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How AI And Machine Learning Are Helping The Insurance Industry

Artificial intelligence (AI) is a technology that enables computer systems to accomplish tasks that would normally require human interaction. The use of AI has increased exponentially across all industries over the past several years. AI can help automate labor intensive processes, leading to lower costs and saved time. It can also be used to understand customers better. We are now using AI throughout our daily lives, often without realizing it. 

Over the past several years, AI technology has progressed immensely and continues to develop and improve. It has become increasingly proficient at performing tasks that were historically difficult for computers to execute. The successes of AI are also being facilitated by the massive amounts of data we have today, increased computing capabilities, and changing consumer expectations. 

AI is composed of several technologies

AI is composed of several technologies, including but not limited to: 

  1. Machine Learning: Machine learning enables a computer system to make predictions or make some decisions using historical data without being explicitly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate results or give predictions based on that data.
  2. Deep Learning: Deep learning is a subset of machine learning that has networks capable of learning from unstructured or unlabeled data without any supervision.
  3. Neural Networks: Neural networks are a subset of Deep Learning. They can identify, classify and analyze diverse data, and can find patterns that are too complex for a human to recognize. Neural networks rely on training data to learn and improve their accuracy over time.

Where is AI needed in the real world

Where is AI needed in the real world? 

Everywhere! One specific area that we’ll cover in this post is the insurance industry. It’s very old, and it relies on manual, time-consuming paperwork. Policies are also not tailored in order to meet every customer’s unique needs. AI can be implemented to design customer-centric policies in order to fit each client. 

The wealth of data the insurance industry generates is overwhelming. It needs AI and machine learning tools to unearth the underlying insights in their data that insurers are struggling to take advantage of.

AI has the potential to affect the insurance industry in multiple ways, from understanding risk appetite and premium leakage, to expense management, subrogation, litigation, fraud identification, sales, marketing, and operations.

How is AI being implemented in the insurance industry?

The insurance industry has already begun its venture into AI. Insurers have no other option but to embrace artificial intelligence and machine learning to remain competitive. There are many areas where insurers are adopting AI solutions, below are some notable examples:

  1. Fraud Prevention: Insurance companies lose billions of dollars a year to fraudulent claims. Artificial intelligence can help insurance organizations query the alleged events of an accident while processing claims. Machine learning algorithms (cluster analysis) can tap into unstructured and semi-structured data, such as claims notes and documents, as well as structured data, to identify potential fraud. 
  2. Lead Management: AI can assist insurers and salespeople in pointing out leads by extracting valuable insights from data. AI can personalize recommendations according to the buyer’s purchase history and potential spend for the salespeople, thereby helping the salespeople to interact more effectively with the buyers. 
  3. Intelligent Virtual Assistants: Chatbots using neural networks can be developed to understand and answer the bulk of customer queries over email, chat, and phone calls. This can free up significant time and resources for insurers, which they can deploy towards more profitable activities.
  4. Customer Retention: AI can look at a variety of data, including new data sources, to determine risk, which can be used to recommend the best offer that will most likely retain a valuable customer.
  5. Claims Processing: Claims processing includes multiple stages, including review, investigation, adjustment, and remittance or denial. Speed is critical to customer experience in these processes. Thanks to document capture technologies, businesses can rapidly handle large volumes of documents required for claims processing tasks, detect fraudulent claims, and check if claims fit regulations. 

Other applications include risk tolerance calculation and management, claims analysis, asset management, and consistent optimization of customer investments and insurance coverage. 

What is the future of AI in the insurance industry?

Companies in this space face numerous challenges. It’s a highly-competitive industry, especially when customers are able to easily compare competitors online. Unfortunately, it has suffered from a long period of underinvestment in new technologies. As insurance companies realize the benefits of AI, they will build upon the above use-cases and find new applications for providing an enhanced customer experience.

AI has the potential to transform the frustrating insurance experience for customers to something fast, on-demand, and more affordable. If insurers start applying AI technology to the abundant data they are sitting on, we will soon start to see more flexible insurance as insurers will be able to better understand what their customers want and need. AI will also make it easier for the customers to interact with the insurance companies, which will result in people being more likely to purchase.

Learn more about how Atrium has helped businesses in the insurance industry harness the power of AI and machine learning to achieve their goals