Practical First Steps for Integrating AI Without Disrupting Operations

“AI is definitely frontier-level stuff that’s changing rapidly, so it’s natural to be cautious about its adoption,” Villa explained. A practical first step is to focus on data hygiene, ensuring that AI has access to accurate and structured data. He recommends insurers take key steps, including:

• Establishing clear data standards for formatting, naming conventions, and storage.
• Enhancing data security and privacy by anonymizing or adapting personal data for AI model training.
• Extracting, integrating, and consolidating data from various systems.

“Having limited data sets that are thoroughly cleaned and vetted will create a strong data foundation and position AI initiatives for success,” Villa added.

Using AI to Enhance Teams, Improve Decision-Making, and Drive Efficiency

Most insurers start their AI journey with chatbots or automated document processing to improve data access and decision-making. AI streamlines manual tasks, such as summarizing home inspection reports, which typically take underwriters about 30 minutes to review. AI can ingest data, redact personally identifiable information (PII), and generate a summary in seconds, making it immediately actionable. “This level of AI precision reduces cycle time, but does not replace the underwriter,” said Villa. “Instead, it’s a collaborative process that combines human expertise with machine learning a ‘human-in-the-loop’ approach.”

Overcoming Key Challenges in the AI Journey to Deliver Measurable Value

“I think the biggest challenge we face is thinking differently about the work we’ve been doing for the past 20 years,” said Villa. “Using ChatGPT to help enhance the quality of and reduce the time it takes to put things in writing or researching topics feels natural. Who wouldn’t want to spend less time writing emails or researching topics?” However, the challenge arises when AI begins to automate tasks professionals feel they have mastered. “What if I’m a senior underwriter and I am an expert at inspection report reviews?” Villa posed. “I may not be as open to using AI, even if it gives me back time in my day. Helping our team understand that AI isn’t going to replace the work we do, but rather augment it, will be key to successful adoption.”

How OneShield Helps AAIS Members Navigate the Evolving AI Landscape

OneShield is at the forefront of AI-driven transformation, offering two modern core systems: OMS and Enterprise. “Both solutions can be delivered as enterprise suites to automate policy, billing, claims, workflow, and reporting, or they can be implemented as a modular solution to address any one particular aspect of the insurance value chain,” Villa explained. For AAIS Members, OneShield’s expertise in AAIS lines of business makes adoption even smoother. “Across our two products, we can support all AAIS lines. We have particularly strong experience with unique AAIS lines such as COP and Artisans,” Villa noted. “Leveraging this experience to deliver pre-built AAIS content within our core solutions can accelerate core transformation projects at a significantly reduced cost to the insurer.”

Learn more at OneShield.com.

To view the full interview with Tony Villa, click on the video above.

The post AI in Insurance: Streamlining Underwriting Without Disruption first appeared on AAIS.

How Insurers Can Leverage New, Unconventional Technologies and Insights to Improve Loss Ratio

Ham believes that new behavioral insights offer insurers a critical tool to enhance risk assessment and loss ratios. “Insurers can leverage new and unconventional behavioral insights by performing better, more thorough risk assessment,” he explained. These insights provide an additional layer of understanding that complements traditional factors used in risk evaluation. With the inclusion of behavioral insights, carriers get “a factor that to date they haven’t had access to,” offering a fuller picture of the risk profile. This allows them to make more informed and profitable decisions.

How Carriers Can Integrate Behavioral Intelligence Into Existing Risk Mitigation Strategy

Carriers can integrate behavioral intelligence into their risk mitigation strategies at multiple points in the insurance value chain, according to Ham. By using behavioral insights, they can target individuals whose profiles align with their risk appetite, tailoring risk selection from the outset. “It goes down the insurance value chain, where they can dictate the buying journeys based on these new insights,” Ham explained. Additionally, carriers can use behavioral intelligence to develop renewal strategies, allowing for a more dynamic approach to risk management.

