Grid Dynamics Ebook
Are small insurers being left behind?
How can generative AI help them succeed by streamlining product filings, compliance, and brokerage?
DOWNLOAD EBOOK
Thriving in the insurance industry depends on accurate risk pricing, and the more data you have, the sharper your pricing becomes. When small insurers struggle with limited data, particularly in new markets, generative AI and large language models (LLM) can help tap into historical filing data to sidestep compliance issues, assist actuaries in nailing down accurate risk and premium calculations, and create product filings that sail through approvals—turning pricing challenges into growth opportunities.
Thriving in the insurance industry depends on accurate risk pricing, and the more data you have, the sharper your pricing becomes. When small insurers struggle with limited data, particularly in new markets, generative AI and large language models (LLM) can help tap into historical filing data to sidestep compliance issues, assist actuaries in nailing down accurate risk and premium calculations, and create product filings that sail through approvals—turning pricing challenges into growth opportunities.
The U.S. P&C insurance market is massive, valued at $873.7 billion, and growing steadily, with an average increase of 1.5% each year over the past five years. But for small carriers, it’s tough to break in.
From natural disaster risks to strict regulations like California’s rate limits squeezing profits, or costly legal battles in states like Florida, staying afloat can feel impossible. Add fierce competition from big players, and many small companies are forced to leave these markets.
So, how can small insurers overcome these barriers and compete with industry giants?
The answer lies in precise risk pricing. By leveraging generative AI and large language models, small insurers can automate the analysis of both structured and unstructured data, providing rapid insights into existing products, pricing strategies, economic trends, and consumer behavior. This enables them to adjust pricing, benchmark against competitors, turn past objections into strengths, ensure regulatory compliance, and enhance broker-client relationships—ultimately giving them the edge to thrive in the market.
Analyze product filings for effective benchmarking
Uncover valuable insights from insurance product filings to improve benchmarking, streamline approvals from state departments of insurance (DOI), and successfully launch products in regulated markets. These filings, which detail new or revised products, contain essential information for compliance teams and actuaries, including objections from state regulators. For example, New York mandates that tenant insurance filings clearly outline renter protections, emphasizing the importance of compliance in product filings.
Ensure post-filing regulatory compliance and consumer protection
Adapt policy documents to new regulations, streamline the renewal process, and keep existing customers informed with real-time, accurate information using conversational AI assistants. LLMs can process regulatory documents and identify key requirements to ensure strict adherence to consumer protection rules and financial solvency standards, covering everything from policy language to sales practices and claims handling. This results in the creation of straightforward policies, accurate disclosure documents, and effective coverage validation.
Augmenting human brokerage with direct engagement
Leverage LLM-powered chatbots to establish direct engagement channels that augment brokerage and help expand the business into new regions by keeping costs low while offering personalized advice and 24/7 support. By automating the analysis of policy details, claims, emails, and social media, these tools rapidly assess claims, detect fraud, and minimize risks—allowing small insurance brokers to focus on what really matters: strengthening relationships with clients.
Key takeaways
1. Turn historical objections into opportunities
Decipher historical objections from existing filings, which reveal the back-and-forth between insurers and DOIs over regulations and unwritten ‘desk rules,’ to better understand how state laws are enforced, streamline future filings for quicker approvals, and tap into the real value of deeper unstructured data within these filings.
Get EBOOK
2. Build stronger ties with DOI using accurate filings
Channel effective benchmarking to create filings that align with state regulations, follow actuarial standards of practice (ASOP) by outlining the steps actuaries should take and what they need to disclose in their reports, and build stronger connections with the DOI by submitting accurate, well-prepared filings that refine the review process and foster collaboration.
Get EBOOK
3. Effectively handle coverage validation for specialty policy claims
From confirming whether the peril or event is covered to determining what is included in the policy, such as location or contents, multimodal LLMs can significantly assist adjusters by interpreting complex policy language and directing them to relevant sections, thus expediting the claim process and reducing litigation risks.
Get EBOOK
4. Automate financial solvency compliance and reporting
Ensure financial solvency by leveraging LLMs to understand state regulations on reserve requirements and financial reporting, and to maintain a healthy assets-to-debt ratio based on the insurer’s risk exposure, available cash reserves for immediate claims, invested funds for future claims, and reinsurance for high-risk or concentrated contracts.
Get EBOOK
5. Create continuous product improvement loops
Analyze past brokerage-client interaction logs using generative AI, revealing patterns in preferences and behaviors, and deliver tailored insurance packages that meet unique needs—taking into account factors such as location, business type, and growth potential—effectively bridging the gap between business goals and customer expectations.
Get EBOOK