by Sylvester Mathis | Mar 27, 2025 | Featured Post
Following intense expense management and efficiency investments, commercial property and casualty insurers are increasingly focusing on growth and business expansion opportunities in 2025. As the insurance landscape undergoes significant transformation, these companies are adapting to evolving risks and increased regulatory scrutiny. By leveraging opportunities created by shifting market dynamics and rising customer expectations, insurers can enhance their product offerings and position themselves for long-term success. This evolution requires a strategic approach to navigate the complexities of the modern marketplace effectively.
In today’s dynamic landscape, the necessity for specialized bureau-managed services goes beyond mere growth; for example, it was crucial during the most recent updates to general liability rates, rules, and forms.
The growing demand for advanced bureau-managed services highlights the industry’s urgent need for solutions that combine extensive regulatory knowledge with cutting-edge technology and flexible, customer-centric approaches. The future of insurance depends on the capacity to adapt and innovate within this intricate framework, ultimately transforming customer experiences and operational efficiency.
Why Bureau-Based Content Is Crucial for Admitted Carriers
Bureau content has long served as the backbone of product development for admitted insurers, providing a stable foundation for creating policies and ensuring compliance. Whether for complex commercial, specialty, or mainstream admitted products, bureau services offer pre-approved, standardized content that alleviates the burden on insurers’ internal teams and minimizes regulatory complications risk.
These services are especially vital in a market where speed and accuracy are paramount. By adopting bureau-based content, insurers can avoid reinventing the wheel for every new product or coverage change. Instead, they can focus on differentiating their offerings to meet the unique needs of their growth markets.
However, as the insurance industry evolves, traditional bureau-based services are being tested by several new realities:
- Accelerating Risk Complexity: Cyber threats, climate risks, and business interruptions are increasing in range and complexity at an unprecedented pace.
- Customer Expectations for Agility: Policyholders want personalized products and faster service. Insurers require flexible tools to quickly adjust bureau content and launch customized products.
- Increasing Regulatory Scrutiny: Insurers must keep their bureau-based products compliant as regulations evolve and still meet market demands. Balancing compliance and agility is crucial.
The Shift Toward Managed Bureau Services
The demand for efficient, expert bureau-managed services is growing in response to these challenges. Unlike previously in-sourced or hybrid bureau support, bureau-managed services offer a more integrated, scalable approach that helps insurers maintain compliance while gaining the flexibility to adapt quickly to market changes.
A well-executed bureau-managed service does more than deliver static forms and rates—it provides insurers with a dynamic framework that enables them to:
- Access Real-Time Updates: Managed services improve insurance by offering real-time access to the latest bureau content. This solution streamlines operations, reduces risk, and eliminates manual updates. Insurers can focus on delivering excellent client service and increasing profitability. Stay competitive with managed services.
- Customize Products Efficiently: Insurers can adjust bureau content to match their specific risk appetite, market position, and customer needs. Managed services simplify the customization of forms, rules, and rates without requiring extensive development.
- Enhance Speed to Market: Automating bureau updates helps insurers launch new products faster and swiftly address emerging risks.
The Future of Bureau-Based Managed Services
As the insurance industry progresses towards next-generation capabilities, the role of bureau-based managed services will continue to grow. The future lies in fostering a more collaborative ecosystem that merges regulatory expertise with advanced technology to provide a seamless experience for insurers.
Key trends to watch in this space include:
- Predictive Bureau Content: Predictive analytics enables insurers to anticipate regulatory changes and emerging risks, allowing them to lead the market.
- API-Driven Integrations: Empower insurers to integrate bureau content into their digital ecosystems, enabling instant product updates and significantly streamlining operations for enhanced efficiency and effectiveness.
- Intelligent Automation: Using AI-driven tools to automate regulatory compliance and product configuration, allowing insurers to focus on strategic growth initiatives rather than manual processes.
Is Your Org Ready for the Opportunity Ahead?
As the risk landscape is set to continue evolving, insurers will need to rethink their approach to bureau-based services. The demand for modern, real bureau-managed services is poised to grow as insurers strategize to balance regulatory requirements with market agility. By embracing next-generation solutions and forging collaborative partnerships with bureaus, insurers will be primed to tackle future challenges directly, thereby enhancing the value delivered to both their business and their customers.
by Hicham Elhassani | Mar 26, 2025 | Featured Post
AI may be everywhere in insurance, but without one critical component, your strategy is doomed to fail. Despite its potential in streamlining underwriting, accelerating claims, and optimizing risk management, many insurers are finding that their AI initiatives fall short. The problem? It’s not the technology itself, but the absence of one crucial element: data science that translates insights into actionable outcomes for humans.
