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Analyst
ICICI•  July 2018 - Present
o Developed a behavioral scorecard for Canada credit card customers. Every month 2k student cards are renewed basis this scorecard. A stepwise logistic regression model was fitted to generate the score of the customer. Data extraction was done in SAS and the model was developed in R o Developed a credit card propensity model for the liability base of the bank. The event rate was 2.8% at the portfolio level before developing the model. This model helped the bank in saving resources by targeting less population and getting high conversions o Built a propensity model for travel card using XGB and GBM (gradient boosting) technique. The model takes past 3 years spends, bureau and demographic details of the customer as input and gives the probability of him/her traveling international in the coming months. Model development and EDA were done in Python while SQL was used for the data extraction o Built a recommendation model (RFM) on merchant level which helps in sending the customized offers to a customer on internet banking/ i-mobile app. This model generates RFM scores for each customer on every merchant category which the customer has transacted on in the past. Basis these scores top 3 merchant offers are shown to a customer. Also, developed Alternate Least Square in Python for finding the next best merchant categories on which he has never transacted but other customers from the same cluster have transacted on and therefore he is also likely to try o Built a debit card optimization model to drive debit portfolio spends using a stepwise approach to address the need of a portfolio segment.
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