The insurance sector receives an overwhelming number of claims daily. The claims contain different papers, forms, and fees, and they also go through various checks. The manual processing of these claims is time-consuming and costly. Therefore, the insurers started to implement automation. The first step was traditional automation, and subsequently, many firms are opting for AI (Artificial Intelligence) over it.
Today, this situation poses a huge question for the insurance companies. In the case of AI vs Automation, the question is which model really brings a better return on investment, or ROI? In order to arrive at an answer, we first must have a clear understanding of the two approaches and then compare them in a very simple and practical manner.
Unraveling Traditional Automation in Insurance Claims
Traditional automation is rule-based. Humans set the rules, and the software just executes them. There is no reasoning or learning involved in the system. It just performs the tasks as per the commands. Traditional automation is widely applied in the insurance claims sector for processing the most basic activities. The processes that are included are entering the data, moving the files, updating the claims, and approving simple claims based on predetermined conditions. For instance, if the amount of the claim is within a certain limit and all the necessary documents are visible, the system will approve the claim.
This approach lessened the workload of manual workers in the insurance sector. It also allowed the companies to process claims faster than in the case of complete manual operation. Nevertheless, such a processing approach has many drawbacks, and one of the major drawbacks is that it can’t handle high claim volumes or complicated documents.
What AI Means in Insurance Claim Processing
AI really outpaces traditional automation. The actions of AI systems include, but are not limited to, reading, understanding, and learning from data. They also develop their capabilities corresponding to the changes of time; thus, by means of analyzing past claims and making decisions, they eventually train themselves to be more proficient.
AI has become widespread in usage in the insurance sector, covering lots of areas such as, e.g., reading of the scanned documents with the help of OCR technology, recognizing the various formats of documents, spotting and finally even outlining the patterns of fraud. AI forms the backbone of the most recent insurance systems that involve automated processing of claims.
In contrast to rule-based systems, AI has no capability to adapt if formats change. It rather goes on resolving new situations and becomes more efficient.
What Does ROI Mean for Insurance Companies?
In short, ROI is referred to as return on investment. In very simple terms it can be described as the amount of profit a firm receives against its expenditure.
For the insurance claim processing, a good ROI means reduced processing cost, quick claim payment, fewer errors, and more customer satisfaction. Automation that minimizes both delays and manual work but improves accuracy gives the best ROI. Let’s now see the AI vs. automation comparison from this ROI viewpoint.
Initial Cost Comparison Between AI and Automation
The traditional automation is the cheapest method in the short run. It entails the installation of software, creation of rules, and basic maintenance. Hence, numerous companies select it as their initial step towards automating the process.
The initial investment required for the artificial intelligence systems is more. It requires great data, training, and expert teams. This expensive starting point sometimes puts the companies in a dilemma.
Nevertheless, the traditional automation remains constant throughout its lifetime. On the contrary, AI continues to grow. Eventually, AI reduces the need for human effort much more and also produces a stronger ROI over the long run.
Claim Processing Accuracy
The truthfulness of insurance claims is an absolute necessity. Even a tiny mistake can cause the process to slow down, dissatisfaction among customers, and extra expenses.
The traditional method of automation has difficulty achieving precision in cases of hard-to-read documents, handwritten ones, and files that are in the new format. Each change in the format brings the need for creating new rules, which is a time-consuming and labor-intensive process.
However, AI is more powerful in these instances. The AI system can recognize all kinds of documents and also interpret the variations and, at the same time, minimize the errors made. So, this is a big step for the justice side of claim processing in the insurance area that once again leads to faster approvals and fewer rejections.
Claim Processing Speed and Scalability
With the growth of insurance companies, claim amounts also increase. The traditional automation can work effectively only to a certain extent. With the increase in the volumes of claims, the systems get slow and very hard to manage. AI systems, on the other hand, are built to be very large.
They can handle the simultaneous processing of thousands of claims at the same time without losing their pace. Moreover, the AI can take the situation of natural disasters or medical emergencies, which usually cause the eruption of a peak in the number of claims, more efficiently. Thus, this scaling ability directly translates to greater operational efficiency and significantly increased ROI.
Fraud Detection and Risk Control
Insurance companies have fraud and cost control as a core focus area. In this context, traditional automation can only apply simple checks based on rules and thresholds. It is completely incapable of detecting complex fraud patterns.
On the contrary, AI comes out highly competent in the area of fraud detection. AI goes back in history and looks at the past data, finds the most unusual behaviors, and then, early on, points out the claims that are risky. Insurance companies save tons of money by cutting off even a tiny percentage of fraud.
Thus, the role of AI is not only in cost savings, but it can also be seen as a powerful tool that improves the ROI beyond just cost savings.
Impact on Customer Experience
The customer demands that the claim settlement process be fast and flawless. The whole process of delay and repeated documentation requests leads to nothing but dissatisfaction.
The automation of traditional processes still requires a major input of human effort, which naturally results in a slower process. The intervention of AI results in less human involvement and faster decision-making.
The quicker the claim settlement, the higher the customer satisfaction, trust, and retention. It is a fact that satisfied customers are more inclined to renew their policies and suggest the company, which will eventually increase the ROI indirectly.
Maintenance and System Flexibility
Old-fashioned automated systems have to be updated quite often. If a new document type comes up or if there is a change in policy, the corresponding rules need to be rewritten.
On the other hand, AI systems can be very flexible. They take in and learn from the new data automatically. This not only reduces the IT team’s workload but also cuts down maintenance costs in the long run. Having less maintenance work means higher efficiency and savings over time.
Real-World Example of AI vs Automation
Picture an insurer that handles 10,000 claims monthly. The traditional automation processes allow many claims to enter the manual review stage due to the limitations imposed by the rules. Thus, the time taken for processing remains high.
On the other hand, with AI-based automated claim processing insurance through AI programs, most claims get dealt with automatically. There’s a drop in errors, quicker approvals, and early detection of fraud. Clearly, that is the reason why AI proves to be the best in terms of ROI in the long run.
Difficulties of Employing AI
AI has its flaws. It depends on being top-notch and perfect and deciding and doing it to perfection, deciding at the start. The cost of setting it up might be quite huge, and the process itself will take time to finalize.
On the other hand, once the AI is correctly set up, it will yield continuous value for several years. The advantages thus outweigh the drawbacks.
Conclusion
The answer to the question of AI vs automation comparison hinges on the company’s objectives. In the case of small businesses with transferable claims, traditional automation would suffice.
Yet, AI is undoubtedly the one giving a much bigger and long-lasting ROI for insurance companies that are growing and wish to have speed, accuracy, and fraud control, along with better customer experience.
AI is not just about automating the process; it is about making an intelligent decision. In the present-day cutthroat insurance market, the automated claim processing insurance systems powered by AI technology are not a choice anymore but a need for the sustainable growth of the insurers.
