أقسام الوصول السريع ( مربع البحث )

Read this

Industrializing data and analytics among Asian insurers

 In recent years, Asian insurers have recognized the value of data and analytics in driving growth and improving operational efficiency. Many have invested in analytics teams or formed partnerships with insurtech companies to pilot new initiatives. Popular use cases have focused on increasing new business, improving fraud detection, and enhancing the processing rate of life insurance policies.



The COVID-19 pandemic has further amplified insurers' interest in data and analytics. Insurers understand that customers now expect personalized and convenient services, including from their insurance providers. This has led insurers to prioritize the use of data and analytics to address immediate challenges posed by the pandemic and to capture new opportunities in a more connected and digitized world.


During the pandemic, insurers have used analytics to personalize their response to customers' immediate needs. Instead of implementing broad actions such as offering refunds to all customers, insurers can use analytics to prioritize offers for customers most in need and proactively reach out to them. This targeted approach can be more cost-effective and help strengthen long-term relationships. Insurers with established analytics capabilities can also use customer-reaction data to refine their marketing strategies for new products and launch more targeted digital marketing campaigns.


In countries like China and Thailand, the pandemic has created a surge in demand for health and mortality insurance coverage. Insurers with analytics capabilities can leverage this demand by launching new products and using data to optimize their marketing and customer outreach efforts. For example, Ping An Good Doctor, a healthcare ecosystem platform in China, experienced a significant increase in user visits and consultations during the pandemic and subsequently launched a global telehealth platform.


Insurers have observed that the pandemic has led to changes in customer behaviors at a faster pace, impacting the accuracy of their analytical models. To address this, insurers have focused on increasing their agility and reducing the time required to launch new analytical models. This agility allows them to adapt quickly to evolving customer needs and behaviors.


Looking beyond the immediate needs during and after the pandemic, insurers must plan for the increasing demand for insurance products. The digitization of the insurance industry has accelerated, and insurers are leveraging data and analytics to provide personalized and convenient experiences to customers. This includes adopting omnichannel engagement, streamlining underwriting processes, and offering timely human assistance through various channels.


To fully capitalize on data and analytics capabilities, insurers should transition from single use cases to an industrialized approach. This involves scaling technology capabilities, establishing governance mechanisms for impact assessment and prioritization, adopting a business-led agile delivery approach, fostering organization-wide buy-in, and building technical capabilities such as live model performance monitoring, scalable data pipelines, and flexible architecture.


Furthermore, insurers should form partnerships and ecosystems with entities such as ecommerce platforms, banks, and utilities to expand their reach and access new data sources. These partnerships enable insurers to develop new analytical models, gain insights into customer behavior, and identify prospects based on risk, value, and customer needs.


In summary, Asian insurers are increasingly relying on data and analytics to drive growth and improve customer experiences. The COVID-19 pandemic has accelerated this trend, prompting insurers to address immediate challenges and seize new opportunities. By leveraging data and analytics effectively, insurers can personalize their offerings, enhance convenience, and position themselves for success in a rapidly changing insurance landscape.

Comments



Font Size
+
16
-
lines height
+
2
-