In the third and last part of the series on how AI can be a game-changer for the health insurance industry, we will explore various technologies that assure faster, accurate, and smoother solutions in carrying out a range of tedious and complex tasks.
The conventional approach to claims management based on an inflexible rulebook has been made obsolete by intelligent algorithms that learn from historical cases and constantly evolve. Such a system can systematically identify and correct errors while avoiding unnecessary or ineffective interventions.
In large companies, a quarter of senior executives plan to fundamentally reimagine their businesses with AI by the end of 2021 (compared to 14% in 2017), and 54% will use it to transform processes (up from 41%), according to the latest Genpact AI 360 degrees report.
Investments in chatbots are expected to quadruple by the end of 2021, says the latest Opus Research report. It is being seen as the outcome of a cut-throat competition. Businesses across sectors, including health plan, are in search of a smoother and effective communication strategy, and they have found answers in chatbots. Be it answering queries, keeping communication channels open at odd hours, customer relationships or clearing doubts, chatbots can do it all 24×7 without any break.
The conventional approach to claims management based on an inflexible rulebook has been made obsolete by intelligent algorithms that learn from historical cases and continuously evolve. Such a system can systematically identify and correct errors while avoiding unnecessary or ineffective interventions, says a Mckinsey report. Gaining an understanding of profile is related to a huge amount of data processing, and claims management is no different. Here, extracting relevant information from volumes of data is the key. When done manually, it is a low-skill tedious task that cannot be claimed to be error-free. Automating this process with AI-powered tech is here to bring a revolution in how claim management is done. It saves time, effort, and costs. AI technologies are poised to drastically bring down document-related expenses for health insurance companies.
Each health plan company processes customer data in bulk on a daily basis. Whether to turn it into a gold mine or junk depends on how the company processes the numbers. Technologies like Deep Learning can dig their teeth into electronic data and churn out the relevant ones in the most useful manner. The most important being building a model with help of Deep Learning that can evaluate customer risk profiles with higher accuracy. The accuracy will help come up with optimal insurance prices, which is a win-win situation both for the payer and the customer. This, in other words, means cost reduction and more deeper understanding of customer profiles. With an increasing amount of customer data, insurance companies can build machine learning models to evaluate customer risk profiles more accurately and provide optimal insurance prices. This will reduce costs significantly and provide a better understanding of customer profiles.
The growing focus on telehealth and the drive toward care empathy initiatives find their conflux in affective computing. This involves analyzing facial expressions, tone of voice, and other non-verbal cues to better understand the patient’s physical and mental health. By
harvesting this data, enterprises can optimize diagnosis and treatment, helping speed, streamline, and cheapen the care process, thereby improving the quality of care provided.
Use cases of Affecting Computing in health insurance space:
-Smart call routing: The simple and effective leads are customer calls. They have a high conversion rate. No wonder, it is important that customers’ calls go to the right person, locations and departments. Smart call routing is the answer. It ensures that all customer calls get diverted to the persons most efficient to provide the information or address the grievance.
-Fraud detection: Insurance companies can benefit from voice analytics to understand if a customer is lying while submitting a claim.
Use IoT and smart devices
From monitoring customers to getting access to medical device data with the help of connected devices like smartphones and wearables, AI technology is here to change the way the healthcare industry operates. What is gradually leading to is personalized policies based on proactive prevention. This helps in dropping outdated methods of meeting underwriting requirements with fact-based risk assessment, enhanced profiling, and real-time actionable analytics for predictive decisions.
The last year has been full of challenges. But it also presented opportunities for new innovation, technologies, and evolution for payers as an organization. Digitalization got a much-needed push with AI and other technologies putting the transformation on the fast-track.