Using Behavioral Insights to Help Carriers Achieve Goals of Equity and Fairness

Behavioral insights can play a pivotal role in helping carriers meet goals of equity and fairness. “By getting that complete picture, we have to recognize the uniqueness of individuals, and behavioral insights are exactly that they’re telling the carrier unique insights about that individual, so they don’t have to bucket them or ban them, ” said Ham. He explained that by understanding individuals on a more personal level, carriers can avoid the unintended exclusion of certain groups, ensuring a more inclusive approach to underwriting and risk management. “It’s not based on banking, so you’re getting insights that are more inclusive of individuals, as opposed to those that may unintentionally exclude some.”

About Pinpoint Predictive, Inc.

Ham described Pinpoint Predictive as “the ultimate risk selection platform.” He elaborated, “Pinpoint Predictive leverages machine learning and these new unconventional behavioral insights to deliver unparalleled precision in underwriting and actuarial decisions. The company’s platform addresses not only profitability for insurers but also improves the overall customer experience and provides agents with better tools to represent carriers effectively. “For me, Pinpoint is that ultimate risk selection platform that allows everybody to win.”

Learn more at pinpoint.ai.

To view the full interview with Scott Ham, click on the video above.

The post Enhancing Risk Mitigation with Behavioral Intelligence first appeared on AAIS.

In 2024, a P&C insurer study conducted by Capgemini suggested that 41% of the underwriters’ time is spent on “administrative and operational activities, constraining their capacity and triggering value chain challenges in pricing and broker/customer experience.”

Improving underwriter efficiency has always been a key driving force behind selecting an insurance platform. However, merely adopting a modern insurance platform is insufficient to address some of the current inefficiencies. To truly enhance underwriting efficiency, insurers now have the opportunity to select an insurance platform with built-in advanced AI-based automation and process optimization solutions. Furthermore, selecting a platform equipped with AI capabilities and partnering with a solution provider that is actively investing in AI technologies will not only meet current underwriting demands but also drive future productivity and innovation requirements.

With built-in AI-driven solutions, insurers can streamline operations, reduce manual workloads, and enhance overall efficiency, positioning themselves for long-term success in a rapidly evolving market. A modern platform working in cohesion with its own AI solution is the only way to achieve maximum efficiency and success.

Key areas where AI can bring substantial benefits include:

• Improving User Experience and Automation: AI-powered platforms can streamline and automate repetitive tasks, such as data entry and analysis, thereby reducing the administrative burden on underwriters. For example, Cogitate’s DigitalEdge platform has UW Assist, powered by CogitateLabs, which includes data ingestion capabilities. The AI reviews the input submission forms, automatically identifies the inputs for the submission through its powerful LLM models, and inserts data automatically into the application. This drastically reduces the manual administrative work for the underwriters and improves their user experience.
• Reducing Premium Leakage and Adverse Selection: AI can play a crucial role in minimizing premium leakage by identifying discrepancies and ensuring that premiums accurately reflect the risk associated with each policy. Moreover, AI-driven analytics can detect patterns indicative of adverse selection, where higher-risk individuals might be disproportionately represented. By addressing these issues, insurers can better align premiums with actual risk profiles and improve the financial stability of their portfolios.
• Prioritizing Work: AI can assist underwriters in prioritizing their workload by analyzing and sorting tasks based on urgency and impact. Intelligent systems can assess cases that require immediate attention and those that can be deferred, optimizing the allocation of resources and improving workflow efficiency. This prioritization ensures that critical tasks are addressed promptly, leading to better risk management and decision-making.
• Identifying Demands: Attorney demand letters are one of the biggest challenges facing the insurance industry. Any bad faith claim can have a significant impact, with settlements running into millions of dollars. Insurance companies have to deploy the manual process of reviewing thousands of documents daily to identify demand letters from attorneys. This is a time-consuming and error-prone process. With solutions like Cogitate’s DemandAssist, an AI/ML-based product, significant operational efficiency with an error-free process can be achieved.

Conclusion

AI-based tools are becoming a part of the work process, and proper adoption is key for an organization’s success and sustainability. To effectively leverage innovative tools, particularly AI-assisted solutions, it is essential to first build trust within your team. This involves gradually introducing these tools to address specific issues, consistently using and testing them, and measuring the improvements they bring. By demonstrating tangible benefits and success, you foster confidence in the technology and cultivate advocates for innovation within your organization.

