Automated digital claims - Where accuracy is guaranteed

At a time when technology innovations are giving a total makeover to the insurance industry, the digital claims automation processes have seen slower growth than other operational areas. This, despite the fact that it is the one that customers always perceive as a differentiator. In fact, a survey by EY suggests that a massive 87% of all policyholders consider it a core reason for changing their insurer. Having said so, the industry has been spending considerable time and money on the InsurTech module which empowers adjusters and agents to automate manual tasks, sift through massive data sets and provide a satisfying customer experience.

Faster claims processing with limited human intervention coupled with an ability to evaluate and make data-driven decisions is what could customers with an insurer. Existing technology innovations use workflows, rule-driven automation, interfaces and data enrichment to automate processes and provide the transparency that customers are always looking for in claim settlements. From an insurer's point of view, these innovations also assist in fraud detection besides assisting the third-party administrators with auto-adjudication options using artificial intelligence. 

In fact, artificial intelligence also plays a part in enhancing service quality and delivery of communication to the customer. Since more and more data is getting added to the insurance automation, the machine learning modules help the system better understand the various claim scenarios. They not only guard against customers being overcharged, but also provide them with timely updates during the entire claim process. These data points are shared via automated calls, text messages, Whatsapp and through customized mobile applications built by the insurers. 

The automation of the entire digital claims has been an ongoing process and is slowly getting extended to new claim types. The automation process faithfully follows decades-old templates that track a claim from the moment a policyholder alerts the insurer to claims investigations, policy checks, payment calculations and actual payout. What's changed is that the third-party administrators, who relied on manual intervention to process claims, have upgraded. They are now using artificial intelligence and machine learning created as homegrown solutions to automate the process based on the industry that it maps to. 

For example, in the healthcare business, InsurTech has based the transformation protocol around the digitization of tariff, historical medical data, hospitalization bills and discharge summaries. TPAs work out a standard operating cost with their hospital networks that consumers have access to and saves them from surprise expenses. Similarly, claims evaluated and settled at hospitals also are made available, helping the customers determine actual costs. The AI-ML integration with the digital forms ensures that the bills and charges summaries are far more accurate, a factor that helps TPAs automatically arrive at the validity of claims under policy conditions.  

As discussed earlier, the claims process is what makes or breaks a customer relationship and each time there is a dip in the satisfaction index, the insurer costs tend to go up. This is where the richer, data-driven and analytics-enabled customer experience comes into play. Take the case of property and casualty insurers using historical repair data to decrease estimating time for cars or houses or how advanced telematics data could instantly capture details of an automobile accident and actually be used to trigger a first notification of loss. 

The advent of robotic process insurance automation (RPA) marked the first step towards automation where programmed bots acted as digital workers and took over the mundane and repetitive tasks. Process claims were automated using RPA, making it much faster and more efficient. Some of the functions that got automated included copying and entering data across systems, reconciling and verifying claims data, gathering information from emails and automating the workflow with a set of rules. The introduction of AI further enhanced the overall bot capabilities, while cognitive automation helped analyze images, audio and natural language texts wherever they figured in the claims process. 

Having traversed the journey to this point, where does claims automation go from here? At the base level, third-party data could get integrated with existing records that could potentially enhance automated notifications and chat bots. Deployment of drones as adjusters could be another change that we could witness sooner than later as insurers seek to expand automated claims handling to new claim types. The next step could be the use of visualization and modeling to access claims risk while implementing machine learning to detect fraudulent claims. 

Given the importance of customer experience has shifted from the service and marketing functions to a more public domain due to the proliferation of digital channels, insurers would have to go that extra mile to ensure a hassle-free claims experience. This "moment of truth" for the industry is an ideal opportunity to strengthen customer loyalty and enhance retention by using the best of technology innovations to build and manage trust.