Without the right data science strategy, even the most advanced AI tools are just black boxes generating predictions that no one knows how to apply. It’s not enough to build models and expect results. Success requires structuring the work, training users, and designing solutions that connect complex algorithms to real-world business decisions.
In P&C insurance, where accuracy and speed are critical, the missing link isn’t more AI. It’s how you bridge the gap between technology and human decision-making.
The Problem: AI Alone Doesn’t Translate into Business Value
AI is only as good as the questions we ask and the data we feed it. For P&C insurers, adopting AI without a clear data science strategy often leads to incomplete solutions and frustrated users. Tools might deliver predictive models, but if underwriters, adjusters, or claims managers can’t easily translate those predictions into actionable steps, the system breaks down.
A risk scoring algorithm might flag a policyholder as high-risk, but what does that mean for the underwriter? How does it connect with their existing workflow? What supporting data can they view to understand the rationale behind the score and make an informed decision? AI can’t answer these questions on its own. Data scientists must design solutions that take the insights from models and create something comprehensible, actionable, and aligned with business objectives.
The Bridge: Data Science as the Connector
Data science isn’t just about building algorithms. It’s about context, communication, and translation. A successful data science team acts as a bridge between technical systems and business outcomes.
Here’s how it plays out for P&C insurers:
- Understanding the Business Problem: Before a single model is trained, data scientists must deeply understand the business problem they’re trying to solve. Is it about improving loss ratios, enhancing fraud detection, or optimizing claims processing times? Without this clarity, even the best AI models will miss the mark.
- Structuring the Work for Collaboration: Data science isn’t a siloed activity. It requires collaboration with underwriters, actuaries, claims professionals, and business leaders. Structuring the work to include these perspectives ensures that the final solution isn’t just technically correct, but that it’s practical and usable.
- Building Transparency into Models: In P&C insurance, trust is everything. Black-box models that spit out risk scores without transparency won’t be adopted. Data scientists must build explainability into their solutions, ensuring that business users can see how the model reached its conclusions and what data it relied on.
- Training Users and Integrating Feedback Loops: Delivering a solution is only half the job. Data scientists need to spend just as much time training users and integrating feedback. For example, a claims manager might notice that the fraud detection model is flagging too many false positives. That feedback must flow back into the data science team to refine and improve the model.
Real-World Application: From Data to Decisions
Consider the example of catastrophe claims management. A P&C insurer might implement a geospatial AI model to predict wildfire risk and assess damage. On its own, the model provides probabilities and risk maps. But the real value lies in how those outputs are used:
- For Underwriters: The data science team can create visual tools and dashboards that bring AI-driven insights directly into the underwriting workflow. These tools provide underwriters with a property-level risk assessment that includes real-time data, such as wildfire risk predictions or geospatial overlays. Instead of sifting through dense datasets, underwriters get a clear, actionable view of high-risk policies and the underlying factors driving the risk score. This not only speeds up the underwriting process but also empowers underwriters to make data-backed decisions with confidence and consistency, reducing guesswork and improving accuracy.
- For Claims Managers: Integrating predictive insights into the claims process enables claims managers to prioritize high-risk or high-severity claims more effectively. For example, after a major wildfire event, claims managers can use AI-generated risk assessments to identify areas with the most significant damage and allocate field adjusters accordingly. Geospatial analytics and satellite imagery can further streamline this by reducing the need for physical inspections. The result is faster claims resolution, reduced operational costs, and higher policyholder satisfaction, all driven by actionable insights embedded into the claims workflow.
In each case, the model is only the starting point. The data science process turns it into something actionable and valuable for the people using it.
A New Way of Thinking About Data Science and AI
The insurance industry doesn’t need more AI tools. It needs better ways of structuring work and applying data science to solve real-world problems.
Success in AI-driven initiatives comes from viewing data science as an integral part of the business, not a separate technical function. It’s about asking the right questions, collaborating deeply with stakeholders, and ensuring that every insight generated is immediately usable and understandable by the humans making decisions.
Are You Ready to Bridge the Gap Between AI and Data Science?
