Mavera, a Verisk business的动态

For a long time, we were met with hesitation on how AI could support a claims process where the human touch played such an important role. Today, that hesitation is replaced by knowledge and curiosity on how AI can enable claims teams to create even better and more human customer interaction than before. The change is definitely coming!

Chatbots have been utilized in the insurance industry for years at this point, but recent developments in AI may change how they're used. Before AI developments, chatbot abilities were relatively limited. However, that's set to change. In fact, "The global chatbot market is expected to reach $1.25B USD by 2025." At Crawford & Co., we believe there are 5 major benefits that AI-powered chatbots can have on the future of the insurance industry: ?Customer acquisition: Chatbots can now offer prospective customers detailed information and advice about available insurance policies. ? Underwriting: Underwriters can leverage AI-powered chatbots’ unique capabilities to help them make better decisions and more accurately assess risk. ?Customer engagement: Chatbots can provide 24/7 customer support and answer specific policyholder questions about coverage, claim status, or new policy information. ?Claims management: Adjusters can leverage chatbots to help collect information from customers or notify them of their claim’s status. ?Fraud detection and prevention: Chatbots help add an additional layer of security so insurers can strengthen their fraud protections without compromising the customer experience. #ClaimsProcess #AIChatbots #InsuranceIndustry

Five Sigma, a prominent AI claims management software company, has introduced the insurance industry’s first AI-powered Insurance Adjustment Agent, Clive?. This innovation is set to transform claims processing by using artificial intelligence and automation to boost efficiency, accuracy, and reduce costs, according to InsurTech Insights. Clive? provides extensive automation capabilities throughout the entire claims lifecycle, from initial loss notification to settlement. The AI adjuster performs tasks traditionally handled by human adjusters, such as document management, exposure setting, personalized communications with policyholders, and real-time decision-making. Clive? ensures smooth interactions with policyholders, keeping them updated throughout the claims process. Established in 2017, Five Sigma has led the way in integrating AI and automation into its claims management platform, improving customer satisfaction for carriers, MGAs, TPAs, and self-insured companies. The launch of Clive? represents a major advancement, offering AI-powered claims handling not only for Five Sigma’s own Claims Management Platform but also for any existing Claims Management System (CMS), including Guidewire, Duck Creek, Sapiens, and Majesco.

Frustrated Policyholders & Lagging Renewals? AI Assistants Can Help! Insurance companies face a double-edged sword: policyholders crave a frictionless, personalized experience, yet traditional methods often fall short. Frustrated customers struggle to navigate complex websites, wait on hold for answers, and face lengthy claim processing times. This leads to dissatisfaction and ultimately, policyholder churn. Here's how AI assistants can revolutionize your insurance website and address these critical issues: 24/7 Self-Service: No more waiting on hold! AI assistants can answer basic policy questions (deductibles, coverage details) and guide users through common tasks (claim submissions, payment processing). This empowers customers to get the information they need instantly, reducing call center volume by up to 30%. Personalized Risk Assessments & Quotes: Tired of one-size-fits-all quotes? AI can analyze data to offer tailored insurance plans based on a customer's specific needs and risk profile. By focusing on the right audience and providing relevant quotes, you can increase conversion rates by 20%. Faster Claims Processing: AI assistants can walk policyholders through the claim process step-by-step, collecting information efficiently and even scheduling appointments with adjusters. This reduces claim processing times by 15%, minimizes frustration, and frees up adjusters for complex cases. Proactive Policy Management: Let's boost engagement! AI can send personalized reminders for premium payments, policy renewals, and safety tips relevant to the customer's coverage. This increases policyholder retention by 10% and strengthens customer relationships. The result? Satisfied policyholders who are more likely to renew, recommend your services, and view your company as a trusted partner. This translates to increased customer lifetime value and overall business growth. #InsuranceTech #CustomerExperience #AI #WebsiteDesign #Chatbots #Personalization #MachineLearning Let's discuss how AI assistants can transform your insurance website into a customer service powerhouse and unlock significant business value! Visit us www.tact.asia or write to us [email protected]

