Forecasting & Budgeting
- Performed Forecasting and Budgeting for the Annual Budget Cycle(s) and Stress Testing exercise (CCAR) for total Credit Card Portfolio of Chase, spanning across 36 products over multiple vintage groups, totaling over $200B in Outstandings and $1000B in Sales
- Conducted detailed Month-to-Date Variance Analysis and Divergence Attribution to identify key trends/divergences in the actual performance and the driving factors/products, recommending suggested corrections to be reviewed monthly with Card CFO
- Sized, proposed, implemented overlays to capture Pricing Increase, Cash Line increase and Credit Line increase for CCAR exercise, on top of our base modeled Forecast, eventually documenting and presenting them to senior leadership and review forum before final submission to Fed
- Analysed historical financial data, MoM growth, seasonality and emerging trends in the Credit Card spend, revolving and payment trends and other metrics using different set of tools and aligning future projections to it
- Performed Rate Analysis to finalise the rates for dependent metrics to be fed into models for each model run to capture correct trends and produce accurate outputs
Collaboration & Partnerships
- Partnered closely with partner CFO leaders over multiple iterations to capture their feedback and expectations using detailed reports on key performance indicators and recommendations
- Worked closely with New Acquisitions and Strategy team to understand any new strategy roll out/product refreshes to align our projections and perform overlay adjustments
- Worked closely with Modelling, Strategy, Risk to produce and document overlays in Stress Testing exercises to seek approval from Model&Overlay review forum before final submission
- Partnered closely with MIS and Data Visualisation teams to help develop Tableau & Databricks based dashboards that help size results and report final numbers every budget Cycle
Automation & Process Improvements
- Built an Alteryx based Validation Tool to capture outliers on the forecasted volumes against the historical Month-on-Month growth segmented at 4 levels, for 36 product x 9 vintage groups, across 20+metrics resulting in identifying potential operational errors leading to more refined and high quality projections
- Created an interactive ThoughtSpot dashboard to capture the drivers of variances to enhance forecasting accuracy
- Built several excel based tools to perform deep analytics on our monthly error growth, scenario analysis, product/vintage level performance leading to capture systemic error that requires correction