How the Insurance Industry Can Use Business Intelligence
May 13, 2021
Gone are the days where business intelligence was synonymous with guesswork and the gut instincts of those in positions of power. These days, massive data gathering is standard for anyone who logs into an account online, uses a digital portal, or carries a smartphone in their pocket.
Just gathering the data isn’t an end in itself – it’s more about the ways businesses can or should use the data at their disposal.
The business intelligence origin story
Business data means having access to a lot of information, but business intelligence (BI) happens when that data meets service, this marriage can give industry decision-makers insight into why and how to leverage the data.
AgentSync is built on the premise of integrating data and services to unlock new opportunities and potential in the industry.
The insurance industry often gets a bad rap for being behind the times – at least, technologically speaking – but it’s actually one of the oldest players in the business intelligence space. If BI is data in action, then there is no better early example than actuarial history, which is the data science behind underwriting.
From early Roman annuity pricing in the 200s to the late 1600s, insurers worked with patchy data to make their models work. When Edmond Halley developed the first reliable mortality model in 1693 by mining statistics from a small town’s burial registry, the insurance industry’s use of BI got an upgrade, which only escalated as technology and industrial communications have made it easier to get specific and have larger sample sizes than ever.
From traditional metrics, such as regional mortality or disability rates and causes, to more modern tracking such as driving apps, smartwatches, and feedback from home security systems, the industry has access to exponential reporting.
Case in point, in 2018, a single driverless car produced 30 terabytes of data – “3,000 times the scope of Twitter’s daily data.” Yet, how much of that data is worth keeping and storing? How much of it is useful? A human person, or even a whole staff of them, cannot process that amount of information and mine it for relevance on an ongoing basis.
Now, with predictive analytics and artificial intelligence (AI) software taking hold, there are more ways to turn raw information into true intelligence, to help companies in every industry decipher what is worth tracking and cut through the noise.
New tech presents new use cases
As the insurance industry begins to really make use of these BI digital tools, there are a few areas that are ripe for transformation.
- Underwriting: Just as the first mortality tables and the development of actuarial science have driven more accurate underwriting, using BI to assess risk and plug into existing probability calculations is an obvious application of the predictive analytics available today.
- Claims payout: Insurance data analytics can speed up claims payouts and prevent fraud by flagging outlandish or unusually frequent claims. This is a boon to both customer service and everyone’s bottom line – fraudulent or inflated claims present a risk to the industry, and everyone pays for this risk in higher premiums and a lower bottom line. By reducing fraud, all the honest actors in the claims process have the opportunity to keep more money in their pockets.
- Mergers and acquisitions: The insurance industry is staying strong on M&As, and using smart tools can make it easier to evaluate which businesses or insurtechs to partner with, which are worth acquisition, and which to avoid.
- Service: Using AI, more insurance businesses are implementing self-service portals and 24-hour chatbots that can answer frequently asked questions with the cadence of a human using predictive text.
- Efficiency and growth: Using data-based decision-making, insurance businesses can transform processes to be more efficient and less hands-on and analyze which industry sectors are ripe for growth. Imagine being able to spot low-hanging (read: low-cost) fruit for your company’s expansion based on what state licenses or lines of authority your existing producers hold. Or seeing who your biggest competitors are – and which ones are vulnerable in your field.
With great power comes great (insurance) responsibility
The speed at which BI has the ability to transform insurance companies individually as well as the insurance industry as a whole has the potential for high highs, but also carries the possibility of low lows.
For instance, consider the ability of underwriters to target risks to specific neighborhoods. If you live in a neighborhood with lower risk, your personal property insurance rates could be lower – who doesn’t like lower rates? But, conversely, the same system of data use may have just made it much harder to get affordable insurance for those who live in neighborhoods that are historically disenfranchised by poverty or over-policing.
Considering how to pursue insurance innovations that are just and ethical adds a layer of complexity to BI. To get ahead of harmful use cases, the National Association of Insurance Commissioners released guidelines for AI best practices in late 2020.
The principles their recommendations adhere to are the FACTS:
- Fair and Ethical – don’t use AI in a way that deceives or causes harm to users
- Accountable – take responsibility for using AI and anticipate its impact
- Compliant – always follow the rules and regulations of every jurisdiction in which you deploy this technology
- Transparent – do not obfuscate the origins of your information or your intentions, and retain the data that underpins your assumptions
- Safe and Secure – don’t use BI in a way that exposes anyone’s personal or sensitive data to abuse
As insurtechs and legacy businesses alike use and develop BI to stay competitive and relevant, these principles and practices will continue to evolve, as will the regulatory environment that governs them.
AgentSync was developed as a way to responsibly merge growth and compliance, so the development of BI solutions is near and dear to our mission. Check out on of our demos to see how AgentSync can help.