The Insurance sector is slated to experience phenomenal changes when it comes to automation. Let’s look at different parts of the insurance ecosystem and how automation will enable faster turnaround times for every stage of policy checking and the entire insurance lifecycle.
The ability of computer systems to improve their performance through exposure to data without having to follow explicitly programmed instructions will enable faster document creation and processing.
The process of discovering meaningful correlations, patterns, and trends by sifting through large amounts of data stored in repositories will improve. This can be done by leveraging statistical and mathematical techniques which will revolutionize end-to-end processes in insurance. This will also enable insurance agencies to deliver services faster.
Natural language processing
The ability of computers to work with text the way humans do is bound to improve. For instance, extracting meaning from text or generating text that is readable, stylistically natural, and grammatically correct. This will empower bots to automate document generation and analysis.
Emulating human reasoning by learning, coming to conclusions and appearing to understand complex content by engaging in natural dialogs with people may sound like science fiction but it is not. We will soon see the impact of intelligent agents that respond to workflows based on sophisticated business rules. They will work on the knowledge extracted from the insurance domain itself. This will facilitate a lot of manual processes for insurance agents and policy checkers.
Automatically and accurately transcribing human speech by interpreting the voice and translating it into text or commands will enable policy checkers and document managers to transcribe complex insurance documents without too much effort.
Applications that you are likely to see in the Insurance domain are:
- Robot agents to manage customer service interactions using natural language processing capabilities.
- Virtual personal assistants to help underwriters identify advanced risk attributes.
- Identification of preference patterns based on customer interactions to create cross-selling/upselling opportunities.
- The use of machine learning to teach systems to automatically handle all exception processing.
- Use of deep machine learning techniques to self-identify and repair process bottlenecks to improve efficiency.
- Employing social media information to identify claim fraud patterns.
At Exdion, we employ cutting-edge AI, ML and NLP to speed up the entire lifecycle of Insurance, end-to-end. Exdion Policy Check is a stellar example of what is possible with the application of these technologies.
Get in touch with us to learn more about Exdion and embrace the feature.