In the insurance industry, pricing processes have remained largely unchanged for the past three decades. However, the emergence of machine learning (ML) algorithms has opened new possibilities for revolutionizing insurance pricing, helping actuaries and pricing teams to make better decisions, faster.
Actuaries face plenty of difficulties in delivering the most accurate pricing that consider the excess of risk and data about past claims. These include:
- Cumbersome data preparation
- Utilizing black box ML algorithms
- IT dependency
All of these are usually key elements of the price modeling process.
But the insurance sector is undergoing a significant transformation, driven by advancements in technology and the increasing availability of data. At the heart of this transformation is machine learning, a powerful tool that is revolutionizing both insurance pricing and risk modeling. By leveraging machine learning algorithms, insurers can analyze vast datasets to identify patterns and trends that were previously undetectable, leading to more accurate risk assessments and pricing strategies. Using ML driven portfolio management tools however allows pricing experts to identify profitable or non-profitable segments in a timely manner and take action in real time. Artificial intelligence (AI) and ML algorithms are transforming the insurance underwriting process by increasing its efficiency and accuracy. Insurers can customize policies for each customer’s needs and move to dynamic pricing, by utilizing predictive analytics to better understand risk and provide real-time data for quotes on demand.
Below are some of the benefits of machine learning that insurers can leverage today.
Improve loss prediction
Traditionally, pricing relied on manual data preparation and mostly generalized linear models (GLM) for risk modeling. But with advancements in modeling techniques, machine learning algorithms now offer the potential to significantly improve loss prediction. By capturing patterns and correlations in vast datasets, insurers can make more accurate predictions, resulting in enhanced risk pricing strategies.
Need for transparency in machine learning
One of the challenges in adopting machine learning algorithms is their black box nature, which keeps from transparency. However, if you can solve this problem and deliver transparency through revealing the variables used, identifying their significance, and even their interactions, then you will be able to empower actuaries to gain insights and make informed decisions, enabling more precise and transparent risk pricing.
Inform with better data
In today’s rapidly changing world, agility is crucial. Machine learning and new tech platforms allow for insurers to work with real-time data and conduct analytics, enabling prompt action and behavior correction. Precise monitoring of portfolios at a micro-segment level facilitates informed decision-making and ensures effective portfolio management.
The 360° view of the customer
To optimize pricing, insurers must obtain a comprehensive understanding of their customers. Incorporating external non-insurance data alongside insurance data provides a 360° view of the customer. This results in superior risk pricing and commercial pricing determination. This approach can even be extended to personalized behavioral pricing, tailoring premiums based on individual behaviors and circumstances.
An innovative insurance approach is a privilege that will always keep you ahead of your competitors. Lumnion has a team of experts from software development, ML Algorithms and modeling, and the insurance industry. This team ensures maximum efficiency from the platform by providing guidance and support to insurance companies.
Lumnion provides a unique end to end platform that can connect to any core system, automating data preparation, with more precise risk pricing, impact analysis and dynamic pricing with the use of Artificial Intelligence and Machine Learning
In the platform, Lumnion allows actuaries to model risk in all algorithms and compare them side by side with the same data set. Moreover, Lumnion has also developed its own methodology to make results of any of these black box machine learning algorithms transparent, so that they become operationally usable. The results of any of the ML algorithms are opened up, showing variables to be used, their significance, and interactions with multiple dimensions. The ML based advisory module helps relieve actuaries from operational work and improves model results dramatically providing advice on the portfolio on a real time basis. 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. With its integrated Pricing Engine, Lumnion can push any commercial price decision into the market instantly, allowing for faster time to market given today’s rapidly changing market conditions.
On top of GAM/GLM, all additional ML algorithms of GBM, Random Forest and Decision Trees are also available and free on our platform. While using machine learning algorithms, you can also enjoy the use of Lumnion’s own methodology to make results of any of these black box algorithms transparent. Your data can be easily extracted from the system with just one click in the desired format, ready for analysis and modeling.
Your risk modeling and data preparation are all for FREE now with Lumnion.
Contact Lumnion here, to see how the platform can help your business gain a competitive advantage in the insurance industry.
