How AI is being used in the insurance industry?

Use of AI in the insurance industry
Artificial intelligence (AI) has revolutionized insurance pricing by enhancing various aspects of the pricing process. AI enables insurers assess risk, detect fraud, reduce human error in the application process, advanced data analysis, personalize pricing based on individual risk profiles. Furthermore, by using AI, insurers can save time, reduce costs, improve customer experience, and increase profitability.

In the field of claims;
In recent years, especially with image processing technologies, both in preventing fraud and determining some damage amounts. And also ai helps automating the claim process while maintaining the payment accurate.
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In the field of CRM;
In line with the data obtained with text to speech, speech to text features in terms of customer satisfaction, in terms of customer returns, satisfaction, areas they want to focus on, areas where they seek solutions.
In the field of Underwriting;

With advanced analytics and ml algorithms it is easier to identify the risks of the policy, determine anomalies in portfolios and deciding the direction of actions to manage the portfolio. In the pricing actuary field, more advanced AI algorithms are used to calculate the risk coefficients building risk models and tariffs.
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In insurance, the old way of building risk models for pricing starts with manually preparation of the data which is a complex process and usually contains calculation errors. When data is prepared, most of the insurance companies determine risk coefficients with basic algorithms and in an intuitive way and few companies are using only Generalized Linear Modelling (GLM) for risk modelling.  Time to market of any price change is also problematic as mostly it needs manual intervention, sometimes even requiring hard coded changes in the core systems. On top of that, many companies also lack the data and knowledge to move into behavioral pricing from only risk-based pricing. This manual processes and lack of capable platforms may cost companies lots of money and customer dissatisfaction.
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By using machine learning and artificial intelligence, you can make your risk analysis more accurate and sharper. Machine learning can also help you in commercial decisions by simulating a decision you will make, predicting the outcome in your portfolio, and then deciding whether to take that decision.
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With the use of Artificial Intelligence and Machine Learning, Lumnion provides a unique end to end platform that can connect to any core system, automating model data preparation, with more precise risk pricing, impact analysis and dynamic pricing.
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Lumnion’s open platform allows the use of all widely accepted Machine Learning Algorithms including XG Boost, Random Forest, Decision Tree as well as GLM and GAM for risk modelling. Moreover, Lumnion has also developed its own methodology to make any of the black box machine learning algorithm transparent, so that they become operationally usable.
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The ML based advisory module helps relieve actuaries from operational work and improves model results dramatically by providing real time advice on the portfolio.

Lumnion’s pricing platform also allows companies to optimize pricing on a personal level with the use of external data, getting 360 view of the customer.

Challenges and Considerations
Introducing AI brings many advantages, such as improved efficiency and accuracy in operations, but raises concerns about privacy issues, data security, and algorithm bias. These are just some of the ethical concerns that matter in building honest AI insurance prices. Ethical consideration will reduce the risks of adopting AI and provide an open, equitable premium platform.
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How Lumnion is revolutionizing the process of insurance pricing?
Lumnion's AI-driven insurance Pricing Platform that takes care of data preparation, risk modeling, commercial optimization, and behavioral pricing uses all widely accepted Machine Learning Algorithms, including XG Boost, Random Forest, Decision Tree, as well as GLM, and GAM for risk modeling. Moreover, Lumnion has also developed its own methodology to make the results of the black box machine learning algorithms transparent so that they become operationally usable instantly. The results of any of the ML algorithms are opened, showing variables to be used, their significance, and interactions with multiple dimensions. Instantly compare and contrast all the models built in the platform and see the results by variable and also on the country map which dynamically adapts with the change done in the models and analysis. Multi-dimensional analysis can be done in an integrated business intelligence / dashboard screen to analyze in depth. With its integrated Rule & Rating Engine, Lumnion also allows for seamless time to market for any commercial price decisions. Additionally, Lumnion's platform enables the optimization of pricing on a personal level using external data, getting 360 views of the customer. Our platform is fully integrated into core systems with APIs and is cloud-enabled.
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Conclusion
AI and its related technologies will have a seismic impact on all aspects of the insurance industry, from distribution to underwriting and pricing to claims. However, it's important to note that AI in insurance pricing also raises ethical and regulatory considerations, especially regarding data privacy, transparency in decision-making, and potential biases in algorithms.
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Lumnion wants to revolutionize the insurance pricing process with the use of groundbreaking technologies in ML and AI through its state-of-the-art AI based end-to-end pricing platform for the Insurance Industry.