30/10/2026
If you’ve ever wondered how we know which customers are due for cashback, Azole is one of the people to thank. 👏
Read the caption below, where Azole shares how AI fits into her job, what stood out about Simply’s data setup, and why keeping data accurate is never a one-and-done task.
"AI has become part of my daily workflow. Instead of spending hours searching for a solution, I can test ideas much faster and focus on refining them. That said, I've learned that AI is only as good as the context you give it. In insurance, the business rules behind commissions, payments, and policy administration are often very specific. Understanding those rules, asking the right questions, and validating the results still requires human judgment. AI helps me work faster, but accuracy and understanding remain my responsibility.
I was impressed by how much thought has gone into Simply's data ecosystem. It's not just about storing information - it's about how different systems and teams contribute to a connected view of the business.
I think that the biggest misconception about keeping data accurate, is that data cleaning is something you do once. In reality, it's an ongoing process. Data quality depends on understanding where the data comes from, how it's captured, and how different systems interact.
A report can look perfectly correct while still telling the wrong story if the underlying business rules aren't understood.
One project I'm particularly proud of was improving how we identify customers who are due for cashback. The challenge wasn't simply calculating who qualified - it was making sure the logic correctly handled policy changes, missed payments, cancellations, claims, and benefit upgrades.
It was rewarding because it combined technical problem-solving with a deep understanding of the business, and it helped reduce manual effort while giving the team greater confidence in the results."
We appreciate the work that you do. ☘️