The future of AI in P&C insurance isn’t about more complex models or fancier tools. It’s about focusing on how we structure and integrate data science into our business operations.
For insurers that do this well, the rewards are clear – better decisions, faster workflows, and more value for policyholders. For those who treat AI as a plug-and-play solution, the road ahead will be filled with frustration and missed opportunities. Data science is the connective tissue between AI and human action. It’s time we give it the attention it deserves.
by Hicham Elhassani | Feb 11, 2025 | Featured Post
The recent California wildfires have once again put the unique challenges of wildfire risk into the national spotlight. Insurers are under increasing pressure to balance accurate risk assessment with fair pricing and sustainable coverage. At the same time, policyholders are concerned about rising premiums and the availability of insurance in high-risk areas. However, the solution isn’t retreating from these regions, but leveraging advanced technology, like geospatial analytics, to manage risk more effectively, enhance mitigation efforts, and improve outcomes for both insurers and policyholders.
Geospatial analytics has emerged as a critical tool in wildfire risk management, transforming how insurers assess, price, and mitigate risk. By integrating satellite imagery, AI-powered predictive modeling, and real-time environmental data, insurers can gain a granular, property-level view of wildfire vulnerability. This data-driven approach allows for more precise underwriting, proactive risk mitigation, and faster claims resolution, ultimately benefiting policyholders with fairer pricing, greater transparency, and improved recovery support.
The Role of Geospatial Analytics in Wildfire Risk Management
For decades, insurers have relied on historical data and broad risk zones to assess wildfire exposure, but this static approach is no longer sufficient. Climate change, urban expansion, and evolving wildfire behavior demand more dynamic, real-time solutions.
Geospatial analytics provides three key advantages that enable insurers to better protect policyholders and ensure long-term insurability in wildfire-prone regions:
- Hyper-Localized Risk Assessment: Instead of assigning risk based on generalized zones, geospatial analytics allows insurers to analyze individual property characteristics, such as vegetation density, terrain, wind patterns, and historical fire activity. This enables precise underwriting and pricing, ensuring policyholders in lower-risk areas aren’t unfairly penalized by broad risk classifications.
- Proactive Risk Mitigation and Policyholder Engagement: Wildfire risk isn’t just about location—it’s about preparedness. Insurers can use geospatial analytics to identify vulnerabilities at the property level and provide policyholders with personalized risk mitigation strategies. For example, insurers can recommend clearing defensible space around homes, identify structures that would benefit from fire-resistant materials, and provide real-time alerts when wildfire threats emerge. By helping policyholders reduce risk, insurers can minimize losses while demonstrating proactive customer support, which is crucial for retention in high-risk markets.
- Faster, More Accurate Claims Processing: After a wildfire, policyholders often experience delays in claims assessments, leading to frustration and financial strain. Geospatial analytics streamlines this process by using aerial and satellite imagery to quickly assess damage, eliminating the need for on-the-ground inspections in many cases. This means, faster claims resolution, allowing policyholders to rebuild sooner, more accurate, objective damage assessments, reducing disputes, operational efficiencies for insurers, lowering costs and improving customer satisfaction.
How Policyholders Benefit from Geospatial Analytics
The true value of geospatial analytics isn’t just in how it helps insurers. It’s in how it improves the experience for policyholders. Insurers investing in this technology can:
- Ensure Fairer Pricing: With precise, property-specific risk assessments, insurers can avoid blanket rate increases and offer more tailored pricing models. This prevents lower-risk policyholders from overpaying due to outdated, broad risk categorizations.
- Provide Greater Transparency: Policyholders often feel uncertain about how their wildfire risk is assessed and why their premiums change. With geospatial analytics, insurers can provide clear, data-backed explanations, improving trust and policyholder confidence in the underwriting process.
- Enhance Policyholder Support & Preparedness: Instead of merely reacting to wildfires, insurers can empower homeowners and businesses with proactive insights. Real-time monitoring and early warnings can help policyholders take action before disaster strikes, reducing losses and improving overall safety.
- Accelerate Claims Payouts in Critical Moments: When a wildfire does occur, policyholders need fast access to funds for temporary housing, repairs, and rebuilding. Geospatial-powered claims assessments ensure a quicker, more seamless process, preventing delays that can add unnecessary hardship.
