As the industries are getting digitized more and more, most insurance companies constantly invest in IT services to serve their customers better. According to the Mckinsey report, the insurance companies will increase their investments by 200% in RPA and AI.

Today’s post will focus on how a new generation of technology like Artificial Intelligence (AI) and Robotic process automation (RPA) will revamp the entire insurance industry. Moreover, we will also discuss how they are changing many existing processes and replacing traditional roles with intelligent software, helping adapt to changes.

What does AI in insurance industry mean?

Artificial intelligence covers various technologies, including machine learning, deep learning, natural language processing (NLP), and natural language generation (NLG).

All these technologies work together to facilitate the automation of repetitive tasks. AI and RPA can significantly improve insurance carriers’ efficiency and customer experience when interacting with them.

AI-powered chatbots – or conversational AI – provide a new way for insurers to communicate with their customers. These bots automate customer service by routing clients to the right agent.

The technology is to help insurers extract vital data from documents to reduce manual data entry. This streamlined process frees up time for agents to focus on more complex problems that require human intervention.

5 AI and RPA trends in the insurance industry

Artificial intelligence and robotic process automation promise to revamp the insurance industry process, reduce costs and provide a better customer experience. Here are five notable AI and RPA trends in the Insurance Industry.

1. Machine learning for fraud detection and risk assessment

AI is helping to power the insurance industry’s fraud prevention and risk mitigation processes in a way that has never been possible.

It is especially true for insurers that have to deal with growing numbers of people claiming to be victims of fraud, either by falling for scams or reporting fake claims.

Insurers use AI to help them detect fraud, flag potentially fraudulent claims, and respond to customer complaints. Some of these practices are already in use.

For example, many insurers now use AI to monitor consumer complaints and detect patterns that suggest a fraudulent activity, while others are still experimenting with this approach in different ways.

2. Chatbots offer personalized customer care

The insurance industry is undergoing a significant transformation. In the past, it was primarily a closed system; you either dealt with an agent or put your claim in through an automated phone call.

The last few years have seen a massive shift in online and mobile chatbots, artificial intelligence (AI) programs that simulate human conversations.

But wait, it gets better. Chatbots offer personalized customer care – no more arguing about renewals or price quotes or making duplicate requests for the same information.

So now, companies have to decide how to use chatbots and AI in the industry to drive revenue and improve customer experience. Will they be used for agents or third-party providers? How will customers know who’s doing chatbot support and who isn’t?

3. AI uses data to better predict and mitigate risk

The insurance industry has been using artificial intelligence for decades. The actuarial tables used by insurance carriers are, in essence, an artificial intelligence program.

This program has a good understanding of determining risk across the board, such as the probability that someone will die in a specific year, get struck by lightning, or be involved in a car accident.

But the real power of AI is in its predictive capabilities. Insurance companies can now use data-driven programs to unusual flag behavior and give agents a clearer picture of their customers’ risk profiles.

These new programs can help agents distinguish between “normal” and “abnormal” behavior and determine which customers would benefit most from special premium pricing.

In addition to being predictive, AI algorithms are also capable of helping humans make better decisions with less input time and effort.

4. Automating routine processes

Several companies are already using RPA software to automate routine tasks. However, it’s been slow to catch on with the insurance industry, which has resisted the idea of automating functions that are still done manually.

Companies have often relied on human agents to process claims and resolve disputes because automating such sensitive functions is impossible.

However, new types of AI software could provide some relief. 66% of insurers feel that using artificial intelligence to automate specific tasks in the workplace can make their employees work more efficiently. For example, AI can provide advice to help agents process claims more efficiently.

That could help insurers save money and reduce the financial impact on policyholders when an insurance claim spends unnecessary time trying to resolve an inquiry from a customer who has already been denied coverage.

5. Claim processing

In the absence of AI and RPA, insurance companies rely on claims processors to fill out paperwork. It used to take several weeks for an insured person to receive a statement after making a claim and being paid out by the insurance company. However, much of that paper-pushing is repetitive and repetitively errors.

Today, many organizations process claims within just three days or less, often without human interaction. It can make a huge difference in customer satisfaction and lower costs.

At the same time, insurance companies embrace AI to automate more complex work, including claims processing. It can reduce costs by eliminating manual error and maximizing efficiency.

Key benefits of AI in the insurance industry


The insurance industry is one of the most data-driven industries in the world. The industry is inundated with massive volumes of data. These data can come from various sources, including an insured’s details, medical records, and financial history.

