Upwards of $170 billion of insurance premiums could be at risk over the next five years. The culprits? Poor claims experiences and process inefficiencies.
Challenges currently facing the insurance industry include growing pressure from new competitors, evolving types of risk (such as frequent, extreme weather events and cyber-risk), and heightened expectations from customers for more timely, relevant, and low-touch experiences.
Automation, artificial intelligence (AI), and data analytics based on machine learning can bring value across the entire insurance value chain. This includes anything from flagging fraudulent claims to damage assessment and loss estimation.
According to McKinsey, 10 to 55% of the tasks performed by major functions within insurance firms – including actuarial, claims, underwriting, finance, and operations – could be automated over the next decade.
Concerningly, however, it appears that wide-scale adoption of these technologies has been slow to date. Only about one-third of executives report that their firms are advanced in their use of these technologies.
Let’s take a closer look at the role and potential benefits of data analytics for insurance data analytics in the insurance ecosystem.
Spotlight On: Data Analytics in the Insurance Industry
Fuel for the Lead Generation Engine
Data analytics-enabled tools like CRM systems enable insurance firms to extract valuable data & insights from customizable reports that track the entire customer journey, right from search through to conversion.
These tools are invaluable in helping them understand their customers’ and prospects’ behaviors. They also empower marketing teams to target the right messages to warm up the most promising leads.
Fairer and More Accurate Pricing
A longstanding challenge faced by insurance companies is accurately pricing their premiums for each policyholder. Too often, customers face unfair premium amounts for no mistake of their own.
To ensure they remain fair and competitive in today’s marketplace, more insurers are investing in new methodologies that use insurance analytics to granularly track and analyze individual policyholders’ behaviors, ultimately resulting in more accurate premiums being set.
A Hassle-free Claims Experience
A new Accenture report reveals that increasingly, dissatisfaction with the claims experience is driving customers to switch insurers. According to the report:
- 31% of the claimants haven’t been fully satisfied with their home and auto insurance claims-handling experiences over the past two years.
- Of these, 60% cited settlement speed issues, and 45% expressed frustration with the closing process.
- Nearly one-third of dissatisfied policyholders said they had switched carriers in the past two years, with a further 47% saying it’s something they’re considering.
Data analytics helps address the issue of poor service and lengthy response times, as it solves many of the problems associated with the manual processing of customer questions and information.
Superior Self-service
Data analytics is also an enabler of customer self-service, which reduces time-to-service and cost-to-service. The power of insurance analytics software also allows you to make faster, more relevant recommendations to customers when they’re buying or renewing their policies online.
In addition, providing a dedicated portal to your customers where they can manage their own policies means your internal resources have an ample amount of time to focus on other key issues within your business.
Stopping Fraud in its Tracks
The Coalition of Insurance Fraud estimates that $80 billion is lost every year from fraudulent claims in the U.S. alone. Additionally, fraud makes up 5–10% of claims costs for insurers in the U.S. and Canada.
Using predictive data analytics, carriers can identify and prevent potential fraud before it happens or retroactively pursue corrective measures.
Proactive Business Risk Mitigation
The volumes of data now available for advanced analytics means it’s possible for insurers to base short and long-term risk assessments on fact as opposed to conjecture.
Data analytics allows them to predict eventualities that could disrupt operations and proactively plug revenue leakages that could be eating into profits.
A Smarter Response to Climate Change
Data analytics can also help insurers pre-empt potential unforeseen losses stemming from extreme weather events such as hurricanes, earthquakes, wildfires, flooding, and tornadoes/hail. These incidents are becoming ever-more frequent in the U.S. and across the globe.
Today, we’re seeing exciting advancements in analytics technologies that can perform a more granular analysis of climate-related risk characteristics, especially geo-spacial risk.
Final Thoughts
Data analytics holds significant potential to build more competitive insurance capability, and Insuresoft is taking the lead.
Our Diamond Platform gives you the power to accelerate and scale across distribution and engagement channels – with intelligent, data-driven, human-centered solutions that face forward.
It’s an all-in-one enterprise software solution ideal for both personal and commercial lines, combining core policy processing, digital engagement, and intelligent data to advance your mission.
Contact us today to find out more about our platform.