Why Insurers Must Act Now
As wildfires grow more severe, insurers cannot afford to rely on traditional risk models that may overestimate or underestimate exposure, leading to either excessive rate hikes or unexpected losses. Geospatial analytics provides the precision and efficiency needed to balance risk, protect policyholders, and maintain a sustainable presence in high-risk regions. Furthermore, as regulatory scrutiny over wildfire coverage intensifies, insurers that adopt data-driven, transparent underwriting practices will be better positioned to comply with evolving guidelines while maintaining policyholder trust.
Is Your Wildfire Risk Strategy Ready for What’s Next?
The reality is that wildfires aren’t going away, but insurers that embrace geospatial analytics can better protect their policyholders while ensuring long-term market viability. Investing in geospatial analytics is not just a technological upgrade. It’s a strategic necessity for insurers looking to provide sustainable coverage, improve risk management, and strengthen policyholder relationships.
Insurers can deliver real value to the people who need it most by embracing property-specific risk assessments, proactive policyholder engagement, and faster claims processing. The future of wildfire insurance depends on data-driven solutions that benefit both insurers and policyholders alike. Geospatial analytics is that solution.
by Sylvester Mathis | Jan 16, 2025 | Featured Post
In recent years, insurers have faced mounting challenges as expenses have grown alarmingly. Insurance industry expenses have sharply risen, outpacing premium growth and placing additional strain on tight margins. For an industry that thrives on precision and balance, this disproportionate increase creates significant headwinds, necessitating strategic action to address operational inefficiencies and cost management.
As we look to the future, the ability to adapt to this trend will define success for insurers. By focusing on cost savings while tailoring strategies to meet diverse customer needs, the industry can work toward greater stability that benefits insurers, policyholders, and the broader market.
To create a more stable market that benefits everyone, insurers must again shift from simply reacting to rising costs to addressing their root causes and finding actionable solutions.
The Cost Conundrum: A Multifaceted Problem
At first glance, the drivers of rising expenses may seem varied and disconnected. However, they are deeply interconnected, forming a complex web that challenges insurers to maintain efficiency while adapting to change.
One significant factor is claims complexity, driven by evolving risks such as extreme weather events, cyber threats, and litigation trends. These developments are straining existing claims processes, leading to higher administrative costs. Additionally, inflation has affected everything from reinsurance rates to labor costs, further tightening margins.
In addition to these pressures, insurers must invest in new technologies to remain competitive. Although these innovations promise long-term efficiencies, they necessitate significant upfront investments in infrastructure and talent, leading to a short-term financial burden.
Together, these forces amplify the challenge: insurers must tackle rising costs while addressing market demands for speed, innovation, and customer-centricity.
The Ripple Effect: Impact on the Insurance Ecosystem
The impact of disproportionate expense increases doesn’t stop at the insurers’ bottom line. it cascades through the entire insurance value chain.
Rising expenses often translate to higher premiums for policyholders, creating dissatisfaction and reduced loyalty. Insurers that are unable to absorb these costs or find efficiencies risk losing their competitive edge, especially to peers that can streamline operations more effectively.
At a market level, these cost pressures lead to volatility. Insurers may withdraw from specific lines of business or geographic regions, reducing capacity and forcing a recalibration of pricing models across the board. The resulting uncertainty complicates planning for all stakeholders.
Rebalancing the Scales: A Focus on Collaborative Cost Reduction
Breaking free from this cycle requires a shift in perspective. Instead of viewing expense increases as an insurmountable obstacle, insurers must see them as an opportunity to redefine priorities. Collaborative cost reduction among insurers, customers, and partners offers a viable path forward.
- Empowering Customers to Reduce Claims Costs
Risk mitigation strategies can lead to substantial savings for both insurers and policyholders. By educating customers about proactive risk management—such as implementing safety measures and adopting preventive technologies—insurers can help decrease the frequency and severity of claims. These savings not only reduce operational costs but also strengthen relationships with customers.
- Leveraging Technology for Efficiency Gains
While the initial cost of adopting new technology can be high, the long-term benefits are clear. Insurers can use advanced analytics to pinpoint inefficiencies and automate routine processes like underwriting and claims management. It is essential to focus on targeted investments that provide immediate operational improvements while also preparing for future scalability.
- Optimizing Partnerships and Outsourcing
Partnerships with vendors, reinsurers, and service providers are essential. Insurers should consider outsourcing non-core functions and negotiate better terms with partners, ensuring alignment between costs and strategic goals.