It’s no secret that AI and RPA can help insurance companies process, analyze, and store all this data. Here are some of the most significant benefits:

1. Process automation and streamlining

Automation tools can be used to automate processes across various departments of an insurance company, like claims management, underwriting, marketing, and customer service.

RPA can be used to automate simple and repetitive tasks like data entry. It is also used to automate complex rules-based tasks. Companies use AI, machine learning (ML), and computer vision to automate claims processing.

2. Customer service improvements

One of the most significant new trends in the insurance industry is an increased focus on customer experience.

Clients want to meet their needs quickly and efficiently. They want to communicate with their insurance companies quickly and get answers fast.

Clients also want to access their information anywhere at any time. To keep up with these demands, insurers should adopt AI and RPA technologies that help automate different processes and streamline workflows across departments.

3. Fraud detection

Insurance fraud is a costly problem for the insurance industry. According to experts, it costs insurers nearly $80 billion per year.

AI can help companies effectively detect fraud by identifying patterns or anomalies in claims data and other factors such as applicant information and medical records.

The combination of AI and RPA helps automate detecting fraudulent cases and reduces the need for human intervention to minimize processing time while improving accuracy.

4. Advanced analytics and more accurate underwriting

Underwriting usually takes a lot of time due to manual research of application data and decision-making based on specific criteria.

But with machine learning algorithms, this process can be automated significantly, making decisions through data analysis and learning from past experiences — all in seconds or minutes. Additionally, RPA can help with automating the end-to-end process.

5. Personalized customer experience

The insurance industry is one of the most dynamic sectors globally, with the most number of customer touchpoints across a wide range of channels.

Even though customer engagement is critical to the success of any business, most insurers are still relying on outdated, manual processes that are time-consuming and lead to customer dissatisfaction and attrition.

Artificial Intelligence (AI) and Robotic Process Automation (RPA) can help insurers transform their traditional customer-centric processes by automating them for enhanced customer experience.

Top 5 use cases of AI in the insurance industry


The report also reveals that insurers are looking forward to investing in these use cases as they see potential growth in the revenue of $1.1 trillion across the functions. AI and RPA have changed how insurance companies handle their business, from processing claims to answering customers’ queries.

Here we will explore some of the ways AI and RPA have revolutionized insurance industry processes:

1. Automated claims processing

Claims processing is one of the critical areas where artificial intelligence has significantly impacted the insurance industry.

The initial claim processing was carried out manually, which led to an increase in costs and time. Moreover, there were chances of errors occurring, which led to faults in processing claims.

2. Deliver efficient customer support

Customer support is another area ripe for automation in the insurance industry. It can include simple chatbots that answer routine questions or full-blown virtual agents that can handle complicated customer interactions. Both have advantages over traditional human agents regarding cost, consistency, and scalability.

3. Fraud detection and prevention

The insurance industry is heavily dependent on data for pricing insurance policies and detecting fraud cases. There have been instances where fraudsters have tried to game the system by providing incorrect data.

However, insurers can analyze these data sets using advanced AI tools and detect inconsistencies between the information submitted by customers and third-party sources such as social media platforms. It helps companies prevent fraudulent activities while increasing policyholder trust.

4. Personalized recommendations

AI can analyze customers’ behavior based on their buying patterns and search queries.

This analysis understands customer preferences. It can suggest personalized recommendations to help insurers reach out to more potential customers.

Insurance companies can also use AI to analyze their products and services to determine their customers’ needs. It would allow them to offer products that are relevant to their audience.

5. Customer churn prediction

Customer churn is a significant concern for every business sector. The insurance industry is no exception. Customer churn is more common in this field because customers can easily switch to cheaper policies or better providers. However, churn in the insurance sector can lead to huge losses.

Customer churn prediction is essential for insurance companies to improve retention rates, reduce costs, and increase revenues. AI can be used for predictive customer churn analysis through machine learning algorithms such as random forest and gradient boosting techniques.

To wrap up things

Every industry is reshuffling its business model to accommodate the paradigm shifts created by advancements in technology. It means that the insurance sector is no exception. Their most important need of the hour is a technology that helps them automate their current process flows.

So, there is no doubt that AI and RPA will generate growth in the insurance sector. On the one hand, this process can significantly improve insurance companies’ coverage; on the other hand, it will make the service even more convenient for clients.