How Unified Data is Disrupting the Insurance Industry
Of all the industries of the world, there are few more reliant on the power of data than the insurance industry.
Data is what makes insurance possible. Without individualized data points about customers, insurance companies wouldn’t have the ability to calculate the risk profiles on which their business depends.
The problem is, though, that for decades now, insurance companies haven’t had access to the data points that matter most when determining the probability that consumers will file claims, causing insurance products to be mispriced and inefficient.
At Unification, where I serve as Product Lead, we are creating technology that dramatically disrupts the way data is exchanged and accessed. For industries like insurance, which have long been ripe for disruption, this is gamechanging development.
Data fragmentation within the insurance industry
Until recently, access to datasets among businesses and between industries has been limited. As a result, insurance companies have been unable to incorporate many types data into their prediction models, even they indicate a very high likelihood of positive or negative outcomes, simply because they haven’t had access to it.
Example: Health Insurance
In an ideal world, insurance companies would be calculating health insurance rates based on an individual’s actual physical fitness, such as the amount of time they spend exercising or the health of their diet. Because this data has heretofore been inaccessible, however, insurance companies have had to rely on broad-stroke demographic information to make predictions about long-term health.
This is unfortunate, because while a customer’s age, gender, and location of residence may have some correlation to their likelihood of filing a claim, that data alone doesn’t paint a full picture of a customer’s health. The reliance on demographic data, rather than individualized data, is thus creating major inefficiency within insurance companies’ prediction models, and leading to higher prices for otherwise-healthy consumers.
Example: Car Insurance
Within the car insurance industry, lack of access to real-time data about individuals means that customers are charged based on similarly broad, demographically based categories, rather than their actions.
A 25-year-old male pays more for car insurance because of the statistical likelihood of a 25-year-old male having an accident, even if he drives less than five times per month and always stays below the speed limit. If companies could access his individualized data, they count price his car insurance based on his real risk profile, rather than the profiles of people who are presumed to be like him.
The emergence of individualized data profiles
Unified data is dramatically changing the insurance landscape. When insurance companies can purchase and incorporate data sets from a wide range of apps, they gain a much better sense of the overall risk profile of a specific individual. This allows companies to price their insurance based on a specific person’s actions and lifestyle, rather than abstract demographics alone.
Aiming to stay ahead of the trends, insurance companies have already been investing in more individualized data that will allow them to make better risk predictions. A number of companies have already started incorporating hundreds of non-medical data points into their prediction models, and this phenomenon is growing daily.
In order for insurance companies to readily make use of a wide variety of data points, however, it is necessary for them to be able to both find and purchase new data sets, as well as to have streamlined mechanisms for integrating each new data set with the others.
Unification & the end of data silos
Unification provides just such an opportunity for insurance companies to acquire the data sets necessary to improving the efficacy of their product.
In the third article of our series “Why Unified Data is Inevitable,” the Unification team dove into the methods that Unification is using to exchange new data sets more efficiently than was ever before possible.
Unification offers a two-pronged approach to support companies in utilizing data to improve customer experience:
- HAIKU, Unification’s C++-based smart contract protocol, seamlessly standardizes data sets within a wide variety of markers into a singular, unified format, making it easier for data sets from many different sources to be correlated against one another.
- BABEL, Unification’s user interface, offers a data marketplace for standardized data, where companies can both buy and sell data sets within the unified data format.
With Unification, insurance companies are able to acquire the data that they need to make better prediction algorithms and to incorporate it with very minimal human effort, skyrocketing their ability to more accurately predict risk and offer fairer rates to consumers.
The individualization of insurance
At present, insurance companies are already targeting customers based on personal characteristics, offering them better pricing if they can prove factors that lead to better outcomes, like their level of fitness (as shown in the ad below for Health IQ, for example.)
There are also a number of auto insurance companies utilizing individualized data to better price car insurance.
Metromile offers users a pay-per-mile model, while Drivewise by Allstate and Snapshot by Progressive incentivize users to attach a data-collection device to their vehicles and reward them for low-risk driving habits.
Certainly, personalized quotes based on individualized factors are where the future of insurance is heading, but several problems still exist.
At the moment, much of this data is self-reported with huge inefficiencies and possibility for error. Additionally, data collection often requires installation of proprietary devices that can’t be easily correlated with data collected by, say, a user’s smartphone or FitBit.
For instance, once someone tells Health IQ about their nine-minute mile, how can the insurance company verify without a shadow of a doubt that the information reported is accurate, and that they won’t abandon their runner’s lifestyle the next day and start indulging in daily Netflix and cheeseburgers instead?
How Unification affects the insurance industry
Unification can help to solve the myriad of challenges listed above in two ways:
- Better data access: We enable the insurance company to acquire verified, accurate data from other apps that are collecting personal information that may be useful in risk assessment.
- Dynamic contracts: We future-proof rates agreements so that as a user changes their lifestyle, their insurance rates are automatically updated accordingly.
