8 DECEMBER 2024IN MY OPINIONTHE BENEFITS OF ANALYTICSFOR INSURANCEBy Pantea Vaziri, Head of Global Cyber Analytics, Allianz Global Corporate & Specialty (AGCS)One of the best pieces of career advice I received was shortly after joining Allianz as a Catastrophe Analyst, following several years of employment with a top risk modeling firm. During my first one-to-one meeting with the Global Head of Catastrophe Management, I asked how best to achieve success with this new company and she simply stated, "Learn how the underwriters think."Although much has been written on the latest advancements within the Insurtech space, leaders in this area rarely discuss the paradigm shift that needs to happen in the minds of analytics teams - as well as corporate organizations as a whole - necessary to establish a truly data-driven business. While insurance companies initially feared Insurtechs would slowly takeover their market share, partnering with these firms is now widely seen as the tool needed to drive growth and development. Analytics with PurposeThe first shift needed to take place is within the mindset of the analytics talent. Too often top employees treat their jobs as an extension of their graduate school dissertation, which results in siloed thinking, costly projects, and under-utilized reports. Instead, analytics work should have a business purpose, and all must develop a crisp understanding of how their results are used to make a business decision. Programs such as mandatory shadowing, job rotation, and investing time in understanding the details could be effective in achieving this change in mindset.Leaders should also invest time to ensure teams understand the key business KPIs, their components, and their relations to the broader strategy. Analytics teams are often skilled in delivering their piece but fail to understand the puzzle they are part of. We often speak about upskilling business teams in data and analytics. Upskilling analytics teams in business concepts is just as important.Analytics embedded in BusinessWhen it comes to data, it is important to establish a single source of truth. It is also crucial to continuously improve data quality at its point of entry. As low-quality data cascades through the organization, fixing it becomes exponentially costlier. However, too often IT, business, and analytics teams workin separate units with few touch points scattered as meetings throughout the year. This creates silos, multiple versions of the truth, and reports that may not serve immediate needs of the business.Pantea Vaziri
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