“From emerging risks across the P&C industry, disruptions caused by rapidly growing InsurTech companies, and pressure to improve risk management capabilities, deliver exceptional and personalized customer experiences while generating new sources of revenue – insurers face multifaceted challenges.”

In a constantly evolving economy, AI/ML and GenAI continue to reform our social way of thinking and interacting such that insurance carriers are striving to bring forth unique customer experiences and offer personalized products for their customers. Notably, connected and smart digitalization has also greatly influenced insurance distribution worldwide. Implementing advanced technologies and innovative learning models to drive intelligent automation across claims, underwriting, and proactive risk assessment is now the center of an organization’s strategy, among other strategic initiatives. Claims and Underwriting business functions are the primary business units where 50% more automation has been achieved, especially in claims processing – boosting efficiency and accuracy.

Role of advanced technologies in elevating insurance value chain

Amid economic uncertainties, challenges due to rapidly evolving technology, regulatory complexities, and disruptions caused by InsurTech in the recent decade – insurance leaders are tackling heterogeneous challenges today. Increasing pressure to enhance risk management capabilities using intelligent automation, delivering exceptional and personalized customer experiences while generating new sources of revenue, insurers need business model recalibration in response to evolving customer needs and expectations, protecting existing customers while increasing new customer acquisition, and expanding into new market segments. This is where intelligent automation becomes the cornerstone for modern digital transformation initiatives.

Insurers today are adopting cognitive automation or intelligent automation—weaving machine learning (ML), artificial intelligence (AI), natural language processing (NLP), robotic process automation (RPA), APIs, low-code / no-code platforms, automated decision-making (ADM), data aggregation, and the use of specialized integration platforms—as a core element in their technology strategic roadmap. Moreover, they are internally establishing AI councils with the goal of providing enterprise-wide guidelines and a well-defined framework. This structure will ensure the safeguarding of all data and assets, adherence to global regulatory and legal requirements, and stringent cyber security compliance. A testament to the growing financial commitment towards intelligent automation is surging investments – with 90% of insurers focusing on underwriting, claims, sales, marketing, and customer service.

Let us have a look at how cognitive automation is impacting core insurance areas:

Generative AI (GenAI): The insurance sector’s maturity in GenAI is evident from cutting-edge solutions that can identify anomalies and patterns from organizational data to generate new data. Carriers are increasingly interested in implementing large language model (LLM)-based solutions across insurance business functions of sales, customer service, underwriting, and claims to incorporate straight-through processing (STP) and improve key business metrics such as operational efficiency and accuracy. For instance, a large insurance company has observed up to 30% productivity by deploying a GenAI-based claims processing system.

Data aggregation: Insurers often gather data from disparate sources such as customer interactions, smart wearables, connected cars, smart homes, IoT, and more. Ingeniously engineered integration platforms integrate and unify the data for further processing and recommend tailored products best suited for customer needs. Additionally, insights derived from such data, when integrated with underwriting decision-making systems, can be utilized to make effective underwriting decisions and flag alerts of possible fraud, therefore requiring human (underwriter) review. The utilization of both relevant external data and individual entity and personal insured data allows carriers to harness AI technology to decline high-risk quotes and instead offer tailored policy constructs to better meet customer needs.

Machine learning (ML): ML models can correlate and gauge risks by analyzing historical underwriting data of exposures, perils and sub-perils, and other variables in identifying specific patterns. AI combined with ML can parse through various data in assessing risk factors comprehensively to adjust policy terms in real-time driven by market trends and incorporation of customer behavior data gathered during customer interactions. This is a critical step in improving pricing accuracy and risk management. For instance, a cloud-ready digital first notice of loss (FNOL) solution can help insurers receive claims requests in any format – digital copies, PNG, EML, voice messages, IVR, and chatbots. Users can prefill and create an FNOL even with minimal information. With telematics data, the solution can also provide added features ranging from roadside assistance to towing support and beyond, elevating the realm of claims-related services. Furthermore, AI/ML can assist insurers in declining high-risk quotes and instead offer tailored policies to better meet customer needs.

Robotic process automation (RPA): Insurers can embed RPA into their systems to generate a comprehensive claims summary and expedite claims processing. When integrated with AI/ML/GenAI, automated information extraction can lead to more accurate documentation of claims forms. Claims departments can greatly benefit from the reduced turnaround time and minimized errors. Moreover, data collated by intelligent chatbots from customer interaction interfaces can also be utilized to expedite chatbot training and enhance contextual understanding of customer’s issues and needs.

Through intelligent automation, carriers can elevate insurance operations and outcomes by streamlining processes, reducing manual tasks, and eliminating human errors. This, in turn, will lead to minimal business disruptions, bringing down the overall cost of operations.

HTC in action

The next steps in intelligent automation

Through its vast industry expertise, research, and discussions with the leaders of global organizations – HTC, as a technology partner, believes that intelligent automation will be a key driver for elevating the insurance ecosystem. Our proven implementation framework has helped many insurance customers to successfully implement intelligent automation and enhance operational efficiency. In addition to fueling exceptional customer service experiences, insurers can also allocate their resources and efforts towards high-value tasks, scaling up technologies, and driving long-term growth.