Equally important is finding the right partner, like Cogitate, to support your transformation journey. Selecting the right solution provider who not only offers advanced tools as part of their insurance platform but also invests in ongoing innovation and support ensures that you have a reliable ally in navigating the complexities of modern insurance technology needs. This partnership is crucial for maximizing the potential of AI solutions and achieving long-term success in underwriting and beyond. Learn more about Cogitate at cogitate.com.

The post AI-Powered Insurance Platforms Boost Underwriting Efficiency first appeared on AAIS.

The Evolving Landscape of Homeowners Insurance

The homeowners insurance market is under intense pressure due to a combination of factors:

• Population Shifts and Real Estate Development: Growing populations and new developments in high-risk regions exacerbate underwriting difficulties.
• Unpredictable Weather: Increased frequency and severity of weather-related events make risk prediction more complex.
• Market Disruptions: Factors like social inflation, macroeconomic pressures, rapid innovation demands, and heightened competition are intensifying the strain on insurers. Litigation management costs surged 19% from 2018 to 2023 for the combined P&C sector, reflecting an approximate $24 billion loss adjustment expense (LAE).

These issues are compounded by a surge in consumer insurance shopping, a rise in higher-risk policies, and an increase in long-time policyholders switching carriers. Insurers are forced to make tough choices, such as raising premiums, exiting markets, or discontinuing certain coverage lines. These pressures are preventing the industry from achieving necessary positive outcomes critical for future profitability.

The Burden on Underwriters

Amid the ongoing market uncertainty, underwriters particularly are facing significant challenges:

• Overwhelming Submission Volume: An influx of submissions strains underwriting resources.
• Inaccurate Risk Prediction: Traditional methods based on demographic data and zip codes are proving to be inadequate, necessitating more precise risk assessment tools.
• Data Quality Issues: Poor-quality or unstructured data and manual processes further complicate risk assessment.

Underwriters are questioning why the process is so burdensome and how it can be alleviated. The crux of the issue is underwriting profitability, crucial for maintaining healthy bottom-line results. Fortunately, there are modern solutions to address these goals.

Modernize Risk Assessments with Behavioral Predictions

Traditional underwriting relies heavily on demographic data and location. Enhanced risk assessment goes beyond traditional methods such as ZIP Codes and credit scores by incorporating individual behavior and decision-making patterns.

Underwriters today can access a wealth of data outside traditional risk variables to deepen the understanding of their policyholder’s risk profile. By utilizing AI-powered behavioral predictions, which incorporate information about consumer activity, interests, buying choices, etc., underwriters can more accurately predict outcomes relevant to insurance underwriting performance.

To remain competitive, insurers must invest in this digital transformation and reduce reliance on complex, manual processes. In fact, a McKinsey analysis found that the most successful carriers are those leveraging the latest technologies to optimize underwriting capabilities. Enhanced approaches for success involve adding:

• Comprehensive Risk Profiles: A detailed view of prospective and existing policyholders to start transforming underwriting workflow.
• AI and Person-Level Insights: Using AI to access powerful person-level insights about customers and their individual risk propensities, which directly impact underwriting profitability.

Leveraging Behavioral Predictions Across the Insurance Value Chain

Using behavioral intelligence represents a transformative shift in insurance underwriting. By incorporating policyholder behaviors into risk evaluation, insurers gain a deeper understanding of risk profiles and individual customer nuances, leading to a more customer-centric approach to coverage. This intelligence offers specific predictions that enhance risk assessment:

• Identifying policyholders with a high propensity to seek an attorney at first notice of loss (FNOL) or a likelihood to litigate.

• Predicting claims frequency and severity for current policyholders and prospective customers.

• Assessing the likelihood of non-payment or early cancellation.
• Determining which prospects are most likely to convert to new customers and predicting their lifetime value.

When insurers identify policyholders with a higher propensity for risk, they can proactively manage these policies more precisely using unique identifiers. Meanwhile, they can handle other policies based on different qualifiers that indicate varying levels of risk. This becomes a game-changer for insurers’ ability to predict and review for underwriting.

