AI
December 6, 2024

AI use cases in Property and Casualty (P&C) insurance industry

Create your own AI assistants using on your data & deploy it on channel of your choice. All without writing one line of code.

The Property and Casualty (P&C) insurance industry is at a crossroads, facing a mix of old challenges and new opportunities. With inflation squeezing policyholders' wallets, they are demanding simplicity, transparency, and—most importantly—affordable premiums. 

Yet, the traditional processes that insurers are struggling to keep up, primarily because of manual underwriting, inconsistent claims handling, and slow customer service dragging down efficiency. 

Insurers are definitely getting exposed to rising costs. But to make matters worse, external pressures like natural disasters, cyber risks, and regulatory threats have pushed combined ratios past 100%

These are clear red flags in operations and something needs to change. But where do we start? From reducing process inefficiencies to managing new, unpredictable risks, the key lies in integrating the right AI solutions.

How can AI help? 

AI finds its application in multiple areas in the P&C insurance industry. The technology streamlines operations and improves efficiency across various operational processes – right from onboarding and training new recruits to automating key tasks like summarizing data, sales, customer support, and claims processing. 

Source: Sapiens Report

AI-driven tools are practically changing the way insurers operate in every aspect. By integrating AI technologies into their operations, insurers get to reduce costs, improve accuracy and speed, and customer satisfaction. 

Despite so many benefits, only a handful of insurers, 8% to be precise, are consistently outperforming mainstream carriers by using AI-driven insights and automation to make informed decisions and accurate risk assessments with efficiency. 

In this blog, we will understand how AI is changing the dynamics of the P&C industry in areas like onboarding, training recruits, task summarization, sales, customer support, and claims processing.

1. Onboarding

Onboarding is one of the most time-consuming steps in the P&C insurance process. It involves collecting customer information, verifying documents, setting up accounts, and offering personalized coverage options.

Before AI:

Before AI, much of this work was manual: agents would input data, verify documents slowly, and often provide generic policy recommendations. The process led to bottlenecks, inconsistencies, and a lengthy process with several touchpoints.

After AI:

With the use of AI, the change is clear. AI-driven OCR (Optical Character Recognition) tools now automate data extraction and entry, while machine learning models handle instant document verification and fraud detection. Predictive analytics further personalize coverage options based on customer data. 

Case Study of a Leading Asian Bank

Assurance IQ, a leading insurance company, reached out to Alltius to improve agent onboarding efficiently as well as assess and fine-tune three specific assistant skills that would provide the maximum value to Assurance’s sales agents. 

They wanted to create an AI assistant that provides clear, concise responses to customer queries like "My client is a 60-year-old woman in Atlanta who utilises physical therapy, has glaucoma, and prioritises dental benefits. Which plan would best suit her?" 

Alltius created a product discovery assistant by processing over 6,000 plans, each with multiple pages. Assurance's team utilised Alltius' APIs to quickly generate thousands of responses for a sample set.

Read entire case study here

Benefits for Company:

  • Automating repetitive tasks cuts operational costs. 
  • Accelerated onboarding process 
  • Improved accuracy and regulatory compliance. 

Benefits for End User:

  • A quicker, smoother experience.
  • Personalized insurance coverage.
  • Fast verification and fewer errors.

Metrics Affected:

  • Onboarding time reduced by more than 60%.
  • New agents could reach mid-level productivity three times faster.
  • A 20% improvement in overall productivity over an average two-year tenure for agents. 

2. Task Summarization

Task summarization in P&C insurance involves summarizing claims, policy updates, customer interactions, and large, complex documents. Task summaries act as an easily accessible source of information for agents and customers.

Before AI:

Before the integration of AI, task summarization was a manual process, with agents reading and summarizing documents by hand. The old process often led to inconsistencies, human errors, and delays in retrieving necessary information. But that’s not all as agents used to spend a significant amount of time processing data which eventually slowed down their decision-making.

After AI:

AI-driven Natural Language Processing (NLP) tools now automate the summarization of large volumes of text. The tools can extract key points and present them in real time. AI-powered chatbots and virtual assistants also offer quick, on-demand summaries of complex documents. 

