5 Ways MGAs can Boost Insurance Claim Process with AI

MGAs are competing with one another to set themselves apart with novel goods and services. Conning estimates that the US MGA market will continue to grow, with premiums estimated to reach over $80 billion in 2023, a 13 percent increase from the previous year.

Growing competition from both new start-ups hoping to take advantage of the opportunities and more established MGAs is driving this expansion. The MGA can usually swiftly establish new offers and increase its market share if it is the first to introduce a new product to the market.

AI tools are helping MGAs accelerate time to market. These tools range from more recent generative AI platforms to more traditional machine learning solutions. From product introduction to retail distribution, these technologies can impact everything.

Let’s take a look at some ways Artificial Intelligence (AI) solutions can help MGAs bring new products to market faster:

1. Beating the Marketing Trends

AI tools are not new to Managing General Agents (MGAs). For years, many MGAs have integrated AI technologies such as machine learning and robotic process automation into their operations. Given the insurance sector's heavy reliance on documentation, these tools have proven invaluable. For instance, MGAs have used AI to automatically extract and populate their systems with information from documents like statements of value, loss run reports, and submission applications, significantly reducing the need for manual data entry.

With the rise of Generative AI (GenAI), MGAs now have the ability to combine data processing with advanced content generation, offering deeper insights into emerging market trends. For example, Intelligent Documents Processing (IDP) can extract relevant information from the vast array of documents collected by MGAs and feed that data into predictive models. These models can then forecast risk appetites, set optimal pricing, and make decisions on whether to offer specific terms and conditions.

Furthermore, GenAI can incorporate data from third-party sources to enhance the accuracy of these models. For instance, after a significant event like the Baltimore bridge collapse, an MGA could use GenAI to analyze market conditions and assess the demand for new insurance products that protect ships traveling through newly identified high-risk zones.

By leveraging AI-driven insights in their modeling processes, MGAs can identify untapped market opportunities and develop innovative insurance products ahead of their competitors. For example, by analyzing real-time data trends and external market shifts, an MGA might create a unique policy tailored to a newly emerging risk category, gaining a first-mover advantage.

2. Spreading the word

The MGA notifies its distribution network about the newest offering as soon as a new insurance product is prepared for launch. Whether or not the product is a good fit, an MGA used to have a general strategy and deliver information to every retail agent; this may occasionally cause certain retail agents to ignore pointless messages.

Insurance Agents may ensure that the goods reach the agents who are most interested in selling that kind of coverage by using GenAI to conduct customized marketing. Additionally, by using GenAI technologies, the MGA may develop personalized messages for various agents that highlight the ways in which the new product will benefit their clientele.

For MGAs, getting to market quickly is crucial. By employing GenAI engines, they may reduce expenses and their influence on the target implementation date, remain ahead of the competition, and develop products more rapidly and efficiently while identifying new areas of need and launching them ahead of schedule.

Also Read: How Insurance Agents are Using AI

3. Optimizing Claims Processing

Claims processing is another area where MGAs can leverage AI to improve speed and efficiency. The traditional claims process often involves multiple steps, including data entry, document verification, fraud detection, and payout approval, which can take days or even weeks. AI solutions, such as Natural Language Processing (NLP) and machine learning, can automate these steps by analyzing claims documents, cross-referencing data, and identifying anomalies that might indicate fraud.

For example, Zurich Insurance Group utilizes AI to predict claims severity and prioritize cases, which helps in faster processing and settlement. AI tools like these can drastically cut down the time it takes to resolve claims, reducing operational costs and enhancing customer satisfaction. MGAs using AI to optimize claims handling can not only speed up their internal processes but also build a reputation for reliability and efficiency in the market.

Also Read: How is Artificial Intelligence (AI) used in the Insurance?

4. Improving Compliance and Regulatory Reporting

Insurance is one of the most heavily regulated industries, and compliance is a constant concern for MGAs. AI can streamline compliance by providing real-time monitoring and automated reporting tools that ensure adherence to regulations. These AI tools can automatically generate compliance reports, flag potential issues, and reduce the risk of costly penalties.

For example, after a new regulation is introduced, an AI system can quickly assess all existing policies and identify those needing adjustment to comply with the new rules. By speeding up these processes, MGAs can bring new products to market without getting bogged down by regulatory hurdles. IBM Watson, for instance, provides AI-powered tools that help insurers and MGAs navigate the complex regulatory landscape, minimizing compliance risks and enhancing operational efficiency.

5. Expediting product launches

The majority of MGAs are intensely concerned with gaining market share, thus they must launch products fast before rivals provide comparable coverage. The speed-to-market objective suffers when a new product is set up in an MGA's policy administration system since it takes a lot of time and money.

MGAs are able to greatly expedite this procedure because to GenAI. It can be applied to develop the product's commercial requirements. The coding required to add the new product to the platform can also be assisted by the technology.

When the product is prepared for release, GenAI solutions let the MGA cover customers more quickly. AI-powered technologies are able to scan retail agents' submissions, identify applications lacking information, and assess if they comply with underwriting standards. After that, the underwriter can finish reviewing and devote more of their time to reviewing submissions with greater complexity.

Conclusion

Incorporating AI into their core operations allows MGAs to achieve faster time-to-market and greater operational efficiency. From automating underwriting and claims processing to enhancing customer experience, driving data-driven product development, and ensuring regulatory compliance, AI provides numerous opportunities for MGAs to outperform competitors and meet evolving market demands. As the insurance industry continues to evolve, MGAs that embrace AI-driven innovation will be best positioned to thrive in a fast-paced, competitive environment.

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