AI-powered underwriting platform: Solving underwriting challenges with AI 

McKinsey’s Insurance Report 2023 estimates that insurance companies lose around $13 billion per year because of legacy underwriting software and processes. Traditional underwriting is time-consuming, manual, and relies on underwriters’ experience and ability to analyze large volumes of data from disparate sources.  

However, many insurers are shifting towards new ways of underwriting — powered by advanced technology like artificial intelligence. This post reveals how AI can help insurers solve their challenges with cumbersome underwriting. 

Traditional underwriting challenges

Traditional underwriting faces several challenges. We highlighted the following as the most important. 

1. Many underwriters still collect and process data manually. Underwriters spend a bigger portion of their time gathering the required data from emails, financial statements, medical records, third-party data sources, and applications. This information is usually unstructured and requires manual review.  
2. Underwriting specialists lack real-time data to make effective decisions. Manual data processing takes days or even weeks to finish due to the need to review piles of fragmented data. It leads to significant delays in approvals and customer frustrations with the insurance company’s services.  
3. Risks are assessed inconsistently. Traditional underwriting usually relies on individual underwriters’ judgment and expertise, which is not always objective. Two different underwriters evaluating a similar application might have different conclusions and decisions, respectively.  
4. Operational costs are growing. Obviously, manual jobs and a growing number of applications require additional human resources. Insurance companies usually try to scale without increasing the headcount, which leads to inefficient processes, inaccurate decisions, and profitability losses. 
5. It’s difficult to detect fraud.  It’s challenging to detect fraud if you review applications manually. Underwriters can miss hidden fraud patterns, leading to losses and financial risks. 

How AI solves underwriting challenges

Artificial intelligence has become a game-changer for almost every industry. It’s hard to imagine a business that hasn’t been impacted by AI. According to Morgan Stanley’s AI Adopter survey (July 2025), AI adoption among insurance companies grew from 48% in January to 71% by July 2025, marking one of the fastest growth rates within the financial sector. It’s not surprising that this technology can be used to address the challenges we mentioned above effectively.  

AI collects data automatically 

With the help of Natural Language Processing (NLP) and Optical Character Recognition (OCR), AI algorithms extract data from structured and unstructured sources by scanning the PDF files, handwritten forms, financial documents, medical records, and many more.  

AI helps underwriters assess risks in real time 

Being trained on historical data, Machine Learning (ML) models can evaluate the risks immediately. Based on the assessment, these models provide underwriters with further information and recommendations for the decisions. It facilitates faster approvals and enhances customer experience. 

Artificial Intelligence facilitates objective and consistent decision-making 

Predictive analytics, predefined parameters, and rules — all ensure that decisions are made without bias and subjectivity. It increases customer loyalty and trustworthiness of your company. 

Fraud is analyzed by AI much better than manually 

AI allows early detection of fraud by analyzing vast volumes of information with predictive modeling, anomaly detection, and pattern recognition. Early identification of fraud can protect insurance companies from substantial losses. 

AI reduces operational costs  

Costs are reduced by automating manual and repetitive tasks. With no need to do the majority of tasks manually, underwriters can focus on more complex tasks. 

Key components of our ready-made Underwriting Workbench

Here at DICEUS, we have developed a ready-made software solution — Underwriting Workbench — designed to support effective decision-making and collaboration between underwriting specialists, brokers, and Managing General Agents. Below is a list of key features we offer to efficiently do risk selection and make decisions.  

• Dashboard with a view of all submissions and a full portfolio 
• Workflow automation module  
• Risk assessment engine powered with AI recommendations 
• Rule-based automation for making decisions on low-risk applications  
• Analytics and reporting  
• Integration with data providers, rating engines, and core systems  
• Reminders and notifications with workflow-based triggers 
• Premium calculations, pricing scenarios, and quote generation 
• Support for multiple commercial lines  
• Collaboration with brokers, MGAs, and other partners 
• Underwriter KPI tracking  
• Unstructured submissions capture (PDF, email, Word, etc.)  
• Clash check and risk overlapping detection   
• Bordereaux processing  

Want to see Underwriting Workbench in action? Discover it! 

Use cases of AI in underwriting

So, where is artificial intelligence changing the way underwriting is being done? Underwriting is the process inherent in every insurance business line, so we gathered the most popular ways AI helps do that for each line. 

Health and life insurance. Artificial intelligence can be used to analyze lab results, medical records, and lifestyle to evaluate mortality or similar risk factors.  

Car insurance. AI is widely used to integrate telematics, which improves the accuracy of premium calculations by helping underwriters consider drivers’ behavior and vehicle data. 

Home insurance. Property images, weather history, satellite data, and other information useful for property risk selection can be analyzed by AI. 

Commercial insurance. Here, AI can assess financial documents, market trends, credit scores, and other important information that impacts business risks. 

Learn more about the benefits of AI in underwriting in our comprehensive article on this topic. 

To sum it up

AI-powered underwriting platforms are revolutionizing the insurance industry by solving traditional challenges of manual data processing, inconsistent risk assessment, high costs, and limitations in fraud detection. 

Insurers implementing AI underwriting solutions gain faster processing times, improved accuracy, reduced operational costs, and enhanced customer experiences, positioning themselves competitively in a digital-first market. 

Is your organization ready to embrace AI in underwriting to unlock these benefits and lead the future of insurance?