online insurance claims, chatbot for insurance claims
The concept of Straight-Through Processing (STP) has been around in the financial services market since the ‘90s. The idea is to reduce the need for human intervention and create fully automated business workflows that speed up transactions. Thanks to improvements in software tools and artificial intelligence, STP can now be effectively applied to insurance claims.
STP enables carriers to be responsive, it reduces the risk of errors, drives down costs, and results in much swifter claims processing, which is good for customers and carriers. It was automation coupled with artificial intelligence (AI) that enabled start-up insurer, Lemonade, to process a claim in just three seconds earlier this year. Let’s take a closer look at some of the problems STP can address.
The problem with manual processing
Carriers are under pressure to reduce costs, but manual claims processing is time-consuming, labor intensive, and fraught with the risk of error. There are bottlenecks that slow progress down, hand-offs between siloes, and disparate systems and databases to search and collate. A single policy might necessitate data exchanges from multiple agencies, carriers, and other third-parties. Due to incompatibilities between IT systems and siloes, that data is often manually re-keyed.
When inaccurate or incomplete data is discovered, communications can take several days to pass from adjusters to agents to customers and then back again. The result is a slow process with limited transparency for the insured. For carriers, it’s expensive, and every manual task and transition introduces an opportunity for error.

The potential power of AI
Artificial intelligence has improved dramatically over the last few years and it is having a tangible impact on many industries. A full 75% of 550 insurance executives surveyed by Accenture said they believe that AI will either significantly alter or completely transform the overall insurance industry in the next three years.
There are several ways AI can improve STP, according to PwC’s annual Top Insurance Issues Report for 2017. Robotic process automation (RPA) can automate data entry and validation, track compliance and standards, and streamline processes. Machine learning can provide insightful analysis and predictive modelling. There’s even scope for AI to assist with the looming skills gap, with 61% of carriers reportedly exploring the benefits of humans and machines working together.
Removing as many manual steps as possible is going to be beneficial, but it’s not all-or-nothing. Taking steps towards automation and leveraging AI where you can, also frees up skilled adjusters to bring their experience to bear where it can add the most value. AI is excellent for eradicating repetitive manual tasks and establishing consistency. With machine learning and the right metrics in place it’s also possible to create a self-improving system.
Reaping the rewards of STP
Expectations about service are changing rapidly with the rise of a customer-centric, always accessible approach. Customer service is growing more and more important, and it’s easier than ever for customers to switch carriers if they have a bad experience.
In Accenture’s Customer Service Survey, the top two key contributors to customer satisfaction with the claims experience were speed of settlement, which 95% of respondents said was important or extremely important, and transparency of the process, which 94% of respondents felt was important or extremely important.
The great thing about STP is that it drastically reduces claim cycle times. The standardization of customer data reduces the risk of error and ensures that everyone receives a consistent level of service. By automatically collating data from disparate sources and applying the same logic, STP systems can handle straightforward claims.
We’re talking about a technology process to automate the processing of contents claims from start to finish requiring no human intervention from insurance carriers. Once a user submits their inventory, a proprietary rules engine scores the contents for fraud and fast tracks eligible claims for instant payment settlement. Updates can be automated to keep customers fully informed at every stage of the process.
When specific criteria are not met, it can trigger a query that may automate further investigation, spark a request for customer input, or command the attention of an experienced adjuster. With time-consuming, repetitive tasks eliminated, carriers can cut labor costs per claim and reduce the number of errors, all while speeding up the overall process.
The opportunity to improve efficiency and accuracy, while boosting the customer experience, cannot be passed up. Carriers that fail to embrace AI and automation to achieve STP risk being left behind.
To see how Elafris Virtual Insurance Agents can help your company click here to schedule a free online demo.
This article was originally published on propertycasualty360

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