Empowering Underwriters

Underwriters are tasked with building profitable books with targeted risk profiles. To be successful, they need to make quick, effective, and accurate assessments of the profitability of each policyholder. However, they are often working with limited or convoluted information and are under considerable time constraints.

Utilizing person-level intelligence in underwriting allows underwriters to focus their craft and expertise on the most complex risks. By integrating person-level intelligence, insurers can:

• Identify High-Risk Insureds Early: Early identification of high-risk individuals allows underwriters to focus on the most complex cases, improving resource allocation.
• Improve Efficiency: With simply using a name and address, significant risk insights can be obtained in seconds.
• Enhance Risk Handling: Focus on complex cases while automating the handling of low-risk applications, improving overall workflow efficiency.
• Provide Personalized Service: Offer coverage tailored to individual risk profiles, moving beyond traditional factors like location and credit scores.

Future-Proofing Insurance Underwriting

For P&C insurers, integrating person-level intelligence into underwriting processes offers a more precise and complete view of the policyholder risk profile. This approach helps insurers better prepare for uncertainty, respond to market volatility, avoid adverse selection, and achieve profitable, sustainable growth. These AI-powered behavioral predictions empower insurers to:

• Predict and Manage Risks More Accurately: Identify high-risk individuals earlier and adjust policies accordingly.
• Enhance Customer Understanding: Gain insights into customer behavior, such as propensity to litigate or likelihood of early cancellation, improving risk management strategies.
• Improve Underwriting Profitability: Achieve more accurate risk assessment and better manage underwriting resources, contributing to healthier bottom-line profitability and sustainable growth.

Using Advanced AI Risk Assessment with Pinpoint Predictive

A more comprehensive and inclusive risk assessment requires a deep understanding of the individual behind the policy, as well as incorporating insights into an insurer’s decision-making processes as part of risk analysis.

Pinpoint Predictive empowers underwriters by enabling them to make smarter, more equitable assessments of risk, accurately identifying high-risk and low-risk individuals. This enhanced accuracy in underwriting workflows helps insurers better serve their customers by identifying and quantifying individual risk earlier and more accurately.

By bridging the gap between the most powerful behavioral predictions made by the world’s leading tech companies and the specialized requirements of the insurance industry, Pinpoint is delivering unmatched risk-selection capabilities at various points along the insurance value chain.

Conclusion

The homeowners insurance sector faces unprecedented challenges. Behavioral intelligence, centered on individuals, represents the next generation of technology, transforming policyholder risk assessments and offering insights into future customer risks. As the industry adapts to these new technologies, the focus will shift toward more informed, efficient, and customer-centric underwriting practices, paving the way for a more resilient and profitable insurance market. Insurers that integrate these advanced risk assessment tools and insights will ultimately be the most successful in enhancing their underwriting processes, addressing the evolving risks associated with new developments and weather events, and ultimately improving financial outcomes.

Improve your Underwriting Outcomes with Pinpoint

With predictions available earlier and more accurately than any other risk solution on the market, Pinpoint is transforming the P&C insurance industry and helping underwriters drive better outcomes with an AI-powered, real-time solution for precise risk selection. For more information about how Pinpoint can help you, visit www.pinpoint.ai or contact info@pinpoint.ai.

The post Addressing Homeowners Underwriting with Behavioral Risk Predictions first appeared on AAIS.

AI Game Changers for Underwriters

With extensive industry experience and a keen eye on the evolution of technology platforms, particularly in AI and underwriting, Schaendorf identified numerous use cases for carriers, especially in underwriting and claims. She also sees significant potential in data access and utilization. Currently, data is often presented in static reports or dynamic formats, but AI has the power to transform how data is interpreted and interacted with.

Advancing Predictive Modeling in Underwriting and Claims Processes

In addressing the future of predictive modeling, Schaendorf explained how Cogitate focuses on its application in underwriting. “We’re looking at the profile of our risks, specifically the risk attributes that come in with each different type of client,” she said. While there are similarities in some variables, many are distinct, and Cogitate’s goal is to use these data attributes to build models that predict outcomes. For instance, Cogitate aims to determine the propensity for a loss ratio based on specific risk attributes.

