Insurance professionals will agree that speed and efficiency are critical elements for a well-functioning claims process. However, processing claims has traditionally been a complicated and lengthy affair; as it stands, many carriers still find themselves bogged down by manual claim activities, data inconsistencies, and errors that result in delayed settlements, increased management overhead, and perhaps most crucially—negative customer experiences. Fortunately, insurance firms these days have various solutions at their disposal for mitigating these issues
In this article, we’ll explore 6 ways insurance enterprises can accelerate their claims administration workflows to offer customers a more streamlined and positive experience.
1. Process Mining for Surfacing Claims Process Inefficiencies
Process mining is carried out by analyzing business processes, assessing their performance, and identifying any potential issues. Within the process mining activities, discovery techniques are carried out using event data to develop process models; these models represent the operational processes’ key activities and can be used for surfacing bottlenecks and problematic edge cases.
For example, insurance firms can use process mining tools to analyze critical data collected at key points during the customer’s claim journey. By using this data to visualize the entire claims process, carriers can surface potential issues (e.g., bottlenecks, idle time, extraneous or skipped steps) that may ultimately impact customer satisfaction.
2. Implementing RPA in Claims Processes
Accelerating the speed at which claims move through administration workflows is crucial for meeting rising customer demands/expectations—that said, allocating more human resources to scale claim handling operations is not a scalable, long-term solution.
Insurance firms can adopt AI/ML technologies to enable their employees to work smarter, not harder—specifically, by relieving them from manual, repetitive tasks and shifting their focus to delivering more customer value (e.g., more personalized interactions and informative touch points). For example, AI/ML can be used to quickly process data from disparate documents and forms, resulting in faster collection and verification of claims intake data.
These robotic process automation (RPA) solutions are exceedingly performant at tasks prone to human error–external data gathering, pointing and clicking, typing, double entry of information, and checking values, to name a few.
3. Standardizing Processes and Formats
Inefficient claims workflows are often stifled by differences in standards used by the various parties involved in the claims lifecycle (e.g., customers, insurers, brokers, agents, banks/financial institutions). By standardizing processes and formats through an integrated claims management system, insurers can ensure that all parties have access to the information they require, in the expected format.
4. Preventing Workflow Delays Caused by Missing/Erroneous Data
Even with the proper automation in place, missing and erroneous data is bound to create bottlenecks in the claims administration workflow. AI/ML-driven automation can automatically survey customers or query them for additional claims information at each/any stage of the claims process; in turn, customers are reassured that their claims are moving forward in a timely, efficient manner.
As mentioned previously, automated claims processing workflows will sooner or later encounter scenarios that require human handling. In the event of missing data, AI/ML-driven automation can automatically solicit customers for additional information. However, more extreme exceptions may still require assistance from the appropriate staff member/employee or third party. In these cases, claims administration workflows can be designed to automatically route specific exceptions to the proper individuals for expedited handling.
5. Improving the Claims Communications Flow
During a claims investigation, various parties (e.g., customer, claims adjuster, agent) are involved in critical, sometimes contentious interactions to paint a clear picture of the incident. With an automated claims process in place, such interactions are avoided; instead, all artifacts (e.g, evidence, photos, reports/documents) are digitized, stored, and sent to the appropriate parties automatically.
6. Adopting a Low/No-Code Claims Administration Solution
In the past, implementing a customized solution for claims management meant building one in-house—a costly effort in terms of both time and money. These days, insurance enterprises can implement a low or no-code solution that enables them to get up and running quickly with powerful automation capabilities built-in, with the option to further customize for existing or planned claims processing workflows.
Leading claims management solutions enable the proper collection, digitization, and archival of claims data for all parties, consolidate claims information from various sources, and accelerate their claims administration workflows through comprehensive, intelligent automation. Furthermore, competent solutions should play well with existing systems and legacy platforms, if a firm opts for a more gradual system migration.
Competent low/no-code solutions will allow insurance firms to customize their implementations through the use of APIs—for example, Zurich Insurance Group leveraged the Ventiv Risk Management Information System API to connect directly with one of its largest and oldest customers, Nestlé.
Automated Claims Administration Solutions
By adopting an enterprise solution specially designed for insurance policy administration, firms can reduce the amount of time, level of effort, and errors associated with managing policies and claims. These solutions allow insurance carriers to optimize their workflows and automate processes for both collecting claim data and delivering it to the relevant parties.
To learn more about how an automated claims administration solution can help accelerate your claims administration workflows, request a demo today or contact us for additional information.
