Harnessing Machine Learning for Next-Gen Insurance Pricing: Insights by Lumnion


Harnessing Machine Learning for Next-Gen Insurance Pricing: Insights by Lumnion

With positive advances in ArtificialIntelligence (AI) and Machine Learning (ML) technologies, it is possible toaccess powerful tools that can automate data preparation, optimize pricingcapabilities, and manage risks. AI-drivenpricing is crucial for risk management and making informed decisionsfor pricing.

Harnessing Machine Learning for Next-GenInsurance Pricing: Insights by Lumnion

With positive advancesin Artificial Intelligence (AI) and Machine Learning (ML) technologies, it ispossible to access powerful tools that can automate data preparation, optimizepricing capabilities, and manage risks. AI-driven pricing is crucial for risk management and makinginformed decisions for pricing.

The insuring pricingplatform provided by Lumnion is a platform that automates insurance data preparation, with moreprecise risk pricing, impact analysis and dynamic pricing and can beconnected to any core system.

The Role of Machine Learning in RevolutionizingInsurance Pricing

In the insuranceindustry, pricing processes have remained largely unchanged for the past threedecades. However, the advent of machine learning (ML) algorithms has opened upnew opportunities to revolutionize insurance pricing by helping actuaries and pricingteams make better decisions, faster.

Machine learning is atransformative force in the insurance industry, particularly in the context ofpricing.

Actuaries face amultitude of challenges in delivering the most accurate pricing that takes intoaccount the inherent unpredictability of risk and the nuances of historicaldata related to claims. These include:

•          Cumbersome data preparation

•          Utilizing black box ML algorithms

•          IT dependency

All of these are usuallykey elements of the price modelling process.

 ML-driven portfoliomanagement tools enable pricing experts to identify profitable ornon-profitable segments in a timely manner, allowing them to take action inreal time.

These pricing-relatedissues are of significant consequence. Insurance companies experience poorcustomer retention rates (up to 9%), quantifiable time loss, and higher lossratios in new business of up to 5%.

Predictive Analytics: Driving Precision inInsurance Pricing

Predictive analytics,powered by machine learning, is at the forefront of this revolution. Byleveraging advanced algorithms, insurers can forecast future trends andbehaviors with remarkable accuracy. This predictive capability is crucial fordynamic pricing models, which adjust premiums in real-time based on evolvingrisk assessments and market conditions.

For example, machinelearning models can analyze customer data, claims history, and external factorslike economic indicators and weather patterns to predict the likelihood offuture claims. This enables insurers to set premiums that are not only fair butalso optimized for profitability. Moreover, predictive analytics can identifypotential high-risk clients before they even file a claim, allowing insurers totake proactive measures to mitigate risk.

Lumnion’s pricingplatform also allows companies to optimize pricing on a personal level with theuse of external data, getting 360 view of the customer.  With its integrated Pricing Engine, Lumnioncan push any commercial price decision into the market instantly, allowing forfaster time to market given today’s rapidly changing market conditions whichcan help insurance companies make improvements to strike the delicate balancebetween risk exposure and revenue generation.

Unlocking the Power of Data Science forInsurance Sector Growth

Data science is thebackbone of modern machine learning applications in insurance. By harnessingthe power of real-time big data, insurers can gain unprecedented insights intomarket trends, customer preferences, and emerging risks. This wealth of informationsupports more informed decision-making and strategic planning.

Insurers improve lossforecasting, enable precise risk pricing with machine learning algorithms,leverage better data, and obtain a complete customer profile. It can improvepricing accuracy and help us better serve customers. Advanced technologies, predictive analytics, and predictive modeling influencedistribution and underwriting by pricing, purchasing, and linking policies inreal time. Those who embrace machine learning as an operational and commercialenabler in the insurance industry will gain a first-mover advantage and becomepioneers in this rapidly evolving market.

Actuaries and pricingexperts spend too many hours on administrative and data-entry duties. In fact,a recent survey indicated that actuaries spend more than 50% of their time ondata issues. But with the help of new ML technologies, actuaries can forgetabout non-core tasks. They can focus on where they’re needed the most:performing complicated analysis, and scenarios that require human judgment andexpertise.

The integration ofmachine learning into the insurance industry is not merely an exercise inenhancing existing processes; it is also an opportunity for innovation.Insurers that effectively leverage data science and machine learning candevelop new products and services tailored to the evolving needs of theircustomers, thereby positioning themselves as leaders in the market.

Building Competitive Advantage with Lumnion'sAI-Driven Pricing Strategies

Lumnion’s open platformallows the use of all widely accepted Machine Learning Algorithms including XGBoost, 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 theblack box machine learning algorithm transparent, so that they becomeoperationally usable. The ML-based consulting module helps actuaries simplifyoperational work and significantly improves model results.

Lumnion developsAI-driven pricing platforms for the non-life and Health Insurance Industry.Discover the benefits of Lumnion and how it seamlessly integrates AI solutions.


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