On the claims side, the objective is to value claims accurately, especially complex ones. “It’s easy to handle the least complex claims, such as glass and towing in auto, but when it [comes] to a case that’s going to go to litigation, how do you set the reserves on that and what does that look like over the life of that claim?” Schaendorf proposed. “I see the ability to use that data and predictive modeling to get a little more accurate and a little better at it.”

Biggest Data Challenges Carriers Face and How to Overcome Them

According to Schaendorf, the biggest challenge carriers face when it comes to data is its structure and accessibility. While some data, like written premiums, policy numbers, and loss ratios, are well-structured, other types are not. This lack of structure poses significant difficulties in obtaining better, more accurate, and more useful data. To address this, Schaendorf believes it is crucial to foster a strong partnership between data professionals and top leadership within a company. “One group has one set of skills, and the other group has the business knowledge,” she explained. Although establishing these standards is time-consuming and may not seem immediately rewarding, they ultimately facilitate faster and more accurate data access.

About Cogitate

Cogitate was formed in 2012 by Schaendorf and her co-founder, Arvind Kaushal, as a digital platform operating on a software-as-a-service model. It is designed to streamline rating, quoting, binding, and issuance across all lines of business, including both commercial and personal lines. This modern-facing platform boasts numerous third-party data integrations, enhancing its functionality. “The proudest thing I can say about Cogitate is it’s an enabler,” Schaendorf shared. Cogitate has seen rapid growth and implementation success with their clients, processing a significant volume of quotes, binders, and premiums through the platform across various lines, such as commercial transportation, personal property, flood, commercial property, and professional liability. “It’s really facilitating growth for our partners, and that’s what we’re most proud of with the company.”

Learn more at Cogitate.com.

To view the full interview with Jacqueline Schaendorf, CPCU, click on the video above.

The post AI, Predictive Modeling, and Data Trends in Underwriting first appeared on AAIS.

Why is GenAI Different?

In our opinion, beyond everything else, the following three characteristics of GenAI make it very different from previous generations of AI/ML:

• Generally Pre-Trained: GenAI tools come out of the box with the impressive ability to understand the English language and reduce the overhead of training task-specific language models.
• Ability to Analyze/Synthesize Complex Language: GenAI can effectively summarize text and create new content with little training.
• Large Context Abilities: GenAI tools can work on large volumes of text to draw inferences.

Insurance Complexities and Limitations of Traditional AI

Insurance is saddled with enormous manual processes that make it error-prone, expensive, and slow. A lot of insurance processes still rely on exchanging documents up and down the value chain. Brokers need to fill out complex forms, review multiple quotes and policies to effectively inform their insured clients about their choices, and then check policies thoroughly for errors. Issuing certificates, managing mid-term alterations, and renewals are all still largely done manually. Insurance companies are also still analyzing forms sent by brokers, reading claims reports and matching them against policy coverage, issuing reinsurance bordereau, and performing many other similar tasks manually.

Traditional ML tools cannot process and analyze insurance language or extract insights from these complex documents. Standard workflow and robotic processing automation (RPA) technology do not support true AI-guided workflow or AI-guided human review and decision-making. This is where GenAI can make a huge difference.

The BluePond.AI Approach to Making GenAI Work in Insurance

While GenAI tools natively bring a high degree of English language understanding and analysis capability, they do not understand insurance concepts. To make effective software for automating human tasks, machines need to understand the insurance terminology, the context of a process or purpose of a document, the references between various documents (e.g., the policy associated with a claim assessment report), different coverage types, and more.

Therefore, to solve complex insurance process automation and document-understanding tasks, BluePond.AI has built our proprietary “P&C Domain Reference Library” to serve as a repository for insurance language, entities, values, fields, coverage, and document types. This reference library is the master orchestrator of the repository consisting of traditional and GenAI tools that, when used in symphony, can execute tasks like a trained insurance professional, thus creating a unique P&C insurance “CoPilot.”

