SR is Leading Non banking finance company Market Share of 40% commercial vehicle finance in India 600 branches all over India. Financing the different commercial vehicle SGV- Small good Vehicle (4 wheeler only) LGV- Light good Vehicle (6 wheeler Only). HGV-Heavy goods Vehicle
Transcript of "Data Mining Technique Clustering on Bank Data Set "
Glimpse to process
XYZ is Leading Non banking finance company
Market Share is 40% of commercial vehicle finance in India
600 branches all over India.
Deals with different commercial vehicle
Small goods Vehicle (4 wheeler only)
Light goods Vehicle (6 wheeler Only).
Heavy goods Vehicle (Above 6 wheeler only)
Passenger (Commercial only)
Due to stagnation in the market of Commercial vehicle and
Problem 1 - Whom to be focused for Top-up loans/Different
Problem 2 - Whom to be focused for NPA collection/
Portfolio of 1092 customers of the Single Branch.
Data contains total attributes of 21
Used Attribute: 8
1) Gross Demand
2) Gross Collection
4) Arrears Month
5) Advance Amount
6) Agreement Value
7) Settlement figure
8) Loan no
• Group the Customer by using the Data mining
Technique - called Clustering.
• Tool Used - Rapid Miner
• Clustering Technique - X means.
• Execution of data in Rapid Miner by using Optimization
Process to define the number of clusters and than
clustering with X-mean technique
• No of Clusters formed - 4
• Cluster 0
The average loan amount in this set is 3.5 to 4 lakhs
Average preferable Emi is Rs 10132
Average collection is 75%
Comprised of Passenger, Small Goods Vehicle and Light
• Cluster 1
The average loan amount in this set is 1.5 lakhs
Average preferable Emi is Rs 5438
Average collection is 82%
Mainly Passenger and Small Goods Vehicle
• Cluster 2
The average loan amount in this set is 7.55 lakh
Average preferable Emi is Rs 12915
Average collection is 37%
Comprised of Light Goods Vehicle and Heavy Goods
The average loan amount in this set is 6.10 lakh
Average preferable Emi is Rs 17391.
Average collection is 55%.
Light Goods Vehicle, Heavy Goods Vehicle.
• Cluster 1: It contains 499 customers which should be
focused for top up loans/promotional offers- like credit
card, tyre loan, engine loan, power loan. Cluster 0 can
also be focused for the above but it should be optional
call by the Manager.
• Cluster 2: The data here is having the average arrears
of 45 months, which should be handed over to collection
agent and must be forwarded for legal processing.
Similarly in Cluster 3, the average loan amount is high
and are in arrears so executives can be improvised to
maintain the portfolio.
If successfully executed, plan for Pan
Targeting the Cluster 2 to improve the NPA ratio
Targeting the Cluster 1 for Business Capitalization
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Cluster 0: 361 items
Cluster 1: 499 items
Cluster 2: 22 items
Cluster 3: 210 items
Total number of items: 1092