Automated data extraction: The key to straight through processing in insurance
Customers prefer quick insurance solutions and opt for insurers who deliver faster, transparent, and efficient services. To enable this, insurers improve straight through processing (STP) and automatically process transactions without human intervention. STP ensures insurers have speed, consistency and productivity to provide a convenient experience to their customers. A wave of new players, who have understood this, offer highly innovative value propositions and operate at higher speed and effectiveness.
The emerging social first insurers like Lemonade have algorithms that are smart enough to analyze vast amounts of data, where they promise to deliver claims in just 3 minutes. Though traditional insurers realized this trend, they are currently plagued by critical challenges like manual operations, lack of people-centric and personalized offerings, fraud and risk threats, and so on.
One of the main reasons why traditional insurers are unable to keep pace with demand is that they are heavily dependent on document-driven business processes that are mostly manual, drawn out, and involve stressful phone calls. These processes involve data gathering, entering the data into disparate systems, and data validation.
In any enterprise, only 20% of its data are structured and are easy to process, whereas 80% of the data are either semi structured or unstructured and difficult to process. Structured data like tables or boxes with clear descriptors are easy for people to read, understand and identify key information. Unstructured or semi-structured data like emails, texts, images, video, audio are difficult to gather, store and analyze.
With a focus only on structured data, where data extraction is straightforward, the STP is just 30%-40% and the human intervention is higher. But by bringing structure to unstructured data, there is an increase in STP of more than 70% and less human intervention.
Manually processing the data and performing repetitive tasks is time-consuming and leads to increased customer wait times. This challenge often leads to inconsistencies and errors in data, increased costs, and reduced customer satisfaction. Also, with semi and unstructured data in all the processes, it becomes difficult for insurers to streamline and operationalize existing processes. To sustain, improve market share, and grow, it becomes essential for insurers of every quadrant to ensure fast and accurate operational delivery through advanced automation.
The data extraction avenue
The emerging value drivers in the insurance journey roadmap will accelerate the insurers to reconstruct their businesses and secure their future competitiveness. The technological advancements in each insurance process is not just a fad but an essential strategic function. Identifying the differentiators in traditional businesses due to emerging technology implementation is a strategic move to pace ahead.Here is the illustration to show the difference in process efficiency improvement between a manual process and a fully automated data extraction process that drives the insurance ecosystem.
The absolute imperative: STP in insurance
STP is no more an option but a priority for insurers to improve their business operations and create a more convenient experience for their customers. The emergence of intelligent automation technologies has helped the insurance industry to achieve data excellence and move towards STP more easily. It helps them make decisions and complete transactions based on algorithms, predictive models and simple business rules by ingesting the data digitally.
The reason to improve STP by extracting unstructured data could range from optimizing customer experience, reducing costs and errors to improve process efficiency, or it could be a part of your digitization efforts. Whatever the reasons may be, here is a checklist that can help identify the right strategy to reap high ROI:
An automated data extraction not only helps in transforming the traditional operating model of the insurance industry but also helps critical resources focus more on productive tasks such as managing complex claims, improving underwriting decisions and providing world-class customer service and free them from doing manual data extraction work. With enormous value, data extraction is an essential strategic function.