Better data means more accurate rate assessments
Until recently, most data acquired by insurance companies was self-reported or at best a snapshot, prone to inaccuracy and unable to shift dynamically with changing conditions.
With Unification, insurance companies can purchase more robust data sets directly from other enterprises, ensuring up-to-date accuracy while respecting the privacy of the user themselves.
Example: Life Insurance
In the example of life insurance, Unification allows insurance companies to acquire data that helps them more accurately predict the likelihood that a given customer will die during the term of a policy, via health and other predictors.
There are several factors that make this a better choice for both insurance companies and end users, including:
- Data provides real proof
To take the above life insurance example, using Unification’s BABEL interface, an end user can provide proof that they can indeed run a nine-minute mile by consenting to share their Strava, Fitbit, and/or Google Health records with their insurance company.
- Rates can correspond with risk
In real time, their life insurance company can adjust their rate to accommodate the fact that they have a significantly lower chance of dying than someone who takes twenty minutes to run a mile.
- Better rates for users
The end user not only gets rewarded with UND, Unification’s utility token, for opting into the information sharing, they also save money because they are able to purchase a cheaper insurance policy than the one they were previously offered.
- Real-time rate adjustment
Additionally, because data is being collected continuously, the insurance company is able to keep updating the policy rate in real time, further lowering costs if the customer continues to do more exercise. Instead of being locked into an annual rate that doesn’t reflect changing lifestyle choices, users are actually incentivized to change their behavior in the short term to produce better health outcomes.
- Better sales pipeline
On the business’s side, with Unification, they now have access to a system that allows them to guarantee accurate assessments of risk profiles over the long term, while also being able to access data that could inform them of other products a customer might be interested. For example, if they purchase GPS data about a customer and discover that that person spends a significant amount of time traveling, they can offer to sell that user travel insurance as well.
Example: Auto Insurance
In the example of auto insurance, Unification enables insurance companies to gather data from multiple data sources in real time that allows them to properly calculate the risk of each driver, setting dynamic insurance rates that shift with risk.
This is a better choice for both insurance companies and end users for several reasons, including:
- User compensation for data sharing
Within Unification’s BABEL dashboard, the end user themselves elects to share their driving records and related data (such as education level, community affiliations, professions, or distance from office) with their insurance company. If they already use a tracker on their car from a service like Metromile, Drivewise, or Snapshot, then they can offer this data to their insurance company directly through BABEL. They are compensated with UND for authorizing the exchange.
- Access to more robust data sets
The insurance company is able to then take these multiple data sets and correlate them to produce a far more accurate and up-to-date assessment of their risk profile, so they can set rates accordingly. Safer drivers who present lower risk have this fact borne out via the data, leading to lower car insurance rates overall.
- Rates can update dynamically
The beauty of this system is the ability for rates to maintain a high degree of flexibility relative to the actual risks presented by insuring a specific user. Data tracking, as authorized by the user, can continue in perpetuity, allowing the rate to reflect real-life changes in a driver’s situation, so they’re never paying for insurance that they’re not using.
- Users maintain control
Meanwhile, the keys to the data exchange remain firmly in the users’ hands, so if at any time a user wishes to stop data exchange with their insurance, they are able to do so with a click (knowing that it may affect their ability to access the best rate).
A full-cycle data exchange that benefits all parties
Unification’s revolutionary model for data exchange is profound in the way that it creates a win/win situation that benefits businesses and consumers alike.
Key to way Unification’s exchange systems are structured is that fact that enterprises are offered the opportunity to be both buyer and seller of data in one unified marketplace — a scenario we call “full-cycle data exchange.”
In this example, insurance companies play both data consumer and data purchaser roles.
Benefits to insurance companies
- With an accessible way to acquire data in a highly efficient standardized format, insurance companies are able to adjust the end-user’s rate based on real time data like never before.
- elying on data rather than self reporting allows insurance companies to mitigate the risk of “bad actors” who lie about their driving history, exercise habits, etc.
- Lower rates are created by more accurate risk assessments, leading to happier customers who purchase more products.
- Being featured on the Unification marketplace provides them access to new, more qualified leads by being able to offer programs directly to users.
- Insurance companies generate data about their customers, including claims registered and payouts made. With access to a data marketplace, they can more easily monetize this data by selling it to other enterprises (with the user’s consent).
Benefits to end users
- Users are compensated directly in UND tokens for electing to share their data with their insurance company.
- Safe drivers and healthier people are able to access lower rates than were previously available, and these rates are automatically updated over time with little effort.
- The insurance company having access to more data about them allows end users to be presented products that are more relevant to their individual situation.
Learn more about Unification
If you’re interested in what we’re building at Unification, there are several ways to get learn more.
The best place to start is our Telegram group, where I and other members of the Unification team are present to help answer any questions you may have about the project.
More details can also be found on our website and our Medium publication.
If you’d like to go deep, I highly recommend you dive into our technical paper and white paper (both available on our website).
We’d love to hear your feedback.
