Data Analysis
Budget: ₹1,250 – ₹2,500 INR
A consumer bank with a range of products would like to cross-sell insurance to its consumer base (that is, cross-sell the personal protection insurance (PPI) product to those customers who have a secured or unsecured type of loan, but no PPI product as yet).
Attached is a sample data set from their customer portfolio containing various fields about their product ownership, credit standing, outstanding amounts, and whether they already have an insurance product (called as PPI / personal protection insurance), if any, the type of PPI product they own.
The bank would like to adopt analytics driven approach applied on this sample data for deciding:
- Who should they target from the pool of customers that currently do not have a PPI, and
- What type of PPI product they should be targeting them with.
Using the attached sample data as a guidepost, please come up with a relevant analytics approach focused on the following, in a PowerPoint presentation format:
- Your understanding of the different data fields
o Note: No further information is available on data field descriptions etc. You could make smart assumptions about what the fields mean, and call out such assumptions.
- Call out the various types of analysis that could be performed with the data. Feel free to include any exploratory insights from the data that you were able to glean. We are not looking for you to necessarily come up with any Data Science / ML model. We are interested in the quality of insights you are able to generate, even with some slice & dice. However, if you can, you are welcome to give it a shot too..
- How you would use the insights from the analysis in designing a simple, but effective strategy to achieve the goal of cross-sell (pls note, the intent is not to sell an incremental product, but to introduce personal protection insurance to those who don’t have it as of now).
- How would you measure the improvement driven by the approach?
Attached is a sample data set from their customer portfolio containing various fields about their product ownership, credit standing, outstanding amounts, and whether they already have an insurance product (called as PPI / personal protection insurance), if any, the type of PPI product they own.
The bank would like to adopt analytics driven approach applied on this sample data for deciding:
- Who should they target from the pool of customers that currently do not have a PPI, and
- What type of PPI product they should be targeting them with.
Using the attached sample data as a guidepost, please come up with a relevant analytics approach focused on the following, in a PowerPoint presentation format:
- Your understanding of the different data fields
o Note: No further information is available on data field descriptions etc. You could make smart assumptions about what the fields mean, and call out such assumptions.
- Call out the various types of analysis that could be performed with the data. Feel free to include any exploratory insights from the data that you were able to glean. We are not looking for you to necessarily come up with any Data Science / ML model. We are interested in the quality of insights you are able to generate, even with some slice & dice. However, if you can, you are welcome to give it a shot too..
- How you would use the insights from the analysis in designing a simple, but effective strategy to achieve the goal of cross-sell (pls note, the intent is not to sell an incremental product, but to introduce personal protection insurance to those who don’t have it as of now).
- How would you measure the improvement driven by the approach?