'In case of AI liability, risk assessment is a new frontier to be explored. In such case, insurance is not a static concept: it could be very difficult appraising the aggravation or reduction of the risks, since risks can change rapidly.' https://lnkd.in/dFTk9hUP

Kanverse's end to end insurance Submission and claims intake automation ingests, extracts, classifies, validates and files data from documents and images https://hubs.la/Q02wmGgf0 #AI #automation #Insurance #ACORD #FORMS #claims #underwriter

Underwriting Automation and Pricing Optimization Underwriting automation and pricing optimization are transformative approaches within the insurance and financial services sectors. They leverage technology to streamline decision-making and improve the accuracy and competitiveness of pricing strategies. 1. Underwriting Automation Overview: Underwriting is traditionally a labor-intensive process, involving risk assessment to determine a policyholder’s eligibility and premium level. Automating this process uses artificial intelligence (AI), machine learning (ML), and data analytics to streamline and speed up decision-making. Benefits: Improved Efficiency: Automated underwriting can assess applications faster, reducing turnaround times and lowering administrative costs. Enhanced Risk Assessment: AI and ML algorithms can analyze vast amounts of data (such as historical claims, financial records, and social factors) to provide a more comprehensive risk profile. Consistency: Automation minimizes human bias and error, leading to more consistent underwriting decisions. Applications: Predictive Models: ML models can predict the likelihood of claims or losses, helping underwriters adjust policies accordingly. Rules-Based Systems: These systems can automatically approve, decline, or flag applications based on predefined risk thresholds. 2. Pricing Optimization Overview: Pricing optimization aims to determine the best pricing strategy for insurance policies, balancing profitability and competitiveness. It involves analyzing market data, customer behavior, and risk profiles to set prices that maximize revenue and market share. Benefits: Data-Driven Decisions: Pricing models can incorporate real-time data to adjust prices dynamically based on market conditions and competition. Customer Segmentation: Algorithms can segment customers based on behavior, needs, and risk, allowing for personalized pricing. Profit Maximization: Pricing optimization helps identify the most profitable price points, reducing the risk of underpricing or overpricing. Applications: Elasticity Modeling: Understanding how sensitive customers are to price changes allows insurers to set optimal prices that retain customers without sacrificing margin. Competitive Analysis: Automated tools can track competitors' pricing and adjust policies accordingly. Lifetime Value Prediction: Models can predict the expected lifetime value of policyholders, helping determine long-term profitable pricing strategies. Key Technologies Enabling Automation and Optimization AI & ML Algorithms: Enable pattern recognition, predictive analytics, and personalization. Big Data Analytics: Allows integration of diverse datasets, such as social data, economic indicators, and customer profiles. RPA (Robotic Process Automation): Automates repetitive tasks in underwriting and pricing, reducing human intervention. Telematics and IoT: Real-time data ?????? ????? ??? ??????? https://t.me/sedeek90/1199

