Why Robotic Process Automation in Insurance needs an AI upgrade

8 min read
Nov 2, 2022 4:00:00 PM

Since the turn of the millennium, robotic process automation has assisted businesses in streamlining their operations by freeing up staff from monotonous tasks, accelerating workflows, enhancing accuracy, and reducing expenses. It has proven particularly helpful for the insurance sector, allowing employees to expedite tedious computer-based operations so they can concentrate on more crucial jobs in underwriting, customer service, sales, and other areas. Many jobs, including filling out forms, may be completed by RPA in 40% less time than they would be by manual procedures. 

But what if insurance procedures could be carried out even quicker? Business processes for organizations in every industry, including insurance, are changing as a result of new automation technology that makes use of artificial intelligence, machine learning, and other breakthroughs.

The value of RPA in Insurance 

RPA simplifies routine company procedures that sap employees' time, vitality, and morale. Insurance companies may increase accuracy and efficiency while freeing up human resources for more strategic duties by implementing RPA bots across various platforms. In the case of studies, ROI for RPA implementation in financial services has increased by up to 200% in the first year. 

Insurance businesses use a variety of old software and systems. RPA can integrate these disjointed systems so insurers can run operations quicker, pay less for personnel, and explore new business innovation opportunities. In fact, according to Gartner, 70% of new apps created by businesses by 2025 would employ low- or no-code technology. 

How Does RPA Work for the Insurance Industry? 

Insurance businesses use a variety of old software and systems. RPA enables companies to connect these disjointed systems with the least amount of coding possible, accelerating processes and cutting labor costs. 

RPA is well recognized in the insurance sector for connecting systems at a lower level with Application Programming Interfaces while also bridging the gap between traditional insurance systems. 

The following are some things that RPA insurance systems and services can accomplish for a flawlessly dispersed workforce: 

  • Open emails, collect data, then transition to core systems 
  • Integrate with decision-making engines and workflow automation for completely automated procedures 
  • Use AI to improve the capabilities of bots 
  • Utilize data to provide reports on profitability and transfer data between systems and apps by copying and pasting 


Read Also: How Artificial Intelligence is Transforming Business in 2022 


Why insurance robotic process automation is insufficient 

The primitive RPA tools from the early 2000s have been replaced by far more sophisticated automation technologies. Artificial intelligence-enhanced technologies may reproduce complex operations that closely resemble human analysis and decision-making, not just simple, screen-based jobs. AI technology is like a quantum jump in efficiency when compared to robotic process automation in the insurance industry. The following are some of the greatest issues with RPA usage on its own: 

  • Costly implementation 

Robotic process automation in the insurance industry is extremely time-, labor-, and cost-intensive to set up and deploy due to its script-based processes. For IT teams to build the ideal processes and then test them to ensure they are error-free, sometimes takes months of study. The lengthy period required to realize value is further accelerated by the hefty initial expenses. 

  • Not being flexible 

Making any adjustments to a process might also use a lot of resources because RPA processes depend on certain screen locations and other delicate elements. Because updating its RPA would require a resource loss, which makes enterprises oppose change. Even worse, employees would have to come up with intricate solutions to get past the RPA's restrictions, which would reduce productivity to pre-RPA levels. Additionally, updated visuals on OS systems and other applications may make screen automation bots unable to detect them, rendering delicate RPA platforms unusable and causing a cascade of problems. 

  • Limited application 

Robotic process automation in the insurance industry is only capable of carrying out tasks that take place on a computer screen. Unfortunately, processing papers and extracting information make up a large portion of the labor that overwhelms industry experts. Workers must still manage time-consuming tasks in addition to their high-level responsibilities. 

Transforming insurance with RPA & AI Use Cases 

Intelligent document processing is made possible by the most recent versions of AI-powered automation solutions. To improve workflows and reduce tiredness, AI enables computers to take over various duties connected to reading documents and extracting information. In this way, the human brain is effectively spared from mind-numbing labor. In the insurance industry, AI beats robotic process automation in the following ways: 

  • End-to-end document processing 

Virtually every stage of the document lifecycle may be automated by AI, including "reading" the language, categorizing the data, and automatically entering it into target databases or other systems for further processing. Contracts, emails, and even call transcripts are included in this category along with typical insurance paperwork like applications, claims, and invoices. 

  • Processing claims more quickly 

Only claims that can be processed quickly are authorized or refused. Intelligent document processing is far more efficient than processing claims manually or using RPA. AI quickly classifies data and integrates it into databases and customer relationship management systems. Systems that perform fraud detection models can link to some AI platforms. Insurers may now accept claims in a fraction of the time that their clients are accustomed to. 

  • Improved client service 

Better document processing efficiency leads to better customer service, especially in terms of quick response times. AI's ability to understand natural language enables it to recognize email intent and automate answers accordingly. When clients email a claim, artificial intelligence (AI) can automatically detect the request, give a suitable answer, and download and understand any email attachments for quick processing. 

  • Claims management 

From the First Notice of Loss (FNOL) to adjustment and settlement, RPA bots may simplify the whole claims process. Insurance companies can free up their claims inspectors to deal with important problems and exceptions by automating their high-volume claims filing procedures. Standard claims are resolved quickly while staff members concentrate on problems that are crucial to the company. 

