Recent accelerations in digitalization and innovation have provided new opportunities while also making it difficult for insurers to keep up. Customers today have very different expectations than they did in the past. Find out from the market updates below on steps you can take to better understand your customers and deliver the kind of experience they are looking for.
🔙 A Quick Look-Back
Millennials have become the largest demographic in many countries and are entering their prime spending years. But given how they are fundamentally different from older generations, insurers must understand how to reach this tech-savvy, socially active generation with tailored experiences catered to their individual needs, especially at a time when Big Techs like Amazon are venturing into this space. Forbes talked with a customer experience expert to discover more about this topic.
Another recent development that is driving the industry to change its approach to customer experience is open insurance. Similar to open banking, open insurance is helping insurers challenge the norms of what a customer experience should be like. And EY pointed out the key steps insurers must take to seize opportunities in the open insurance ecosystem.
With insurers having access to highly sensitive customer data, it goes without saying that data and privacy are important topics of discussion to offer better and more personalized services. So, how can insurers capitalize on increased data availability without compromising on trust? Geneva Association explored.
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AI in Insurance : A Deep Dive
The insurance industry is a wealth of data waiting to be tapped into. Effectively harnessing this data using AI and related technologies can give insurers actionable insights into customer behaviors and help them identify process gaps.
In this article, we discuss some of the core insurance processes where AI can be of value:
- Document processing: Being a paper-heavy industry, most insurers manually handle the complex, unstructured data flowing in from multiple input channels. This is where AI comes in to digitize and structure the process for reduced turnaround time (TAT), faster processing, and minimal manual effort.
- Underwriting: Underwriters deal with massive volumes of information and data from fragmented sources. Deploying an automated underwriting engine together with a predictive model for risk assessment enables insurers to adopt an ongoing risk management approach to adapt to evolving risk conditions.
- Claims processing: A poor claims experience can affect the profitability of insurers. But using AI, ML, predictive analytics, etc., can streamline the claims process with accurate fraud detection, quicker TAT, and minimized inefficiencies for a customer-centric claims journey.
- Pricing and Product Development: The increase in competition, regulations and well-informed consumers are leading to pricing and product development challenges. A data-driven approach to quantifying risks via AI can offer insurers the flexibility to personalize their offerings and quickly respond to market changes.
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