Benefits for the Company:

  • Reduced workload for agents so that they can focus on higher-value tasks.
  • Faster decision-making process with accurate and consistent information.
  • Improved productivity and efficiency.

Benefits for End User:

  • Faster resolution of queries and claims with concise and accurate summaries.
  • Increased transparency and understanding of complex documents.
  • More personalized and efficient service interactions.

Metrics Affected:

  • Task completion time reduced by 40%+
  • A 95% reduction in time for creating summarization reports 
  • A 10% reduction in claims errors

3. Sales

The sales process in P&C insurance includes prospecting, lead qualification, personalized sales pitches, and closing deals. Effective sales strategies depend on timely insights and a deep understanding of customer needs. AI can help sales teams get both at their fingertips. 

Before AI:

Before AI, sales agents relied on manual prospecting, often based on limited data. Sales executives used generic sales pitches which didn’t serve individual customer preferences. Naturally, it meant longer sales cycles and lower conversion rates.

After AI:

AI changed insurance sales by providing real-time lead scoring and segmentation based on customer behavior and preferences. AI tools generate personalized sales pitches, and predictive analytics forecast sales outcomes.  The tools help agents to focus their efforts on high-potential leads. 

Benefits for Company:

  • Higher conversion rates with targeted and personalized sales strategies.
  • Shortened sales cycles, leading to quicker revenue generation.
  • Improved scalability of sales efforts with AI-driven automation.

Benefits for End User:

  • More relevant and personalized product offerings.
  • Faster response times and smoother purchasing experience.
  • Increased satisfaction due to receiving offers that match their needs.

Metrics Affected:

  • Sales conversion rate increased by more than 20%.
  • Sales cycle length reduced by over 30%. 
  • Increase revenues by as much as 20%.
  • Improved Customer Lifetime Value (CLTV)

4. Customer Support

Customer support in the P&C insurance industry involves managing inquiries, resolving claims, and providing policy information. The support desk often requires quick responses and accurate solutions to cater to customers. Quality customer support is a must to build a loyal customer base. 

Before AI:

Without AI, customer support faced challenges such as long response times due to high inquiry volumes. The inconsistent service quality based on agent experience meant that customer satisfaction was a mixed bag. It also meant high operational costs with higher employee expenses.

Source: Accenture Report

After AI:

Powerful AI support agents like Alltius can handle routine tasks 24/7 as they provide instant support to customers. AI tools assist human agents by suggesting answers and analyzing sentiment, which helps prioritize inquiries and provide the right resolutions.

Case Study of a Leading Asian Bank

A major Asian bank reached out to Alltius to improve its product discovery process. Their goal was to develop an AI assistant capable of delivering quick, clear answers to customer questions like, “What’s the best credit card for someone with a $10,000 monthly income who spends on dining and travel?” 

Alltius responded by building a product discovery assistant that processed over 3,000 pages of product collateral in just minutes. As a result, the bank introduced a chatbot, via its web widget, which reduced product information search time from 15 minutes to 1 minute.

Read the full case study here.

Benefits for Company:

  • Lower operational costs with automation of routine support tasks.
  • Consistent and high-quality support across all customer interactions.
  • Improved ability to handle large volumes of inquiries without scaling costs.

Benefits for End User:

  • Faster resolution times and around-the-clock availability.
  • More accurate and consistent information.
  • Higher satisfaction due to personalized and empathetic support.

Metrics Affected:

  • First response time reduced by more than 50%.
  • Resolution time reduced by over 40%.
  • Customer satisfaction score (CSAT) improved significantly. 
  • Customer experience improved by 95%.
  • AI agents answered 96% of the questions. 

5. Training New Recruits

Training new employees in P&C insurance means educating them on company policies, procedures, product knowledge, and customer service skills. The process is important to train new hires so that they are fully prepared to engage with clients and handle operational tasks. AI is of great help here. 

Before AI:

Before AI, training programs were often classroom-based or followed a one-size-fits-all online format with a lack of personalization. The training model led to inconsistent outcomes, as recruits learned at different paces and faced challenges in handling customer queries when experienced trainers were unavailable.

