Insurance companies today know the value of digital technologies – these tools have transformed the industry across all facets of operations. Whether it be customer-facing portals or holistic dashboards for brokers, there’s no denying the impact of digital transformation on the insurance industry.
One area of insurance that is revolutionizing the way insurers do business is data science. Fueled by artificial intelligence (AI) – and its subcategories of machine learning (ML) and predictive analytics – data science is empowering insurance companies with concrete, actionable insights like never before.
These three tools in particular are helping to speed up and optimize a wide array of functionalities in the industry. AI, ML, and Predictive Analytics in insurance has helped streamline the way we process data, claims, and customers, and their impact will continue to be felt as its capabilities continue to expand. To understand and in turn capitalize on these tools, it’s best to understand how exactly AI, machine learning, and predictive analytics are changing the insurance landscape.
How AI is Impacting the Insurance Industry
When thinking of AI, it is imperative to remember that AI encompasses both machine learning and predictive analytics. Their capabilities empower AI to do what it does and vice versa.
The insurance space is a complex industry, but at a very high level, it can be broken down into five foundational business needs.
- Claims Processing & Customer Service
- New Business Sales
- Employee and Broker Retention
Each is impacted by the trio of technologies – AI, ML, and predictive analytics – in a multitude of ways. To understand the ways the insurance industry is changing, it’s best to examine how the technologies relate to the functions of the industry, rather than how the functions fit the technology.
AI & Predictive Analytics
Underwriting has traditionally been a slow process, as companies must do their due diligence processing and analyzing data before issuing policies. The use of AI and predictive analytics in insurance significantly speeds up this process, enabling insurers to process more data more efficiently and accurately.
Aside from the speed and efficiency with which predictive analytics can process data, the second most important impact it will have on the insurance industry is pricing strategies and risk selection. These technologies can comb through data from multiple sources, identify trends and risks, assess the risk potential for individual customers, and underwrite accordingly.
Beyond pricing and risk analysis, AI and predictive analytics in insurance can also help insurers:
- Extract insights from many data sources
- Automate demand analysis and therefore generate new product ideas
- Improve pricing, policy rating and personalization
AI & Machine Learning
Another antiquated system in the insurance industry is claims processing. The last thing customers want to do during a trying time – either with P&C insurance claims or life insurance claims – is jump through hoops to get their claim filed and processed. AI and ML are changing and improving that process by:
- Triaging claims
- Identifying outlier claims
- Automating where possible
First, triaging claims is becoming a frictionless process. Customers can use an app or virtual assistant powered by AI and ML to file claims, schedule inspections, upload photos of damage, audit the system, and communicate with the customer.
These “touchless” claims don’t require human intervention, and some claims can even be processed and paid out within the digital space. This drastically speeds up turnaround times, reducing operational costs and improving customer service and satisfaction.
Beyond servicing claims, AI and ML are uniquely capable of tracking and identifying patterns in claims to better identify instances of outlier claims and even fraud. Insurance fraud is a $40 billion dollar per year industry, making this capability crucial for insurers. Once potential fraud is detected, the internal dashboard can notify brokers to investigate.
AI & Machine Learning
Look at any industry today and you will see that the name of the game in sales is personalization. People want prompt, personal attention to their needs and inquiries, but they also want self-service capabilities. An insurer who can cater to all these demands will attract new business more quickly and easily.
Using data, AI and machine learning can process the mountains of data at their fingertips and help insurers offer best-fit policies and services to customers. Using these technologies, policies and insurance offerings can seem almost custom-made to each prospective customer, which they almost are, as they are driven by concrete data.
AI can also help brokers recommend coverage levels and policy rates based on historic customer relation and buying behavior data for each customer they encounter. No longer is it a learned skill for brokers, but a data-driven process that is only possible with AI and machine learning.
AI & Predictive Analytics
The power of AI and predictive analytics in insurance goes well beyond customer-facing tools and programs. In fact, these technologies are vital to attracting and keeping high-quality employees, an issue that plagues many insurance companies.
First, it empowers insurance brokers and employees with the tools and information they need to do their jobs properly, correctly, and efficiently. Comprehensive dashboards and data insights provide the visibility needed and the platform required for collaborative work within the organization.
Second, recruiting and training the insurance industry workforce is a costly endeavor. Today, companies can use the same AI technologies they use to gather insights on their customers to gather insights on their employees, helping to both retain their talent and make their teams more efficient. AI can be used to find the optimal learning path for each broker based on their behaviors, interests, and learning styles. These same analytics can also measure and track performance, job satisfaction, and even their potential to look elsewhere for employment.
AI & Machine Learning
Marketing in the insurance industry is big money business. In 2017, Geico, Progressive, and State Farm spent $1.4 billion, $622 million, and $522 million dollars on their marketing budgets, respectively. What if AI and machine learning could make those dollars go further and empower insurance companies to create more effective marketing campaigns.
Turns out, they can. Machine learning and data analytics are helping marketing teams gather numerous, precise insights about customers and customer behavior that weren’t possible before. This data allows them to better target demographic groups and hit customer segments more likely to convert.
Using AI and predictive analytics, insurers can then identify the most effective channels for delivering this marketing content. Consumer’s habits and their online presence are tracked and analyzed like never before, and insurance marketing returns are proving just how powerful that data
Insurance Technology & the Future
The true power of AI, machine learning, and predictive analytics to change the insurance industry is just starting to be felt. A report from PwC forecasts that down the road, these technologies will empower insurers to identify, assess, and underwrite emerging risks and identify new revenue sources automatically, with little human interference required, making insurance a potentially semi-automated industry.
Until this day comes, we have data science teams that are already building highly sophisticated insurance platforms powered by the intelligence of AI, ML, and predictive analytics. At Hitachi Solutions, our Data Science group builds custom models/cloud environment using the Microsoft platform and Azure cloud analytics. With these models, insurers can create robust data platforms with the capabilities and applications they need to stay competitive in this market. If you would like to learn more about how Hitachi Solutions can help with your customer insurance solutions, please reach out to our team.
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