- Reevaluating Reinsurance Programs
Reinsurance is typically one of the largest expense categories for insurers. Conducting a strategic review of reinsurance arrangements can reveal opportunities to cut costs while still maintaining effective risk management. This process may include adjusting retention levels or exploring alternative solutions for transferring risk.
For insurers themselves, the most pressing consequence is an erosion of financial flexibility. Rising costs leave little room for innovation or strategic investments, trapping organizations in a cycle of reactionary decision-making rather than proactive growth.
Is Your Organization Moving Toward a More Stable Market?
The rising cost trajectory isn’t sustainable, but addressing it requires an industry-wide commitment to thoughtful action. Insurers must reimagine their roles as risk managers and partners working toward a more efficient, stable market. This shift involves engaging with customers, exploring new operational models, and embracing innovation strategically.
By prioritizing collaboration, insurers can create cost-saving opportunities that benefit not only their organizations but also policyholders and the broader market. The result is a more resilient insurance ecosystem that is better equipped to navigate the challenges ahead.
The upcoming year will challenge the industry’s ability to adapt, innovate, and find balance. Insurers who manage rising costs effectively and prioritize the development of sustainable, customer-focused solutions will be the ones who succeed and shape the future of insurance.
by Jay Wilson | Dec 19, 2024 | Featured Post
Dashcam footage of attempted car insurance fraud on New York’s Belt Parkway recently went viral, serving as a powerful reminder that fraud has long been a challenge for insurers. Yet, the landscape is shifting – and not for the better. The rise of deepfake technology is ushering in a new era of more sophisticated and insidious fraud, presenting P&C insurers with unprecedented challenges to address.
Deepfakes, AI-generated manipulations of audio, video, and images, have rapidly evolved in sophistication, posing significant challenges across many industries. For P&C insurers, these highly convincing falsifications threaten the integrity of claims processing, underwriting, and fraud prevention efforts. As deepfake technology becomes increasingly accessible, the insurance industry must grapple with new vulnerabilities and identify ways to safeguard its processes.
Here are the top four concerns for P&C insurers regarding deepfakes and strategies your organization can take to combat them.
1. The Deepfake Threat to Claims
Deepfakes create an avenue for fraudsters to submit entirely fabricated claims. With AI-generated imagery or videos, fraudsters can fabricate car accidents, property damage, or injuries that never occurred. For instance, a deepfake video might show a tree collapsing onto a car, presenting compelling but entirely false evidence for an auto insurance claim.
Identity theft is another pressing issue in claims management. Deepfake audio or video can be used to impersonate policyholders or beneficiaries during remote claims verification. Fraudsters may use AI-manipulated content to bypass security measures, posing as the rightful claimant in video calls or online portals.
Fraudulent deepfakes undermine the credibility of visual evidence, one of the cornerstones of claims validation. This forces insurers to dedicate additional resources to investigate claims, driving up costs and slowing the claims process.
Fortunately, there are emerging technologies in image detection that may be able to help curb this increased concern around deepfakes in claims evidence. These advanced AI-powered detection tools can identify manipulated content, effectively using AI to find AI manipulated content in audio, video, or images, claims evidence. Insurers should stay focused on this evolving space to protect their business and stakeholders.
2. The Deepfake Threat to Underwriting
In underwriting, accurate data is paramount for risk assessment. Deepfake imagery or video could misrepresent the condition of insured assets, such as showing a property in pristine condition when it has underlying issues, leading to inaccuracies in premium calculations. Additionally, deepfakes might be used to exaggerate the risks faced by assets in order to inflate claims payments.
Manipulated underwriting data could lead to significant financial losses and flawed risk modeling. Moreover, the increased use of deepfakes in these scenarios could erode trust in automated underwriting systems, hindering the adoption of these innovative technologies.
While AI image manipulation detection systems can help validate visual evidence and reduce risk of deepfakes interfering with proper underwriting, leveraging GenerativeAI in underwriting is a new way to potentially advance the practice beyond mere defense. As will all emerging technologies, GenerativeAI underwriting tools require proper planning, integration, testing and validation, but the most innovative insurers are already investing heavily in this area and it will long-term transform the practice while helping to combat these emerging risks.
3. The Deepfake Threat to Your Employees
Deepfakes are increasingly used in social engineering attacks. For example, a fraudster could use deepfake audio to impersonate an executive and instruct an insurer’s staff to release sensitive data or approve unauthorized transactions. These scenarios represent a significant risk for insurers, who manage vast amounts of sensitive customer data.
