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Ditching Excel for Python – Lessons Learned From a Legacy Industry (2020)

Amy Peniston:

I’ve been in a reflective mood lately, probably because it’s the end of a very eventful year. Change is all around us and technology is the enabler.

On that note, I’ve been thinking a lot about my own experiences with technology-driven change in the reinsurance industry, where I worked as an analyst from 2017 until recently.

During these three short years, I observed a radical shift in data analysis methodologies. Excel-based models, which had seemed top-of-the-line suddenly were too slow and too rigid; Integration with 3rd party data sources, which was once a luxury, became the norm; And analysts began to utilize scripts to accomplish many labor-intensive tasks typically performed by hand or in spreadsheets.

Enabling this change is a suite of accessible Python-powered tools. These technologies are rapidly displacing the old way of doing things, ushering in a new wave of reinsurance models and the talent needed to support them.

Admittedly, the following observations do come from a very niche industry. But I believe that the broader trends discussed here will also apply to other legacy companies and sectors.

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