to refined prompts and additional training data.

Phase Two—Claims Communication

• Buoyed by the auto-policy success, the carrier extended generative drafting to homeowners' claims. A cross-functional "Generative Oversight Council" reviewed outputs for fairness and clarity, and set up alerts for any coverage interpretations beyond established guidelines.
• Staff surveys showed a 30% cut in writing time for settlement explanations. Customer feedback cited better readability and consistency in communications.

Key Insights

• Controlled Scope: Focusing on auto policies first helped the carrier perfect prompting techniques before tackling more complex homeowner's lines.
• Prompt Engineering: Fine-tuning prompt details and references to recognized coverage forms guarded against inaccurate text.
• Iterative Governance: Frequent oversight meetings allowed stakeholders to reconcile new regulatory updates or product changes quickly.

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7. Aligning AI Strategy with Business Goals

AI implementation should align with overarching business goals to maximize impact.

Linking Gen AI to Business Goals

Carriers are more likely to endorse Gen AI projects that directly advance corporate strategies—be it entering niche markets or boosting renewal rates. Showing how automation improves customer satisfaction or reduces operational costs encourages sustained support.

Demonstrating Return on Investment (ROI) and Broader Benefits

Beyond labor savings, generative models can provide consistent brand voice, reduce training overhead, and strengthen regulatory relationships through clearer documentation. Tracking these intangible advantages helps justify continued investment.

Conclusion

Implementing Generative AI in P&C insurance involves more than model deployment. Carriers must ensure data readiness, carefully validate outputs, and adopt governance structures that balance speed with compliance. By coupling cross-functional expertise with robust oversight, P&C insurers can harness Gen AI to modernize policy generation and claims communications without sacrificing regulatory standards or customer trust. Adhering to clear key performance indicators (KPIs), refining processes through pilot programs, and acknowledging ethical considerations pave the way for a more agile insurer—one positioned to thrive amid evolving market demands.

The state of the insurance industry’s reputation in 2025, in a word, is disastrous. 

Last year, insurance claims exceeded $100 billion, and the biggest takeaways for most insurance consumers centered on:

• Coverage cancellations or non-renewals
• Lack of transparency due to complex policy language or fine-print legalese
• Denial of claims or complex processes complicating the recovery process
• Rising premiums, along with either limited or no coverage options available
• An education gap between what consumers think their policies cover versus actual coverages 

This is not to say that last year's CAT events were the deciding factor in how consumers perceive the industry. There has been a decades-long process as insurance has increasingly undercut its reputation by continuing to commoditize itself, competing on price versus service. Last December’s murder of United Healthcare’s CEO and the resulting public swell of support for the alleged killer helped bring the broader insurance industry’s reputation into focus, both for the public and for insurance professionals. 

Why the Bad Rep?

The way the insurance industry operates is hard for most consumers to understand. 

Those who go direct believe they are getting better rates and coverage. However, most insurance policies are difficult to comprehend, and the buy-direct model can frequently expose insureds to increased risks because the focus—of the insured as well as the insurer—is on price, not service or comprehensive coverage. When a claim does occur, most policyholders only then realize they were underinsured or not covered at all.

However, even those who purchase their insurance products through the traditional means of agents and brokers can run into complicating and confusing factors that include:

• Lack of transparency on coverage and pricing
• Manual, time-consuming and duplicative application processes
• Limited or insufficient digital or self-service options

An understanding of the critical fundamentals of insurance is key to changing this perception. Consumers need to be informed on how premiums are calculated or why coverage fluctuates with certain policy changes. The first time most insureds learn of a change to their premium is during the renewal period. Even then, there is little explanation of why their costs have increased when coverage has stayed the same. 

