by By Choudhary Surya on May 06, 2021

Whether it is drawing personalized ratings or calculating risk per policy, data has played a crucial role in determining how the insurance industry functions. Fortunately, the advancements in technology have managed to scale with our data dependence and corresponding demand. Tools like artificial intelligence, deep learning, and machine learning in insurance are empowering agencies to boost operational efficiency, enhance customer service, and detect fraud efficiently. The rising popularity of InsurTech is proof of this trend.

Machine learning, in particular, is witnessing widespread adoption throughout the insurance sector. As per a PwC report , machine learning (including AI) features in the top 10 list of investment priorities set by CEOs. Clearly, it is not a phenomena to be missed. However, discovering avenues where you can introduce machine learning can get challenging. But that should not stop you from making it a part of your business operations.

Read on to know how you can tap into machine learning in insurance.

Use Cases of Machine Learning in Insurance

If you are looking for ways to incorporate machine learning in insurance but don’t know where to start, then we’ve got you covered. Here, we will be taking a look at some practical use cases where you can make machine learning an integral part of your operations:

Process Automation

Machine learning in insurance addresses two common challenges – ability to process high volumes of requests and maintaining quality while doing so. It can achieve this feat through process automation, which identifies redundancies and automates these tasks so that everything moves smoothly. It also reduces the dependence on humans, which bypasses any form of introducing errors.

Asset Analysis

Whether you offer home insurance or vehicular insurance, you would have to analyze the asset’s health before drafting an insurance policy. Machine learning in insurance can be useful in analyzing photos and videos taken of the asset to evaluate its condition. It can also calculate the intensity of the damage, if any, and the corresponding cost of repair. As a result, insurers no longer have to rely on physical inspections, which could cause inordinate delays.

Personalized Policies

Machine learning simplifies the insurance underwriting process by carrying out all the grunt work of profiling your customers. It collects data inputs on the state of the asset and customer behavior, while also carrying out risk assessment, to draft personalized policies. This policy personalization makes customers more willing to avail your services. At the same time, you will also be elevating the customer experience associated with your agency.

Targeted Marketing

Sales and marketing are another area where you can leverage personalization through machine learning to maximize gains. Whether you are dealing with new leads or re-engaging existing customers, you can tap into machine learning in insurance to create custom marketing strategies in consonance with the client requirements, preferences, habits, and lifestyle. You can also indulge in trigger-based events to communicate with your customers and nurture loyalty.

Fraud Detection and Prevention

Insurance fraud is the leading cause of revenue erosion. As such, insurance agencies are always on the lookout to find ways to avoid or mitigate fraud. The use of machine learning in insurance has revolutionized how insurers face this pressing issue. Machine learning adopts a data-driven approach to identify claims that could potentially be fraudulent and raise a flag against them. Similarly, it can also detect customers who may try to pull off insurance fraud and draw up a risk rating accordingly.

Conclusion

Machine learning in insurance is under constant evolution, leading to the discovery of new ways to make it an integral part of the insurance process. Moreover, it is accelerating business growth and streamlining workflows, which makes it well worth the hype. We can only anticipate the maturation and consolidation of this technology in the future, which means that it is best to get onboard right now! So, what are you waiting for? Contact us to know how you can introduce machine learning to the backbone of your insurance business.

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