Plat.AI for the Insurance Industry

How AI Is Transforming Insurance

Insurance companies embrace artificial intelligence (AI) and use more data science across different applications to improve profitability, become more efficient, and deliver an enhanced customer experience while decreasing fraud. Building customer relationships and managing risks are vital for a profitable business. Therefore, insurance companies making extensive use of artificial intelligence reap the benefits and transform the industry.

Transform Insurance Industry with Plat.AI

Plat.AI helps revolutionize the future of AI in insurance. We provide insurance companies the power to optimize their market selection, underwriting, pricing policy, and claims management operations.

With Plat.AI, insurers can deploy analytics and machine learning to help you reduce loss ratios and achieve higher conversion rates.

Ready to Learn More?

We offer one-on-one support to marketing analytics teams. Our data scientists are ready to build, deploy, and maintain a real-time decision-making engine with your data.

Schedule a Demo

Key Trends for the Insurance Services Industry

Here are the top trends that are shaping AI in the insurance industry:

Personalized Products:

Personalized and usage-based insurance products will become more prevalent than the available one-size-fits-all models. Flexible coverage options, micro insurance, peer-to-peer insurance, and insights-driven offerings will become viable options too.

AI and RPA-Based Customer Service:

Artificial intelligence and robotic process automation will automate claim management and policy services for faster and more efficient claims reporting. Our AI technology insurance platform will improve business outcomes in customer experience, leading to higher profitability and market competitiveness.

Advanced Analytics and Pro-active Decision Making:

Advanced analytics will build granular individual risk profiles, adjust policy prices, identify new growth opportunities, offer model behaviors, and identify exceptions. Plat.AI aims to achieve these goals as well.

Insurtech Partnerships:

With an increased demand for innovative products and services, mainstream insurance companies are partnering with InsurTech companies to reimagine business models, boost profitability, and improve customer experience.

Blockchain Technology for Secure Data Management:

Blockchain can facilitate real-time data transfer and management across multiple interfaces. Plat.AI’s technology offers reduced operational costs and detects fraudulent activities.

How Plat.ai Addresses Key Data Challenges in Insurance

Fraud detection

Our AI-driven insurance tool detects fraudulent activity to avoid investigating unnecessary claims. A higher number of frauds results in delayed payouts and costly investigations. Therefore, we introduce models that target this issue.

Data quality

Our AI tool for insurance can extract, clean, and monitor data to ensure accurate results and simplify future steps. By leveraging our intelligent insurance platform, insurers can streamline their operations effectively.

Latency

Risk assessment and claim prediction are time-sensitive. Our predictive analytics insurance tool can identify significant variables and offer real-time predictions.

Why Plat.AI for Insurance Services

Plat.AI supports insurers in optimizing their market selection, underwriting, pricing policy, and claims management operations. Moreover, Plat.AI’s advanced insurance AI platform can clear internal and external communication and manage the business’s lifecycle.

Easy Platform Integration

Our automated insurance platform enables straight-through deployment of analytical models, eliminating the need for reprogramming. Our insurance automation AI tool ensures seamless integration and operation.

Clear Communication

Customers, executives, and regulators can use the Plat.AI smart insurance AI tool to understand and explain predictions. Our insurance AI platform also provides clear insights into decision-making processes.

Managing The Lifecycle

In addition to letting users know when their results diverge from modeled predictions, Plat.AI automatically identifies what might be causing these divergences.

Machine Learning Use Cases in Insurance

Claims Processing:

Dealing with thousands of claims and customer queries can be time-consuming. Luckily, machine learning insurance tools make the process more efficient and effective, saving employees time to focus on more complex claims and direct customer contact.
Claims Fraud Detection:

ML can accurately detect fraud and empower insurance companies to enhance their due diligence process.
Automated Underwriting:

Before the rise of technology, insurance underwriting was heavily employee dependent. Today, intelligent process automation simplifies the underwriting experience by providing ML algorithms that collect and make sense of massive amounts of data.
Automated Submission Intake:

Automation complemented by artificial intelligence and natural language processing can extract data from structured and unstructured sources to help underwriters collaborate and reduce risk decisions.
Pricing and Risk Management:

Price optimization uses data analysis techniques to understand customers’ reactions to different pricing strategies and determine the best prices aligned with the company’s goals. Similarly, risk assessment automation enhances operating efficiency with the help of ML and cognitive technologies. As a result, the automated process significantly reduces time, and insurers can deliver a better customer experience and reduce churn.
Customer Lifetime Value Prediction:

Insurance companies can predict customer lifetime value through data-driven insurance AI platforms that use a customer’s purchase history to recommend other products. Based on the customer’s action, the algorithm discovers hidden patterns. This helps insurers understand the customer’s preferences and find the balance between customer retention and acquisition.
Customer Segmentation:

ML tools analyze customer data to find insights and patterns. This helps enhance personalization and optimize product design, promotion, marketing, and customer satisfaction.

Related Resources and Blogs

5 Important Topics in Machine Learning You Need to Know A Step-By-Step Guide on How to Build an AI Predictive Sales Analytics: Elevate Your Strategy

Plat.AI for Insurance