Insurers need to re-think their data architecture to leverage AI. Source: Shutterstock

Insurers need to re-think their data architecture to leverage AI. Source: Shutterstock

Insurers must re-think their data architecture to thrive in the digital age

EVEN BEFORE the digital era, insurance companies leverage data to build their business.

Data allowed the industry to build its underwriting models, develop new products, process claims, mitigate customer risks, and even attract and retain clients.

It’s why the industry is beginning to embrace digital — given the potential that technology holds when it comes to crunching numbers and making sense of data, faster.

In 2018, insurance giant Chubb spent more than US$1 billion on digital technology and is pushing towards the use of big data across functions.

Truth be told, the nature of data is evolving rapidly. The sheer variety, volume, and speed with which data can be collected and made available are impressive, and ultimately, increases the value of data.

If leveraged wisely, data can help players in the insurance industry leapfrog ahead of the competition, reduce costs, and delight customers — all at the same time.

However, simply possessing a massive amount of data isn’t enough. In fact, data is often underutilized in most companies.

According to a recent report, only 25 percent of insurers have achieved digital maturity, while the other 75 percent are adopting a ‘wait and see’ approach towards digital technologies. The latter group needs to wake up and realize the potential that technology offers.

Speaking more specifically about the insurance industry, the underutilization of data is often a result of poor data management within the organization. The first step to unlocking value in data, therefore, simply needs insurance companies to build a stronger data foundation.

Re-thinking data architecture is key

Changing the way data is approached, analyzed, and consolidated should involve the entire organization, and not be limited to technology teams.

There should be a shift from the traditional ‘one-size-fits-all’ model to one that is flexible and tailored specifically to the changing needs of the company.

Building an efficient data architecture that involves all teams can help sift through data quickly and deliver key sets of data to analytics and artificial intelligence (AI) teams to produce valuable information.

Further, good data architecture can feed into an efficient data management system helping the insurance company make sense of the large amounts of unstructured data that they tap into every now and then.

When the data architecture is right, AI can be leveraged to make data directly available to relevant people across the organization quickly and dynamically After all, in the digital age, insights should not be compartmentalized.

Instead, insights should be delivered on a standardized platform, streamlined, and accessible to those who need it, and in a format that is easily understandable. This saves time, money, and allows data to be rapidly tapped into when formulating strategies.

While the insurance industry hasn’t changed much for decades, the next few years are expected to bring unprecedented change — driven by the needs and demands of consumers living in a digital-first ecosystem.

By delivering insights at scale, the industry can maximize the value of data, leveraging it for a variety of use cases. Insurance companies that re-think their data architecture can definitely get in a good position when it comes to leveraging data, and prepare for smarter, more intelligent decision making.