5 Ways MGAs Can Leverage AI To Streamline Operations

Managing General Agents (MGAs) are at the center of a digital revolution in the insurance industry. With increasing amounts of submissions, decreasing margins, and ongoing pressure to enhance underwriting precision, operational efficiency is more important than ever. AI is rapidly emerging as the solution MGAs need to automate tasks that are currently being done manually, adding to profitability and simplifying their overall process.

For MGAs, applying AI doesn’t mean replacing human expertise – it means enhancing it. When used strategically, AI can automate manual processes, improve risk assessment, and expedite decision-making, which frees teams to focus on higher-value work that requires expertise and judgment. 

In this article, we’ll explore why AI matters for MGA operations, how it can be implemented, and five high-impact use cases that can transform your bottom line.

Why MGAs Need AI for Operational Efficiency

MGAs are unique players in the insurance industry, essentially acting as full-service insurance providers without assuming the same level of capital risk. However, this autonomy comes at a cost. MGAs often juggle high volumes of submissions each month, reconcile complex bordereaux reports, and manage compliance obligations across multiple lines of business. 

Claims teams face similar inefficiencies, sifting through reports, emails, and policy documents to determine eligibility and next steps. Not only are these processes slow and prone to error, they also tie up skilled professionals with tasks that AI could easily handle.

AI automates routine and repetitive tasks, which not only reduces errors and lowers costs, it unlocks the capacity to process more business without increasing headcount. MGAs that implement insurance automation can achieve meaningful efficiency improvements which often lead to boosted profitability and productivity.

Common Hurdles in AI Adoption

Despite the clear benefits, there are still many misconceptions around complexity or fears of disruption surrounding AI that have left many MGAs hesitant about adopting the technology. One common concern is the belief that AI implementation requires a total overhaul of existing systems. In reality, however; modern AI platforms like Brisc can integrate with MGA technology stacks using APIs and data connectors, working in tandem with legacy systems.

Another common obstacle MGAs can face with AI adoption is the risk of inaccurate or fabricated outputs, often referred to as AI hallucinations. Generic AI models, trained on broad datasets, can miss the nuances of insurance language, workflows, and data structures. That’s where insurance-native platforms like Brisc stand apart. With domain expertise embedded in every agent, Brisc delivers highly accurate outputs grounded in your specific data, context, and processes—so MGAs can trust the insights and automate with confidence.

Compliance is also top of mind. AI in insurance must operate within strict regulatory frameworks. This includes explainability —knowing how an AI system arrived at a decision—and data privacy. The good news is that reputable insurance AI vendors build compliance and transparency into their platforms, often exceeding industry standards.

To look at the benefits AI can bring, consider the following:

Five Ways MGAs Can Leverage AI to Streamline Operations

1. Automate Labor-Intensive Underwriting Tasks

Reviewing applications, validating documents, and assessing risks are all time-consuming, especially when done manually. AI can automate a significant portion of this process.

Natural language processing (NLP) tools can extract data from structured and unstructured documents, such as PDFs, emails, SOVs and more. Machine learning models can then validate that data, identify missing information, and flag potential inconsistencies. AI systems can also score and classify risk based on predefined criteria and past claims history.

For example, AI can automatically triage submissions, prioritizing those that match an MGA’s appetite and flagging high opportunity applications for deeper review. This doesn’t just speed up the process—it improves consistency and reduces human error. By automating these tedious tasks, underwriters are empowered to focus on the right opportunities and deliver quotes faster, increasing quote to bind ratio.

2. Accelerate Submission Processing With Intelligent Data Extraction

One of the most common inefficiencies in MGA operations is the manual entry of data. Brokers send submissions in various formats, and underwriters are left copying and pasting information into core systems. It’s not only tedious but also extremely error prone.

AI-powered data extraction tools solve this by using OCR (optical character recognition) and NLP to scan unstructured documents and extract structured data fields automatically. Submission details, such as insured name, location, limits, exposures, and prior loss history, can be populated into underwriting systems in seconds.

This speeds up the intake process dramatically—often reducing submission processing times from hours to minutes. More importantly, it enables faster response times, which improves broker satisfaction and helps MGAs win more business.

3. Enhance Risk Analytics and Pricing Using AI Underwriting

Risk assessment and pricing are where AI can deliver profound benefits. Machine learning algorithms can analyze historical claims data, industry benchmarks, and third-party datasets to identify risk patterns and inform more precise pricing strategies.

For instance, AI can recognize non-obvious correlations in loss history that traditional models might miss. Predictive modelling can forecast the likelihood and severity of claims, enabling underwriters to adjust pricing or proactively decline certain risks. AI can even incorporate external data sources—like weather patterns, credit scores, or industry-specific trends—to supplement internal underwriting models. The result is more accurate pricing, better risk selection, and, ultimately, improved loss ratios. 

4. Streamline Claims Management for Faster Resolution

Claims management is another area where AI shines. From initial intake to settlement, AI can automate key stages of the process, improving speed and consistency while reducing costs.

For example, AI can automatically extract information from First Notice of Loss (FNOL) reports, classify claims based on severity, and route them to the appropriate adjuster. NLP tools can analyze claim narratives and identify potential fraud indicators, including suspicious patterns or language.

By reducing manual claims handling time and standardizing processes, MGAs can not only resolve claims faster but also detect and prevent fraud more effectively. 

5. Integrate AI in Bordereaux Management

Bordereaux management is one of the most time-consuming and error-prone processes MGAs face. AI can simplify and automate much of the management lifecycle, from bordereaux reconciliation to production and reporting.

It can extract and standardize data regardless of file format or terminology, validate entries against internal records, and automatically flag discrepancies or missing data points.

AI can also generate reports tailored to carrier and reinsurer requirements, helping MGAs deliver accurate, timely information that builds trust and transparency. For MGAs managing multiple programs across different carriers, this is a game changer for improving accuracy and efficiency.

Ensuring Data Quality and Compliance

High-quality data is the foundation of any effective AI system. Before MGAs can fully realize the benefits of automation, they must ensure their data is clean, consistent, and well-governed. This often involves consolidating data sources, defining data standards, and implementing validation processes at the point of entry.

Compliance must also be a top priority. AI systems should provide full auditability, enabling MGAs to document the decision-making process and meet regulatory requirements regarding fairness, transparency, and data protection. Leading insurance AI vendors offer built-in compliance features, including data encryption, access controls, and adherence to SOC 2 or GDPR standards.

Looking Ahead: Scalability and Future Trends

AI is not just a short-term fix—it’s a long-term strategy for scalability. Once in place, AI systems can be extended across the MGA workflow, encompassing underwriting, claims, marketing, and more. As AI models continue to learn and improve, the benefits compound over time.

Emerging trends, such as generative AI, real-time risk scoring, and AI-powered customer chatbots, will further reshape how MGAs operate. For forward-looking MGAs, adopting AI now means laying the groundwork for sustainable growth and agility in a rapidly evolving market.

To see how Brisc’s insurance-native AI platform can transform your MGA operations, book a demo today.