Analytics & Customer Insights
A dashboard nobody looks at twice, it’s not a screenshot. It is an analytics deliverable.
I’ve built Power BI dashboards using DAX and Power Query, SQL-driven performance models, Excel macro automation, and Tableau visualisations across banking and insurance clients — and the thing I’ve learned is that the technical build is rarely the hard part. The hard part is understanding what a C-suite audience or a branch manager actually needs to see to make a decision on a Monday morning, and building exactly that, not everything that’s technically possible to show.
The MIS dashboards I built at HDFC Bank and IndusInd Bank eliminated 12+ hours a week of manual reporting — not because the automation was clever, but because I spent time understanding which KPIs the leadership team actually acted on and which ones were just noise in a 40-tab spreadsheet nobody opened.
What I build and why it matters:
- KPI frameworks with genuine leading and lagging indicators — not just a wall of numbers with no hierarchy of importance
- Customer segmentation and churn analytics that give RMs and marketing teams a model they can act on, not a data science exercise that lives in a slide deck
- Revenue analytics tied directly to cross-sell and portfolio performance, so leadership can see not just what happened, but what’s about to happen if nothing changes
- Executive MIS that a branch manager or AVP can genuinely use for their weekly review, without needing an analyst to interpret it for them
Good analytics in banking isn’t about the sophistication of the model. It’s about whether the person looking at it on a Tuesday morning knows exactly what to do next.