Written by Yusuf Gulamhussain, Chief Technology Officer at Systech
The mantra “if it’s not broken, don’t fix it,” is an inherently problematic mindset in the insurance space.
The insurance industry has consistently dragged their feet regarding the digitization of their business model. Historically, they have been heavily dependent on physical documents and paperwork, with a death grip on their legacy model (with most traditional insurers in business for 100+ years). While there’s something to be said for playing to your strengths, this mentality is inherently disadvantageous, and is largely responsible for the lack of data analytic progress in their prospective field. At a snapshot, insurance companies have failed to make changes due to the comfortability and culture of their legacy models, and the general satisfaction of their customers dealing with this model.
COVID-19 devastated many industries. While insurance wasn’t the worst hit, it highlighted the urgency to embrace digital transformation. Heavily reliant a on-premises and a paperwork culture, they were wildly unprepared. COVID was a wakeup call to stop procrastinating, and to find a more tenable business model. Big or small, every business had no choice but to go digital. Physical interaction vanished in what felt like overnight. Since nothing was in person anymore, companies had no choice but to push through the pre-COVID hesitation to modernize.
The first step was investing in technology and innovation. These changes played a key role in the potential for data and analytics to make an impact within the enterprise. Why? Without digitizing over a century’s worth of paperwork, the ability to apply data and analytics would not be possible. No data means no actionable insights. Once digitized, companies could begin to provide a better customer experience, optimize operations, and better address business objectives.
Perhaps the most meaningful development was the ability to apply Machine Learning (ML) at scale. In risk assessment and fraud detection, the two critical aspects of an Insurance business, machine learning will play a vital role. Modern technology coupled with advanced algorithms, applied at scale on vast data assets will drive the next-gen Insurance ecosystem. At the core of this new business model is Customer Experience. The ability to effectively engage throughout the customer lifecycle will be the difference between great companies and good ones or perhaps between the ones standing till and those fallen off the chart.
Going forward, we are going to see data analytics drive the framework of all successful businesses. In light of the impact COVID-19, companies have started to lay the foundation for the digitization and modernization. Those with some fluency in data analytics suffered less than those who had failed to digitize beforehand. Many businesses that had never considered the consequences will make infrastructural changes to ensure that this never happens again, should another pandemic knock on their door.
How can we prepare for the next major global event? How can data analytics help companies stay adaptive? How can we stay informed on what’s going on within our enterprise, and the fallout with my customers? These are all questions that can be answered through the application of data analytics.
As companies become more mature in their data analytics, there is empirical evidence to suggest that their advantage over their competitors increases dramatically. The more that’s invested, the better position they will be in.
It is for this reason that insurance was found to be one of lowest performing industries throughout the duration of COVID. This is because companies that relied on data analytics and digitization saw profits go through the roof because they were able to address the market when the global pandemic hit. Insurance companies, however, had a more difficult time since they lacked the infrastructure to prepare for a disaster of this magnitude.
Whether we like it or not, data analytics is at the heart of all adaptative strategies and innovation. The better a company maximizes their data, the more likely they are to adjust to the twists and turns of a rapidly changing world. The longer they delay, the more likely they are to pay in the long term. The ability to capture the loyalty of one’s customers, and use data to generate actionable insights, will set companies apart from their competition.
In the midst of a global pandemic, it’s difficult to remain a visionary in a sea of chaos. While it may seem counterintuitive, insurance companies can benefit greatly from the same logic they employ when they appeal to their customers: ‘the best time to prepare is when times are good.
The Systech Solutions, Inc. Blog Series is designed to showcase ongoing innovations in the data and analytics space. If you have any suggestions for an upcoming article, or would like to volunteer to be interviewed, please contact Olivia Klayman at oliviak@systechusa.com.
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