A great tool to help us get some time back is automation, specifically to automate different actions or tasks we find ourselves doing over and over again. After all, you figured it out once. Why not automate that action so you can spend your time on something more valuable?
FACT: Despite the needs and importance of automation, only 5% of insurance firms actually use robotic process automation (RPA) to analyze claims, and only 25% plan to do so in the future
This article will walk you through how to automate action that insurers find themselves doing quite often: claims processing.
Why Claims Processing Automation?
In the first place, why do insurance companies struggle with digitization and automation? Setting aside the normal factors such as employee resistance to change or a lack of budget and technological capital, there is one major explanation that stems from the nature of insurance: insurance processes are typically too variable and unstructured to be easily integrated into the digital workflow.
For example, claims data comes in a variety of formats (photos, handwritten papers, voice memos) and is exchanged across a variety of channels (email, document attachments, phone calls, chats), making it incredibly difficult to obtain and evaluate with high precision without the help of an investigator. Decision-making is often more complex than an off-the-shelf machine can accommodate — understanding the context of each individual case is required.
Well, does it mean that the insurance industry can never be fully automated and that every step of the process will require human intervention?
Obviously not. More advanced approaches, such as AI, Machine Learning, and ML-based robotic process automation, will be needed to simulate human perception and judgment. That’s where the modern automation technique, called “Cognitive Automation” comes in.
Here’s an example:
Read how we implement this idea to our client’s claims processing automation.
Benefits of Using AI-Powered RPA in Claims Processing
By intelligently automating existing workflows, insurance companies can reduce the time and resources required to process claims. To develop a valid risk assessment tool, training data would need to be defused using a method that would draw them out from the second source of truth and provide a way to determine whether the process is valid and successful.
Any developer or jurisdiction that uses a risk assessment tool must ensure that the tool provides information in a simple way. If companies are using such tools properly, judges, lawyers, and court staff should have the ability to understand how their claims are interpreted.
The data could also be used to develop tools to help consumers assess market planning options by comparing the payment methods of claims as well as the price. Automatic damage assessment and image analysis is much faster and more accurate.
With Artificial Intelligence (AI), insurers can automate the claims process, saving time and resources that go into the underwriting process, lengthy questions, and surveys. A consistent and agile workflow for handling claims enables claims assessors to respond to customers more quickly and accurately, thereby creating a smoother customer experience.
The faster the process is and the shorter the tedious tasks of automation technology, the more damage assessors will be able to assess more of them. Most importantly, this new tool further helps to deliver cost savings and a timely return to work.
How Artificial Intelligence Works in Claims Processing Automation
By capturing customer-specific data in key areas, the tool enables companies to create a complete report by calculating the impact of automated laser application technology on a customer’s claims process compared to their existing process. With additional analyses in combination with audit results, it can identify process problems by checking suppliers’ payment flows.
Suppliers who are overwhelmed with their current claims risk game and recognize the need for change should consider introducing a claims processing automation and risk management system. Moreover, self-assessment tools have an integrated process for claims processing automation so that the status of claims can be initiated and tracked.
This allows companies to rely fully on image recognition technology for the first stage of claims automation over time. After then, automatically settle claims and resolve insurance fraud cases. As new AI tools constantly reinvent claims management, payouts will inevitably involve a significant increase in the quality of customer experience and a reduction in claims costs.
The value that will be generated from AI use cases in the future requires that carriers integrate skills, technologies, and insights from across the organization to provide a unique and holistic customer experience.
The report seeks to address the technical and human challenges at the computer interface that prevent risk assessment tools from being used to inform fair decisions. In this case, the “human-computer interface” refers to how people collect and feed information into the tool and how they interpret and evaluate the information generated by the tools.
The staff no longer have to stay overtime at work and can get Gleematic to do the job. Gleematic is definitely can help companies to reduce human errors, save time and costs, and increase productivity.
By: Kezia Nadira
Reference
Webb, R. (2019). 6 Benefits Utility Companies Can Achieve With Automated Risk Management. ClearRisk. Retrieved February 4, 2021, from https://www.clearrisk.com/risk-management-blog/benefits-of-risk-and-claims-automation-utilities