After AI:

AI-based adaptive learning platforms understand the learning pace of each individual and now provide training content to each recruit’s learning pace. Virtual simulations powered by AI provide real-life scenarios for recruits to practice. Last but not least, AI analytics continuously assess their performance along with providing regular feedback. 

Benefits for Company:

  • Faster onboarding of new recruits with training lessons based on one’s learning pace.
  • Consistent and standardized training across all locations.
  • Reduced training costs and time required to bring new hires to full productivity.

Benefits for End User (New Recruits):

  • Engaging, interactive, and personalized learning experience.
  • Faster understanding of essential skills and knowledge for higher confidence and job satisfaction.
  • Continuous support and feedback for improved performance.

Metrics Affected:

  • Time to productivity reduced by over 50% for faster onboarding and contribution.
  • Training completion rate increased as more employees finished their training.
  • Employee retention rate improved with recruits feeling more confident and supported.
  • Training costs reduced by 30%+ due to more efficient training methods.

6. Claims Processing

Claims processing in P&C insurance has primarily three steps: receiving, reviewing, and settling claims. The process also includes fraud detection and communication with claimants. The latter directly impacts customer satisfaction and the company’s operational efficiency. 

Before AI:

Traditionally, claims processing was manual, with humans collecting and verifying each and every detail. The process was indeed slow and led to slow processing times. Plus, human errors and inconsistent fraud detection were quite common. The approach delayed settlements and also increased the risk of overlooking potential fraud.

After AI:

The whole process is now much more efficient with AI-based tools now automating the claims process. At the same time, OCR and machine learning models are quickly assessing claim documents for detecting fraud. Last but not least, AI chatbots also handle initial inquiries, status updates, and routine communication with claimants.

Benefits for Company:

  • Significantly reduced claims processing time for quicker settlements.
  • Lower risk of fraud with advanced AI-driven fraud detection systems.
  • Reduced operational costs by automating repetitive tasks and minimizing human intervention.

Benefits for End User (Policyholders):

  • Faster claim settlements leading to better customer satisfaction levels.
  • Transparent and clear communication throughout the claims process.
  • Reduced frustration due to fewer delays and errors in claim handling.

Metrics Affected:

  • Faster resolutions with claims processing time reduced by 60%+.
  • Risk management with fraud detection accuracy improved by 30%+.
  • Improved customer experience with customer satisfaction score (CSAT) increased.
  • A 73% increase in claims process efficiency.

Alltius AI’s Assurance IQ is an AI-powered platform that brings the best of AI technology to the insurance industry. The platform helps insurers optimize processes, particularly those in the Property and Casualty (P&C) insurance segment.

Alltius automates critical processes such as onboarding, claims processing, task summarization, sales, and customer support. Through advanced technologies like Natural Language Processing (NLP), Optical Character Recognition (OCR), and machine learning, the platform helps businesses reduce operational costs, increase efficiency, and deliver personalized customer experiences as it transforms manual and repetitive tasks into automated workflows.

Curious about how Alltius can transform your insurance business? Sign up here to book a demo to see the platform in action.

Conclusion 

With only 8% of P&C insurers regarded as "trailblazers" in AI adoption, those at the forefront are already reaping the benefits of automation and data-driven insights. Companies that fail to integrate AI into their P&C insurance processes risk business setbacks, involving losing business to competitors. 

According to secondary analysis, by 2030, AI is expected to increase productivity and reduce operational costs in insurance processes by up to 40%

Insurers that resist this transformation will face rising inefficiencies. They are also expected to struggle with longer claims processing times, higher operational expenses, and lower customer satisfaction.

Get the best of AI technology to stay ahead of the curve with Alltius AI. We are here to help you streamline operations, reduce costs, and improve customer satisfaction.

Ready to revolutionize your insurance processes with AI?

Book a demo today and see how Alltius can do wonders for your insurance business!

Transforming Your Agency's Property Lines Quoting Process with AI: Boost Efficiency, Accuracy, and Client Satisfaction
Transforming Insurance: How AI is Revolutionizing Specialty Lines Quoting
Unlocking Efficiency: How AI is Transforming Quote Comparison in Insurance
AI-Powered Policy Checking: Transforming Accuracy & Efficiency in Insurance