Whether you’re an insurer, reinsurer, third-party administrator, or broker, our GenAI-based “CoPilot” approach can help resolve persistent challenges within the insurance industry.

Insurers & MGAs

• Automatic Audit of Delegated Underwriting: GenAI can assist with the automatic monitoring of policies written under delegated underwriting authority by program managers, MGAs, or cover holders, to ensure issued policies comply with underwriting guidelines at the time of underwriting.
• Claims Document Monitoring: GenAI tools can automatically identify incoming documents, extract data enabling the population of the claims system, and flag any major risk or severity factors.
• Ingestion of Loss Assessor Notes: GenAI can identify, match, and extract event details and loss cause/estimate from assessor notes. Plus, it can generate claim trends, seasonality, and complexity insights for underwriting and product development.
• Matching Claims to Policy Coverage: GenAI can offer automatic matching of claims against policy coverage, including looking through language that changes coverage under certain circumstances.
• Policy Checking: GenAI tools can help with checking issued policies against submission data, underwriting instructions, and prior terms to ensure there are no errors.

Brokers and Agents

• Policy Checking: Despite Errors and Omissions (E&O) lawsuits against brokers being on the rise, many brokers and agents struggle to make time for tedious policy checking. With GenAI, policies can be checked thoroughly against expiring quotes and detailed submission schedules when and where required.
• Quote Comparison: GenAI can create easy-to-understand summaries of complex quotes from different carriers/MGAs even if they widely differ in format and inclusions.
• Certificate of Insurance (CoI) Issuance: CoI processing is largely a manual process, with various types of non-standard requests making it a complex, time-consuming, and expensive operation. With GenAI tools, we can automate the understanding of CoI requests, extract the right information from policies, and digitize request processing – taking a big operational load off agents’ shoulders.
• Submission Verification & Inspection Matching: GenAI can intelligently automate submission data verification across various documents and cross-check against third-party data sources.
• Placement Recommendations: GenAI tools build recommendations on the right coverage for the insured and best-suited markets to place the risk based on the extraction of data from historical quotes and policies of similar insureds.

Reinsurers

• Bordereaux Ingestion: Data entry from numerous long bordereaux remains an operational challenge for reinsurers, which also creates information asymmetry and can lead to leakage of premiums and overpayment of claims. With GenAI-based tools, reinsurers can extract granular data from premiums and claims bordereaux, saving time and cost of data entry while also ensuring treaty conditions are being complied with at a granular level.
• Claims–Premium Matching: GenAI can automatically match claims information in relation to the assumed (or ceded) premiums and direct premiums through various contract documents to help improve inaccuracies and manual errors.
• Run-Off Book Monitoring: GenAI tools allow reinsurers to set their own parameters to monitor run-off claims development and flag any adverse or unexpected developments.
• Loss Portfolio Transfer (LPT) Assessments: LPTs carry billions of dollars of investments and need an accurate analysis of the underlying portfolio to avoid the risk of underperformance. With GenAI tools, the bottom-up assessment of an LPT book becomes feasible, with the ability to scan for exact exposures carried in the policies, assessment of reserve adequacy, adverse claims development indicators, and more.
• Audit of Cedent Underwriting: GenAI can perform data-driven audits of cedent underwriting based on ingestion of details from bordereaux and cedent underwritten policies.

BluePond.AI: Taking the Friction out of Deployment

The potential of GenAI in the insurance industry is vast. We foresee there being a significant ability to automate complex human processes, leverage AI to guide human review and decision-making, and extract not just data, but also insurance insights from the language in complex documents. That’s why we created the P&C CoPilot Platform. The platform can analyze documents, extract values and fields, and derive insurance insights from complex language (e.g., coverage comparison from two different types of policy documents). However, one might wonder about the difficulty of executing a GenAI strategy in-house. Even if you have a team with deep experience in software engineering or traditional AI, the fundamental construct of GenAI systems is different so it requires a different approach to execution.