???????????? ????????????????????????: ?????? ???????????? ?????? ???? ?????? ???????????????????????? ?????????????????? Bionic underwriting, a fusion of human expertise and artificial intelligence (AI) is changing how insurance works. Combining human skills with AI's speed and data analysis is making processes faster, risk assessments more accurate and above all the customers happier. Although there are challenges like data quality and possible biases, this method creates a more efficient and fair insurance system. Here's how bionic underwriting is reshaping the insurance world: 1. ???????????????? ???? ???????????????????????? Bionic underwriting makes things faster by automating routine tasks like data entry and document verification. AI can handle these jobs, allowing human underwriters to focus on more complicated cases. This speeds up policy processing, helping customers get their insurance faster and with less hassle. 2. ???????????? ???????? ???????????????????? AI is great at analyzing huge amounts of data. It can look at past claims, customer profiles, and even outside factors like weather to predict risks more accurately. With these insights, insurers can offer personalized premiums based on an individual’s unique risk profile, creating fairer pricing for customers. 3. ?????????????????? ???????????????? ???????????????????? AI-powered tools speed up claims processing, meaning customers don’t have to wait long for their claims to be approved. In addition, bionic underwriting can recommend insurance products that match a customer’s specific needs, making the experience more personalized and convenient. 4. ?????????????????????????? ?????????????? ???????????? ?????? ???? Bionic underwriting works best when humans and AI work together. AI can analyze data and automate tasks, but human underwriters add context, ethical judgment, and expertise. By using both AI and human insight, insurers can make smarter decisions while avoiding potential pitfalls. ???????????????????? ???????????????????? To truly unlock the power of bionic underwriting, a few key challenges need to be addressed: Data Quality: AI systems rely on accurate and complete data. Insurers must ensure their data is reliable to avoid biased or incorrect outcomes. Bias: AI models can reflect biases in the data they are trained on. Insurers must regularly monitor and adjust algorithms to ensure fair decisions. Transparency: Insurers need to be clear about how AI makes decisions to maintain trust with customers and regulators. ?????? ???????????? ???? ?????????????????? Bionic underwriting isn’t just a passing trend. It’s helping insurers improve efficiency, enhance customer satisfaction, and manage risks better. While AI offers many advantages, human judgment remains indispensable, and this blend of man and machine will help the insurance industry move towards a smarter, fairer future. #BionicUnderwriting #AIinInsurance #HumanAICollaboration #Innovation #CX #InsurTech

?????? ???? ???????????? ?????? ???????????????????????? ???????????????????????? ?????? ?????????????????? ?????????????????? AI agents are reshaping the insurance industry by automating underwriting, lead management, and customer engagement processes. These agents take over time-consuming tasks, enabling insurers to work more efficiently and focus on high-value opportunities. In today’s competitive market, insurers can no longer afford delays in responding to leads or inefficiencies in underwriting. Manual processes are slow, error-prone, and costly. AI-driven underwriting speeds up risk assessment and enables more accurate pricing decisions, giving insurers an edge. AI agents also ensure 24/7 lead engagement, so no opportunities are missed, even after hours. This increases sales potential while reducing workload. - AI streamlines risk assessments by analyzing vast amounts of data, leading to more accurate pricing and faster decision-making.?? - AI agents automatically engage and qualify leads 24/7, ensuring no prospects slip through the cracks. This allows your team to focus on high-quality leads that are more likely to convert.?? - AI agents re-engage dormant or unconverted leads through personalized conversations, turning cold leads into new opportunities without additional manual effort.?? - AI agents also automate review management, improving your company’s reputation while freeing up internal resources to focus on strategic tasks.? This approach is ideal for insurers seeking to improve efficiency and grow their business without increasing operational costs. Whether you're handling underwriting, lead generation, or customer engagement, AI solutions fit seamlessly into your processes, empowering your team to be more productive. The time to adopt AI is now. As the insurance industry evolves and customers demand faster, more personalized services, those who integrate AI early will have a significant advantage. Companies that embrace these technologies today will stay ahead of the competition and scale their operations more effectively.

Using tactical LLM API calls as part of an origination / underwriting workflow can drastically improve the processing speed for such backoffice-heavy activities. “”” The underwriting process typically involves several key steps: Gathering and verifying information – Underwriters collect and review various data points about the applicant, such as age, health status, occupation, and lifestyle habits for life insurance, or property location, construction type, and safety features for property insurance Risk assessment – Underwriters analyze the potential risk of insuring the applicant using statistical models, actuarial data, and their own expertise Premium determination – Based on the risk assessment, underwriters calculate the appropriate premium for the desired coverage, aiming to strike a balance between competitive pricing and ensuring the insurer’s profitability Policy customization – Underwriters may tailor insurance policies to meet the specific needs of applicants while aligning with the insurer’s risk management strategy Decision-making – After assessing the risk and determining the appropriate premium, underwriters decide whether to accept or reject the application Effective underwriting is crucial for the financial stability and profitability of insurance companies. By accurately assessing risk and setting appropriate premiums, underwriters help insurers maintain a balanced risk portfolio and avoid adverse selection of potential policy holders. “”” #genai #softwareengineering #softwaredesign