Fintech Intelligence




Fintech Intelligence

Business Problem

Leading global investment bank, looking at large-scale accurate forecasting for product segments such as deposits inflow and outflow, securities, and loans, to maximize ROI. 


  • Dynamic pricing model to improve margins by region and provide additional services. 
  • Identify potential outlet churn through forecasting.


  • The models need to be constantly validated against actuals.
  • Fed decisions and rules have a huge impact.


  • Extracted and transformed all business-critical data across regions and product verticals into an aggregated data store.
  • Built multiple forecasting models across different segments.
  • Strategically incorporated seasonality and external factors like rate hikes.
  • Implemented ML models and Deep learning models based on product type to forecast the cash flow on monthly and yearly basis.

Business Outcomes

  • 35% : Projection Accuracy.
  • 60% : Resource reduction

Tech Stack

  • Stats Models
  • Auto-regressive Integrated
  • Seasonal Auto-Regressive
  • Auto AR
  • Trigonometric Seasonality
  • MI Models:
  • CAT & Gradient Boost