One factor that has helped to push consumers to the buy-direct model is the complexity of the insurance application process itself. Many agents still follow antiquated, paper- or PDF-based processes that require significant manual input of duplicative information and extensive supporting documentation. For entire generations of Americans who appreciate the click/buy/instant gratification model of ecommerce platforms, the old-fashioned insurance application process is anathema, which drives them to the buy-direct model at their peril. Even for insurance agencies that offer digital applications, many of their online platforms are limited or must be supplemented by some form of the traditional application model. 

What Do Customers Want?

Consumers are looking for affordability and value, transparency, convenience and personalization. 

I call the commoditization of insurance the Walmart effect. Consumers want reliable products at the lowest possible price. However, focusing exclusively on the lowest-possible insurance premium can expose consumers to significant risks and, potentially, much more devastating long-term costs. This is one of the key education issues the industry must undertake. Consumers must better understand the inherent value of their policies and that higher premiums are not a scam for insurers to make money, but rather a practice to ensure the consumer has the necessary coverage to avoid a potential claims disaster. 

Transparency in insurance isn’t just about pricing—it’s about trust. When buyers clearly understand their policies, they see how coverage choices affect their premiums. A transparent application process shifts the focus from cost alone to the real value of coverage, helping insureds assess their risks more effectively. But true transparency extends beyond numbers. Consumers need to know exactly what they’re paying for and how deductible options affect them. To rebuild trust, the industry must simplify its language, cut the jargon, and ensure every policyholder can make informed decisions with confidence.

In terms of convenience, insurance simply must do better identifying opportunities to incorporate technology to elevate the consumer experience. Consumers expect on-demand quick policy quotes, minimal data input and rapid responses. This is the real-world experience for consumers when they go online to book appointments, select event or travel experiences, buy groceries, shop for cars and make dozens of other purchasing decisions from their smartphones or computers. They expect no less from insurance. 

Insurtechs are driving innovation, equipping the insurance distribution channel with the tools to streamline purchasing and quickly adapt to changing consumer behavior. Beyond simplifying transactions, these technologies enable insurers to introduce new products faster and stay competitive in a rapidly evolving market.

Insurers that successfully deliver the personalization consumers expect will set themselves apart. They won’t just earn customer loyalty—they’ll gain the respect of industry professionals who recognize a better way to do business. But true personalization is no easy feat. AI and machine learning are valuable tools, but they’re only part of the equation. Insurers must invest time, resources and skilled personnel to fully understand their customers’ unique circumstances and risk portfolios. By providing tailored recommendations to mitigate risk, insurers can not only improve coverage but also help lower premiums, creating real value for policyholders.

What Is the Solution?

For many insureds, experienced independent insurance agents with a view to the future offer a first line of defense against the further commoditization of insurance. However, this requires a fundamental rethinking of the agent role. 

Insurance will continue to be a relationship business. Agents as advisers is a model long discussed but executed haltingly over the years. This is where technology and the solutions offered by insurtechs can play a role. The facilitation of better matching experienced agents with risk-focused consumers, as we do at Freshquote, we hope is one step in the right direction to solving not only the industry’s reputation problem but also the business development and coverage challenges of agents and insureds, respectively.

Automation and digital enablement can reduce the friction in the quoting and buying process, both for consumers and agents. Properly applied, automation can easily collect data, obtain and evaluate quotes, and even bind and pay. This frees the agent to focus on the role of trusted adviser, giving them time to help consumers understand what is important from a coverage perspective. It also shifts the agent’s focus from the transaction to better understanding and helping to mitigate risk. Additionally, the agent can spend more time advising consumers on various events or trends that may impact their coverage or premiums.

Changing how we approach insurance — by insurers as well as those we insure — will help us all. For consumers, it means looking beyond premium, seeing insurance as a service and protective shield against adverse events and experiencing an easier, better-informed, and more convenient insurance purchase experience. For agents, it presents an opportunity to recast their roles, potentially expanding their books of business and establishing greater trust and partnership with their clients. It will also help to build back trust in one of the world’s most crucial industries at a time when its reputation is so significantly misunderstood and misrepresented.