These attacks not only expose insurers to direct financial losses but also jeopardize their reputations. A well-publicized deepfake attack could undermine customer confidence in the insurer’s ability to protect sensitive information.
To best protect their businesses, insurers should focus on employee training. Empowering staff to recognize and address suspicious submissions can enhance fraud prevention. Collaboration within the industry, including sharing best practices and developing standardized validation protocols, can strengthen defenses. Leveraging the human side of our relationships with others also can reveal when bad actors are playing games.
4. The Deepfake Threat to Compliance Needs
The rise of deepfakes brings new complexities to regulatory compliance, particularly around data privacy and fraud prevention. Insurers must ensure their processes align with legal requirements like the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA). However, the advanced nature of deepfakes makes it difficult to verify the authenticity of data, raising concerns about the admissibility of visual evidence in legal contexts.
Failing to detect and address deepfake-related fraud could lead to compliance violations, financial penalties, and reputational damage. Moreover, regulators may impose additional scrutiny on insurers, requiring them to implement stricter validation protocols.
As these attacks become more sophisticated, so must our defenses. Looking at advanced identity verification, comprehensive background screening, identity reverification techniques and more over time may be ways to combat this risk.
How Insurers Can Combat Deepfake Challenges
To combat deepfakes, insurers must adopt a proactive, multi-faceted approach. Advanced AI-powered detection tools can identify manipulated content by analyzing inconsistencies in audio, video, or images, while blockchain technology can provide tamper-proof records for claims evidence.
Employee training is equally critical. Empowering staff to recognize and address suspicious submissions can enhance fraud prevention. Collaboration within the industry, including sharing best practices and developing standardized validation protocols, can strengthen defenses.
Do You Have a Plan to Navigate the Deepfake Era in P&C Insurance?
Deepfakes are not just a hypothetical challenge. They are an imminent threat with the power to disrupt claims processing, skew underwriting accuracy, and compromise cybersecurity. Insurers must move beyond reactive measures and adopt a proactive approach, integrating advanced AI detection tools, enhancing fraud prevention protocols, and fostering collaboration across the industry to address this growing issue. Without decisive action, the risks could undermine not just operational efficiency, but also the trust of policyholders.
The rise of deepfake technology demands more than vigilance. It requires a commitment to innovation, investment in advanced solutions, and a readiness to adapt to an evolving digital battlefield. Insurers who lead with these strategies will not only mitigate risk but position themselves as industry leaders, delivering resilience and exceptional value to their customers in the face of unprecedented challenges.
by Matthew Yeshin | Oct 22, 2024 | Featured Post
New tools and technology are emerging that collect and analyze vast amounts of data from every corner of the shipping industry. Yet, despite these advancements, the marine cargo insurance industry may be missing out on a significant opportunity to leverage them in order to improve their pricing decisions and risk management.
Over the past few decades, marine cargo insurers have strived to make cargo insurance programs easier to administer and broader in coverage. To that end, marine cargo insurance policies have shifted from being largely declaration driven, to being more sales or revenues adjusted, where the details of the individual shipment transactions are not captured in the underwriting or policy adjustment process. The marine cargo insurance industry has an opportunity to embrace the availability of more granular shipment data and change how they incorporate data into their policy structures and risk assessment.
Here are three ways the marine cargo insurance industry can augment decision making and, in turn, improve underwriting, portfolio management, and event response by making better use of real-time and readily available supply chain data:
1. Ask for the Data
An issue throughout the industry is that many insurers and brokers are simply not asking their insureds to provide them with more granular data. Through transportation management systems (TMS) and electronic bills of lading (eBOLs) and customs documentation, the logistics industry is collecting and distributing a vast array of information about how goods are moving through the supply chain. This data is often already being enhanced through integrations with Internet of Things (IoT) devices within the cargo or the container that can include cargo values, routes, geopolitical risks, weather patterns, port conditions, among other useful information. However, if the marine cargo insurance industry is not aware that this data is available, or they don’t know how to ask for the data, then clients are not going to provide it.
By not asking for this data from clients, the industry is missing the opportunity to create tailored, dynamic policies that reflect the real-time risks as well as some of the specific needs of the businesses they insure. The traditional approach of setting static coverage based on broad categories of goods and routes can be replaced with detail that was never available in the past. With the right data, policies can be refined to better meet specific insurer appetites, as well as offer more precise pricing, more efficient limits, and broader coverage, better aligned with the actual risks shippers face.
