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How Is Deep Learning Revolutionizing the Insurance Industry?

The insurance industry is being transformed through the use of artificial intelligence. The coronavirus pandemic has also had a deep impact on the insurance sector as it has on many other industries. Even though insurers have not escaped the impact of Covid-19, they have responded quickly. In a matter of hours and days, insurance carriers had to adapt to a remote form of working.  One way in which the insurance industry responded to the pandemic was by making use of deep learning services and data science services in general. 

The insurance industry routinely makes use of large data sets and is based on rules that are often centuries old. Most carriers make use of data that exists in silos. This data is in the form of images, text, and voice and data science services are now allowing carriers to extract and integrate this data into data lakes. Then, deep learning services can be used to automate processes that previously required human intervention and judgment.

Here, we look at some ways in which deep learning services are making a big impact on the insurance industry.

  • Fraud Detection

Fraud detection is an important area where machine learning is being used in the insurance industry. Given the rise in the number of payment channels, there has been a corresponding rise in the number of global transactions. Machine learning and deep learning algorithms are being used for automatic fraud detection that is significantly faster and more reliable than the traditional forms of using historic rules combined with human assessments. Deep learning can distinguish between fraudulent and normal behavior and adapts over time when fed with increasingly more data. Thus, the true power of deep learning over traditional analysis methods is revealed. It can identify fraud that is not only identical to existing patterns but also those that are similar. New types of fraud can also be identified robustly. However, working with an experienced provider of deep learning services is always recommended.

  • Managing Claims

Machine and deep learning can be used to automate the claims management process so that it is much faster than the old ways. Some data suggest that the use of deep learning by insurance companies will reduce the number of people working on claims management by 70% to 90% in 2030, which is a staggering number. Data science services can shrink the claims processing time from days to hours while also increasing customer satisfaction and fostering enhanced internal efficiency. Many carriers are already using chatbots to interact with customers, and this methodology will only proliferate more as the technology matures and becomes increasingly more sophisticated. In terms of claims management, deep learning is already being experimented with to assess the total loss and efficiently process the insurance claim. It is only a matter of time before this technology completely removes the need for human intervention.

  • More Accurate Pricing

The insurance industry is highly competitive, and providers are bending over backward to provide the best rates to their clients. Machine learning and deep learning services are also being used by insurance carriers to evaluate customer risk based on past behavior. In this way, insurance companies are optimizing the pricing plans for every customer segment. Sophisticated deep learning algorithms are being used to assess and quantify the cost vs. risk based on various factors including the past behavioral patterns of each customer segment. When this is done, more accurate pricing can be provided to each customer segment. Customers are also happier when they receive more accurate rates from their carriers. Further, deep learning models can learn from large datasets of policyholder data to calculate the risk premium in real-time. This enables firms that employ deep learning and machine learning to offer much more competitive pricing to their customers, which results in enhanced satisfaction.

  • Customer Analytics

Deep learning, together with predictive analytics and machine learning, is also being employed to reduce churn and enhance customer retention in the insurance industry. Insurance carriers are increasingly turning to deep learning models to identify and maximize customer loyalty related to retention, purchase, and advocacy behavior. Based on the output of deep learning models, insurance providers are developing more sophisticated sales and marketing programs with targeted products and special offers for high-value customers.


Deep learning is making inroads into the insurance sector as it is doing in many other industries. However, to fully capitalize on all the benefits of deep learning, the insurance sector will need to develop targeted strategies and preferably work with specialized providers of data science services. When formulating a strategy, firms should ensure that they train their models with large volumes of accurate and human-annotated data. When the deep learning model is trained on high-quality data, the solutions and output it providers will also be more reliable and robust. This can enable your firm to leverage deep insights to improve productivity and customer satisfaction.

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