AI in the Insurance Industry- Comprehensive Use Cases

3 min readApr 12, 2020

Artificial Intelligence (AI) has been the buzzword for a few years now, showing its substance across various business verticals by providing automated environments, increased productivity and thus, digital transformation.

The Insurance Industry specifically has a lot to gain from investing in AI-enabled technology since the fundamentals of insurance is about finding patterns in historical data and predicting an outcome, what AI is popularly known to do. Further, the Insurance Industry still runs on outdated data processes that are data and time-intensive and has not yet leveraged new technologies for process automation.

  1. Tapping into the potential customers at the right time
  2. Providing the right set of products/services that meets customer requirements
  3. Promising hassle-free claim support to customers

Why should the Insurance Industry adopt AI?

While most insurers have already been leveraging advanced analytics on structured data, they can also analyze unstructured data (images and videos), with the advent of AI. Convolutional neural networks and other cognitive technologies can be used for image, voice, and unstructured text processing that can be applied in a wide range of applications in the Insurance Industry.

Better predictability can be achieved with the ability of machines to learn patterns based on historical data. Another interesting thing about AI is its capability to process language to identify intent and carry out human-like interactions.

All these competencies have made AI a cornerstone of the digital transformation strategy for many insurance companies. Several use cases for AI have emerged that can be leveraged to solve the many problems that insurers face.

Use Case for AI in the insurance Industry:

Formulating Insurance Policies Within Minutes — Advanced image analytics allows for quick analysis of photos (selfies included), to determine parameters like age, BMI, habits, etc. that are important in the perspective of life insurance. These parameters can help determine if medical underwriting is required or not. Insurers can provide an instant quote and formulate policies within minutes if underwriting is not required.

Zero Touch Claims — Advanced image analytics can be applied in Property and Casualty Insurance to analyze images of cars in accidents, determine parameters, and assess the replacement costs. Evolving algorithms can accurately estimate the extent of damage and automate the claims evaluation process within minutes, without any human interaction.

Underwriter shaves the tedious and error-prone job of dealing with multiple pages of unstructured documents and extracting information from them for making business decisions. AI, Machine Learning, and deep learning can help in extracting information from these documents, align it to common vocabulary, and make information easily accessible through a search engine or virtual assistants. Underwriting is thus reduced to an automated process that lasts about a few seconds.

Incoming data received from brokers is most often a cause of concern for insurers. It comes in a variety of formats, without standardization, and requires a lot of people to convert the data to a standard format. Only if the data is mapped accurately can the submission be processed. AI displays high potential here, enabling insurers to reduce inefficiencies in processes. Machines can learn patterns and automatically map new submissions. AI can also improve data quality by detecting gaps in incoming data and addressing them.

With advanced algorithms, insurance claims can be largely automated, enabling insurers to achieve dramatic levels of efficiency and accuracy, reducing processing times from days to hours or minutes. Data-capture technologies including IoT sensors replace manual methods. Claims triage and request for repair services can also be triggered automatically. Evaluation of the validity of a claim is also a much easier task for insurers.

Lengthy documents and complex policies often leave customers confused and daunted about insurance policies. They have questions, expect almost instantaneous responses to their problems and so, 24×7 support is mandatory. Chatbots, developed from Natural Language Processing (NLP) capabilities of AI, serve as Virtual Agents that can answer most customer service requests and questions. These chatbots can also transfer certain requests to human agents if the requests are not in their domain.

AI will soon be deeply integrated into the Insurance Industry. Insurance Companies and Insurers must thus position themselves to respond to the changing landscape.

While digital transformation is probably already on your cards, are you focussing on low code app development that will truly make this transformation seamless?

Find out how you can rapidly develop enterprise applications and adopt AI!