  • Call center support 

Workers in the digital sector can assist those who assist clients. For instance, agents can handle service queries in real-time using attended bots or chatbots. RPA bots may improve staff cooperation, swiftly aggregate customer and product information, and boost policyholder retention. 

  • Personalized Recommendations 

Based on their search queries and purchasing patterns, AI may study consumer behavior. Customer preferences are understood through this investigation. To assist insurers to reach out to more potential consumers, it might give tailored suggestions. 

To understand the demands of their clients, insurance businesses may also utilize AI to examine the goods and services they offer. They would be able to provide goods that are appropriate for their target market. 

  • Forecasting customer attrition 

Every industry of the company has serious concerns about customer attrition. There is no exception in the insurance sector. Because consumers may simply move to more affordable insurance or better providers, customer turnover is more typical in this industry. Churn in the insurance industry, however, can result in significant losses. 

For insurance firms to maximize retention rates, cut expenses, and boost profits, customer churn prediction is crucial. Through the application of machine learning algorithms like random forest and gradient boosting approaches, AI may be utilized for predicting customer churn research. 

  • Administration of Policy 

Automatic transactional activity monitoring is one of automation's main advantages for the insurance sector. Bidding, quoting, rating, issuing, endorsing, and renewing are all part of the policy management process in the insurance sector. The insurance industries frequently struggle with an expanding client base due to their numerous operations. 

While traversing different applications, insurance robotics process automation may automate tasks like accounting settlements, tax settlements, regulations, credit control, etc. You will save a lot of time as a result during the full policy administration procedure. 


Read Also: Innovative Connection Between Insurance & Technology 


5 AI and RPA Trends in the Insurance Industry 


AI & RPA are expected to restructure the insurance industry's operations, cut costs, and improve the client experience. Here are five significant trends in AI and RPA in the insurance sector. 

1. Fraud detection and risk assessment using machine learning 

In ways that have never been feasible, AI is assisting the insurance industry's procedures for risk mitigation and fraud prevention. 

This is particularly true for insurers who must cope with an increase in the number of people identifying themselves as fraud victims after falling for scams or filing fictitious claims. 

Insurance companies employ AI to aid in the detection of fraud, the flagging of possibly fraudulent claims, and the handling of client complaints. These procedures are already used in some cases. 

For instance, several insurers are now utilizing AI to track customer complaints and look for trends that could point to fraudulent conduct, while others are still experimenting with this strategy in various ways.

2. Personalized Customer Care is Offered by Chatbots 

The insurance sector is going through a big change. In the past, the system was essentially closed; you had two options for filing a claim: either you spoke with an agent directly or you used an automated phone call. 

Online and mobile chatbots, and AI systems that mimic human discussions, have seen a significant change over the past several years. 

But hold on—things get better. Chatbots provide individualized customer service; there is no need to argue over renewals or price quotations or submit repeated requests for the same data. 

Therefore, businesses must now determine how to employ chatbots and AI to boost sales and enhance customer experience. Will they be employed as intermediaries or outside service providers? How will clients know which companies offer chatbot help and which don't?

3. Data-Driven AI Improves Risk Prediction and Mitigation 

Artificial intelligence has long been used in the insurance sector. The actuarial tables that insurance companies utilize are essentially machine learning systems. 

This software is adept at estimating risk in general, including the likelihood that someone would pass away a certain year. 

However, AI's capacity for prediction is where its true strength lies. Insurance providers may now employ data-driven algorithms to detect anomalous behavior and provide agents with a better understanding of the risk profiles of their clients. 

These new tools can assist agents in identifying "regular" and "abnormal" behavior and in figuring out which clients would profit the most from premium pricing. 

AI algorithms are not only predictive, but they may also save time and effort by guiding human decision-making. 

4. Automation of Usual Procedures 

RPA software is already being used by many businesses to automate repetitive operations. The insurance sector, which has opposed the concept of automating tasks that are still performed manually, has lagged in embracing technology. 

Companies have frequently used human agents to handle claims and settle disputes since it is impossible to automate such delicate tasks. 

New varieties of AI software, though, could offer some solace. According to 66% of insurers, automating tasks at work using artificial intelligence might increase employee productivity. AI, for instance, may advise agents on how to handle claims more effectively. 

That would enable insurers to make financial savings and lessen the financial burden placed on policyholders when an insurance claim wastes time attempting to respond to a customer's query after coverage has already been rejected. 

5. Claim Processing 

Insurance businesses rely on claims processors to complete paperwork in the absence of AI and RPA. An insured individual would typically get a statement several weeks after filing a claim and receiving payment from the insurance provider. However, a lot of that pushing paper involves repetition and blunders. 

Many businesses today handle claims in three days or less, sometimes without any human involvement. It may significantly impact on customer satisfaction and cost savings. 

Insurance businesses use AI to automate increasingly complicated tasks, such as processing claims, at the same time. By minimizing manual error and increasing efficiency, it can cut expenses. 

How Can TransformHub Help You with Automation Solutions? 

The financial software development services provided by TransformHub, the top digital transformation company, are recognized to speed up digital innovation in companies. Our financial professionals are renowned for reimagining how consumers pay, purchase, and invest in the contemporary period. Our solutions for full-stack FinTech development include: 

  • Financial options 
  • Software for a dynamic KYC platform 
  • Strategies for preventing fraud 
  • Software for wealth management 
  • Electronic wallets
  • Insurance technology 

To connect your business process with requirements for contemporary automation, speak with one of our technology specialists.