*The above picture was created using Generative AI Insurers Rank Automation As Important, But Find RPA Difficult Why?
While many insurance companies are conservative by nature, recent disruptions in business models, customer expectations and technological advances are obliging insurers to re-evaluate the digital nature of their operations. Continual deployment of new technologies are required to improve customer experience, streamline the claims process, and reduce back office overhead in the likely recessionary environment ahead. Because of this, automation has been at the forefront of many CIOs, Finance and IT leaders in the industry. The primary cost drivers in the insurance industry are compliance with regulatory requirements, rollout of new products and servicing of claims. While insurers have managed to tackle some of the back-office tasks, automating processes with higher variability remains elusive.
Statistics show:
- 80% of insurers realize the need for digital capabilities.
- 99.6% of those found it difficult to implement digital innovation
- There is potential to automate nearly 50-60% of the back-office processes by 2025, resulting in 66% time savings for insurers.
Insurers are Deploying RPA but Yet Still Limited in What They Can Automate
The statistics above seem to paint a conflicting tale. On the one hand, it is clear insurers recognize the potential power of automation. Insurers can use automation to de-risk their business and position the company to compete both with other legacy players and insurtech startups. It is projected that by 2025, 25% of the insurance industry’s operations and activities will be automated. The growing implementation of automation in the industry gives insurers a solution to reduce cost, collect more accurate data on the insured, and gather feedback to deploy new, more personalized products. The use of traditional RPA tools in this industry has also reduced the number of human errors incurred and improved customer service. RPA succeeded in automating many of the highly standardized processes, and yet 99% still express a challenge in implementing digital innovation and only a fraction of even back office processes have been automated today. Why this disconnect if it’s such a focus?
The challenge lies in the lack of standardized processes and pain of implementing RPA. Particularly in insurance, data required for many processes may vary from agent to agent, or source to source. High volumes of documentation + variability in those documents can crash automations or require continuous maintenance. In processes like claims, arguably the biggest opportunity for automation for insurers, the vast number of rules and logic required makes the initial implementation of RPA often a burden, and requires frequent meetings between the subject matter experts (claims processors) and the people implementing automation (RPA developers) to detail and communicate all of the different rules. In most cases, the ROI is not sufficient with this approach. Instead, an automation solution is needed that can learn logic, handle variability and be easier to deploy.
Generative AI Automation: Flexible and Easy to Modify
The average business user is not technology savvy, nor do they come with deep domain experience with various coding languages or training on RPA. These skills are in high demand, specifically in the insurance industry, therefore there is a need to be met in this marketplace. Imagine if there was a more user friendly version of these game changing RPA tools that enables the average user to build and manage automations? What if the automation tool itself could learn how to handle each specific document, and problem solve exceptions without a lot of up front work?
Here Kognitos, combined with large language models like GPT3 steps in to open up the power of automation to less standardized, highly variable processes. Claims processors can now teach automation products how to get the desired information from a claim with simple statements like “For this vendor, the patient ID is always under the group number.” Logic can be taught to automation in English, like “If the claim address does not match the account address, send an email to the insured for clarification.” Using Generative AI, all exceptions are handled in a back and forth, conversational manner that any user can understand. All steps of the automation are in English so anyone can audit exactly what occurred, and set approval steps as needed.
Using GPT3 to Teach Rules to Claims Automation
Kognitos is Generative AI for Automation. With Kognitos, implementation costs are reduced, maintenance costs are all but eliminated and many processes now have strong ROI potential with automation. Additionally, the business users are able to interact with automation in a way that requires no training, and is easy to understand. Now insurers can develop a competitive edge and cater to customers without the frustrations previously experienced when rolling out digital innovation.
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Our clients achieved:
- 75%manual data entry eliminated
- 30 hourssaved on invoicing per week
- 2 millionreceipts analyzed per year
