By harnessing the capabilities of AI and ML, ClaimSmart hopes to change the way insurers handle claims, offering substantial cost reductions and enhanced customer experiences.
According to reports, ClaimSmart is engineered to drive down loss costs by tackling prevalent inefficiencies and sources of waste, such as manual redundancies, fraudulent claims, and claims leakage. Its advanced features enable insurers to optimize processes and deliver superior outcomes, ensuring a higher standard of service while containing expenses.
Moreover, ClaimSmart boasts a versatile and integrated digital front-end portal, empowering insurers to provide fully digital customer experiences. This emphasis on self-service not only reduces friction but also enhances the overall consumer journey, making it more user-friendly and adaptable across the entire claims life cycle.
Driving the industry forwards
The introduction of ClaimSmart marks a notable progression for EIS and underscores its growing proficiency in data science. It serves as a foundational step towards the development of a comprehensive suite of Data Science (DS) solutions, aimed at optimising automation and efficiency throughout the insurance sector. The incorporation of DS methodologies is crucial for crafting algorithms capable of analysing patterns, making predictions, and ultimately fostering more intelligent and streamlined operations within the insurance industry.
“We’re proud to be one of ClaimSmart’s first users,” said Atsushi Wada, Claim Dept. Team Manager, Tokio Marine. “It’s helping to revolutionise our claims management process for both customers and employees. Inefficient and costly systems and processes have been transformed, delivering faster resolutions, increased customer satisfaction, and large-scale operational savings.”
The launch of ClaimSmart represents a significant leap forward for EIS and an advancement in its expertise in data science. It lays the groundwork for a comprehensive Data Science (DS) suite of solutions, enhancing automation and efficiency across the insurance sector. The integration of DS methodologies is pivotal in developing algorithms that can analyse patterns, make predictions, and ultimately drive smarter, more efficient operations in the insurance industry.
Alec Miloslavsky, EIS CEO, said: “Claims platforms are in desperate need of transformation. They’re bogged down by manual tasks and ineffective processes that not only drive-up costs but also degrade customer experiences. In response, we’ve developed ClaimSmart to address these challenges head-on.”
“Engineered to streamline operational tasks, ClaimSmart significantly alleviates tedious administration and enhances the digital front-end experience for customers. It ensures rapid processing of legitimate claims while minimising claim leakage and the risk of fraud. This is a crucial expansion to our offerings, integrating ML and AI to enhance our platform’s capabilities and deliver a comprehensive end-to-end claim management solution.”
Innovation compatibility
ClaimSmart is compatible with various core systems, ensuring smooth integration with a wide range of policy and claims management platforms. When used alongside ClaimCore, EIS’s established claims system, ClaimSmart provides a comprehensive solution that expedites claim processing and provides tailored, seamless experiences for both insurers and policyholders. This collaboration plays a key role in reshaping the landscape of insurance claims operations.
He continued: “With ClaimSmart, we’re embracing the transformative potential of data science to revolutionise insurance claims management. Our commitment to data fluidity, intelligence, and extensibility is crucial as we assist insurers in building their future ecosystems. This vision has been recognised by industry experts, such as Celent, who have named our Claims Platform a 2024 Tech Standout.
“As we continue to evolve our platform and collaborate with various insurtechs, our goal remains to deliver the best possible claims management outcomes, setting new standards in the industry,” Miloslavsky added.