For that reason, we have configured our P&C CoPilot Platform as a ready-to-deploy Platform as a Service (PaaS) for any P&C industry participant. With this approach, you will not waste time procuring, testing, configuring, and integrating the fundamental building blocks that are required for a typical GenAI application. The platform is fully configured and ready for quick deployment either as a fully managed PaaS in your environment or as a multi-tenant Software as a Service (SaaS) in ours. It is designed to connect to various data and document sources, an API gateway to connect to internal and external services, and enable seamless enterprise integration.

BluePond.AI manages the ever-evolving GenAI landscape and connects to various best-of-breed services behind the scenes so that you can focus on the insurance use case. We offer complete execution support on data science and software engineering, and post-production human-in-the-loop processing support if required. Even if you have the right GenAI expertise and infrastructure, our platform can still save up to 12 months of setup time and expenses, while providing use case acceleration with our P&C reference library.

To learn more about BluePond.AI and how you can successfully leverage GenAI, visit www.bluepond.ai.

The post The Art of the Possible with GenAI in Insurance first appeared on AAIS.

Catastrophes, higher building costs, and inflation are all impacting commercial underwriting performance and insurer profitability. Proper portfolio valuation is becoming exponentially important as the reinsurance market tightens. So, how can insurance companies better manage their books of business now and into an uncertain future? The answer is rooted in addressing valuation issues by tapping third-party vendors. The answer is tied to partnering with a robust digital platform provider. The answer is collaboration.

In the past, it was easy for insurers to dismiss data as untrustworthy because they didn’t want to invest in it. Now, third-party vendors present necessary advances that help to paint the bigger picture. Platforms like OneShield are the glue that brings these tools together. And, not just for underwriting purposes. In the commercial lines business, customers are generally good risk management partners. OneShield and its customers have seen tremendous engagement with agents and policyholders who want to proactively manage risk. Failing to enable that is a missed opportunity.

Undervaluation Issues

One critical issue plaguing the commercial property insurance sector is undervaluation. Many insured properties are not accurately valued, leading to potential discrepancies when claims occur. This issue is exacerbated by the changing climate, which has expanded the geographic reach of natural disasters.

The Tightening Reinsurance Market

A convergence of global events leading into 2023 resulted in the hardest property-catastrophe reinsurance market in generations. Tightening reinsurance capacity puts pressure on carriers and raises both portfolio-level and granular questions. Commercial insurers are digging into the vulnerabilities and susceptibilities of individual properties.

Beyond Underwriting

A crucial takeaway from a past webinar with OneShield and AAIS was the need for insurers to go beyond traditional underwriting practices to effectively manage a book of business into the future.

We emphasized the value of using data not only for new business but also for existing clients. The webinar showcased how third-party data and insights enhance insurers’ risk management capabilities. Platforms like OneShield act as central hubs that connect these data-driven tools, enabling insurers to engage with agents and policyholders for proactive risk management.

The Path Forward

To remain competitive in the ever-changing commercial insurance space, carriers will need to continue to embrace change along with the unknown, adopting new technology and tools along with data-driven processes to improve loss ratios and customer satisfaction. Each carrier’s path forward is different. What matters most is they begin taking steps to implement new tools and data into their processes that improve loss ratios and customer satisfaction.

About OneShield

OneShield Software provides business solutions for P&C insurers and MGAs of all sizes. OneShield’s cloud-based and SaaS platforms include enterprise-level policy management, billing, claims, rating, relationship management, product configuration, business intelligence, and smart analytics.

Designed specifically for personal, commercial, and specialty insurance, our solutions support over 90 lines of business. OneShield’s clients, some of the world’s leading insurers, benefit from optimized workflows, pre-built content, seamless upgrades, collaborative implementations, and pricing models designed to lower the total cost of ownership. Our global footprint includes corporate headquarters in Marlborough, MA, with additional offices throughout India.

For more information, visit OneShield.com.

The post Commercial Property Preparedness: Bracing for Changing Risks first appeared on AAIS.

Overview of Orion180 & Chrp Technologies

Orion180 is a technology-based insurance company that utilizes cutting-edge technology paired with outstanding customer service to simplify the insurance experience and enhance the customer experience. They are primarily HO3 in six southeast states but are beginning to roll out other products in more states. Chrp Technologies helps home insurance companies build great relationships with their insureds through proprietary AI products that deliver loss prevention and an enhanced customer experience. Chrp has seen tremendous success with clients like Orion180.

