The insurance industry has undergone a great transformation in recent years due to digitization and technological advancement. Artificial intelligence is increasingly becoming a valuable tool for insurance companies, allowing them to improve internal processes, streamline operations and provide better customer service.
In this article, we explore examples of how leading insurance companies are using artificial intelligence and automation to transform their internal processes, offer more personalized service to their policyholders, and improve the customer experience.
Automated document verification
Insurers need to quickly verify the documents submitted by their clients during the initial process or when there are significant changes to their policy. However, this can be very tedious, when handling large volumes every day, if it is done manually, it is necessary to review each document one by one very carefully before approving them.
To streamline these processes, many companies have begun using AI-integrated automated services such as Amazon Rekognition along with technologies such as OCR (Optical Character Recognition) and workflows such as DANAconnect. This combination works especially well when it comes to fast and immediate automatic recognition of important documents. You can analyze documents issued by government authorities such as passports or driver’s licenses using OCR techniques, extracting key information about the holder and automatically incorporating the corresponding digital profile. This drastically speeds up both document verification and allows for a clear base from which to start new services associated with the document obtained.
The proper use of these solutions allows drastically reducing downtime associated with repetitive work, saving considerable time, both for internal personnel in charge of validation and for the client, creating a positive image with clients who appreciate speed and efficiency without compromising security.
Of course we cannot forget to mention how beneficial this is regarding regulatory compliance and due diligence (KYC, AML and CTF).
Sentiment analysis: Understanding customers better
For any company, understanding the needs and desires of the customer is essential. In the particular case of the insurance industry, this translates into a positive experience for the user, which can ultimately lead to a higher retention rate.
Sentiment analysis uses algorithms based on artificial intelligence to examine large amounts of data produced by interactions between customers and employees, with this process, key patterns can be identified in order to offer personalized solutions.
Companies use this technology to analyze comments left by their users during customer experience measurements and satisfaction surveys. In this way, they can quickly detect any common problems that may be negatively affecting their image with consumers, such as recurring problems associated with technical service, excessive delays, etc.
Conversational AI: automatic identification of customer intentions
Chatbots and automated customer service systems are very useful for many companies as they allow their customers to request information online, which is much faster and more efficient. However, these bots can be even more effective if they are able to identify the intentions behind the message.
The identification of intentions in natural language is another useful tool available thanks to the use of artificial intelligence, that is, simply being able to converse with the language we use daily. This technology allows you to create conversational chatbots capable of answering frequently asked questions, preparing precise answers, saving valuable man-hours and answering repetitive queries.
The artificial intelligence behind conversational systems allows us to automatically identify the intentions behind each question asked during the interaction, thus allowing us to obtain a more precise answer according to the user’s requirement without any human intervention.
Automated analysis of unstructured documents
In some situations there are specific documents where it is not enough just to recognize them but also to process and interpret them. A large amount of relevant information is found in unstructured documents such as emails or printed records. The manual task required to classify this information can take many days; however, once again the integrated AI allows them to be processed automatically, considerably saving time as well as reducing errors caused by human fatigue.
With language processing tools insurers can analyze unstructured text, such as contents of emails, invoices, money orders or medical reports. This technology allows insurers to obtain valuable information about customers and their needs.
By integrating Amazon Comprehend, via API, into DANAconnect’s automated flows, insurers can insert a little task in the process to automatically analyze these documents and extract relevant information such as the date of the accident, the type of injury sustained by the customer, and other important details before moving on to the next step. In this way it is possible to structure data from different sources and with different formats.
This helps insurance companies to process these requests faster and respond more quickly to the customer.
Automatic response generation
Chatbots have been commonly used recently due to their ability to respond to queries quickly, but they also have limitations when they are programmed to only answer basic and impersonal questions.
Chatbots with GPT-3.5 integrations use advanced artificial intelligence to answer complex questions asked by users. The ability of these systems lies precisely in their ability to understand the context behind each question received, which allows them to generate a clear coherent response according to user requirements.
Furthermore, GPT-3.5 capable chatbots can also generate personalized and unique responses for each user. This is a huge advantage compared to traditional chatbots that often offer generic and impersonal responses.
The proper use of these solutions can help improve the image before users by providing immediate help, improving the customer experience with the company.
Automatic Fraud Detection
Fraud detection is another area where artificial intelligence is being used in the insurance industry. Insurance fraud is a significant problem that costs the industry billions of dollars each year. AI can help insurers identify fraudulent claims and prevent losses.
One way AI is used in fraud detection is through predictive modeling. By analyzing historical data and identifying patterns, AI can predict which claims are more likely to be fraudulent. This can help insurers prioritize their investigations and allocate resources more effectively.
Another way AI is used in fraud detection is through anomaly detection. AI algorithms can analyze large amounts of data and identify unusual patterns or behaviors that may indicate fraud. For example, if a claimant has a history of making frequent claims for the same type of injury, this may indicate that the claims are not legitimate.
AI can also be used to analyze social media and other online data to identify potential fraud. By monitoring social media posts and other online activity, insurers can identify claimants who may be exaggerating their injuries or engaging in other fraudulent behavior.
Overall, the use of AI in fraud detection can help insurers reduce losses and improve the accuracy of their claims processing. By identifying fraudulent claims more quickly and accurately, insurers can save money and provide better service to their customers.
The insurance industry has undergone a great change thanks to the incorporation of new technologies, including artificial intelligence.
Integrated artificial intelligence is radically transforming how insurance companies work, making it possible to optimize downtime between different critical points during the entire insurance process, as well as improving both the emotional and functional customer experience.
Access to unstructured information is facilitated by simplifying document and text classification tasks with artificial intelligence, while chatbots with GPT-3 and intention identification offer more personalized and intelligent attention. In short, the integration of IA in insurers’ processes allows improving operational efficiency as well as providing fully customer-focused services to achieve full satisfaction of the end user.
Now, we just have to wait and see how this field will evolve and imagine future applications where artificial intelligence can continue to transform everything even faster.