For example, consider how cargo value accumulation and route optimization data could impact pricing decisions. Knowing the exact route goods are taking, particularly through high-risk areas, could allow insurers to provide pricing options that may promote the selection of lower risk routing, and/or allow the shipper options to work with alternative markets, or alternative coverage structures to better manage that specific risk. It also becomes feasible to look at creating new risk mitigation solutions to address traditional insurance limitations, such as coverage for trade disruptions or loss of market due to delay.
2. Standardize the Data
Collecting data is just the first step. To fully leverage the benefits, the marine cargo insurance industry must standardize data so that it can be reviewed consistently across a wide portfolio. In its desire to meet specific client needs, particularly in the way commodities are documented and categorized and coverage is constructed, the marine cargo insurance industry has created highly tailored wordings that address risk differently, but generally lead to a very similar coverage result. This practice also can make it difficult to analyze and compare risks across different shipments, routes, and insureds — even where the exposure and coverage is likely analogous.
By working to standardize the collected data, such as cargo descriptions and shipping routes, the industry can not only achieve better reporting, but can also start to unlock more sophisticated data analysis. Standardized data allows insurers to compare risks across clients, identify patterns, streamline pricing and even start to predict potential risk issues before they arise. It also provides a common language for insurers, shippers, and shipping companies, making it easier to communicate about risks and coverage needs.
For instance, standardizing how cargo is documented based on existing standardized documentation, such as eBOLs and customs documentation, can give insurers a more granular understanding of the goods they are covering. This deeper insight allows for more precise risk assessments and better alignment of coverage with actual needs. In turn, this specialized coverage alignment could lead to more competitive pricing, as insurers would have a clearer picture of where risks lie and could adjust premiums accordingly.
3. Use the Data to Create More Flexible Policies
With data properly collected and standardized, the structure of marine cargo insurance policies can keep pace with the evolution of global supply chains. Traditionally, policies have been designed to simplify coverage for insurers, often at the expense of fully reflecting the complexities of modern shipping. But today’s supply chains are highly integrated and data-rich, offering a wealth of information that could be used to create more dynamic, flexible policies that can be better integrated into the overall process of moving goods, such as freight costs, contracting, and financing.
To take full advantage of the data available, the marine cargo insurance industry needs to rethink both the structure and distribution of marine cargo policies. Rather than relying on rigid, one-size-fits-all coverage that are tailored to the cargo owner, insurers could develop policies that are flexible and responsive to real-time data. For example, policies could automatically adjust based on the entire route a shipment takes or the geopolitical risks present at the time of transit. This structure could not only help ensure that businesses are adequately covered but also allow insurers to price policies more accurately based on the actual risks involved.
Such innovations could also open the door to new types of coverage. For example, with better visibility into shipping routes and cargo values, insurers could offer parametric insurance that triggers payouts based on predefined conditions, such voyages being delayed beyond a specified number of days, or cargo sensors showing an impact or temperature variation beyond a certain threshold.
The Real-World Impact of Data-Driven Claims Handling
The benefits of collecting and standardizing data extend beyond pricing decisions. They also have a significant impact on how claims are handled.
In a traditional claim scenario, insurers often rely on the shipper’s account of what happened and lengthy investigations to determine the validity of the claim. With access to accurate, real-time data, insurers can validate claims expeditiously, based on records coming from IoT devices and telematics that are monitoring the condition and handling of the cargo, reducing the time and cost involved in processing claims.
Further, with access to real-time data, insurers can monitor shipments as they move through the supply chain and identify potential issues before they result in claims. For example, if a shipment deviates from its planned route or encounters severe weather, insurers could proactively engage with the shipper to assess the situation and manage the risk before it escalates.
Predictive data can also help reduce the frequency of claims by allowing insurers to identify and address risks early. If data shows that a particular route is prone to delays or losses, insurers can work with shippers to adjust their routes or take other precautions to mitigate the risk.
It’s Time to Modernize the Marine Cargo Insurance Industry
The marine cargo industry is sitting on a treasure trove of data, but we are not using it to its full potential. By actively collecting and standardizing this data, we can revolutionize the way marine cargo insurance is priced, structured, and managed.