Finding Solutions by Utilizing AI Tools

Orion180 as a company focuses on three areas: efficiency, accuracy, and customer experience. “Our challenge was timely identification of risk and issues,” Wyrick shared. “Specifically, having inspections completed, allowing us time to review them, and giving the insured time to repair anything that we found had adverse conditions. So, we really needed to streamline that process to make it more efficient.” Accuracy is also extremely important to Orion180 because they base their outcome on the data that’s provided back to them from inspections. And, overall, the inspection process is a customer experience. What attracted Orion180 to Chrp Technologies was the ease of use and that it hit all three of the company’s focal points. “From an efficiency standpoint, it’s an automatic process,” said Wyrick. “You don’t have to manually order inspections, follow up, track, and keep all that data together. [The] AI built into the platform is accurate. We’ve gone from months of training time down to weeks. And if we have an issue, I know Chin and his team will be there on the customer experience side.”

Impact on Retention Rate & Policy Holder Engagement

Since partnering with Chrp, Orion180 has been able to retain its policies. “When we launched Chrp, our average date of a completed inspection returned was around 16 days,” Wyrick reported. “With all of the updates, we went from 16 days to now nine days completed and it’s still dropping. We’ve got drastically increased policy retention because we’re able to review those risks and provide those solutions and keep that policy.” Wyrick believes this process with Chrp has made policyholders more aware of their risk and its impact on insurance.

Overcoming Challenges

Being a company born out of Florida, Ma admits one of the biggest challenges for Chrp is that a lot of its customers are of an older demographic and do not feel they are tech-savvy enough to use the service. “So, one thing that we’ve put into place right away is a seven-day-a-week, 365 customer service model,” said Ma. “In our company, you go through a rite of passage called the legendary conversation.” This is essentially walking a customer through the inspection process and guiding them through the app. These conversations with customers influence the way that Chrp designed its application. “Those are the types of conversations and experiences that give us the opportunity to make improvements.”

Insight on How Chrp Works

Chrp complies with two mission statements: Eliminate Non-Cat Claims and Help People Have Healthy Homes. “Conducting inspections is [not] a new thing for the insurance industry,” Ma confessed. “But doing so the right way is incredibly important. Right now, the ‘right way’ also necessitates an economic model that works with an underwriting.” Being able to leverage self-inspections in concert with physical inspections, in a cost-effective way, is a huge plus in driving volume, according to Ma. Then, the correct symptoms that lead to claims need to be analyzed. “If you get those two things right, you should see a high inspection conversion, roughly between 75% to 85%, on the self-inspection side. Blended cost-wise, that can actually reduce your overall inspection cost,” he stated. Chrp delivers highly accurate AI to streamline what symptoms require underwriting action and also offer a solution to customers so they can prioritize their time. This leads to the end result, which is how to eliminate non-cat claims to ultimately improve profitability.

When the inspection report comes through to the customer, any adverse conditions that the AI has found are listed first. “We’re looking at those first before we even get through the rest of the inspection,” Wyrick shared. “That’s the efficiency aspect of [Chrp]; we can see right off the bat what’s wrong. If it’s bad enough, we’ll already know how this risk is going to end up.” But the best function of the Chrp platform in Wyrick’s opinion is the ability to escalate inspections. “If we have a reviewer that’s kind of guessing at something or if they have a question, they can escalate that inspection to a new cue, and myself or another senior member can go in to look and write our notes. Then it goes right back to that inspector.”

To view the webinar in its entirety, click on the video above.

Questions? Please don’t hesitate to reach out to any of the featured speakers through the contact information below.

Werner Kruck
President & CEO – AAIS
wernerk@aaisonline.com

Chin Ma
President – Chrp Technologies
cma@chrptech.com

Brandi Wyrick
AVP of Experience – Orion180

bwyrick@orion180.com

The post Webinar: Leveraging Today’s Underwriting Technologies to Modernize Homeowners Insurance first appeared on AAIS.