Home Articles GIS – Tool for Simplifying the Collection Management System in Banks and...

GIS – Tool for Simplifying the Collection Management System in Banks and Financial Service Organizations

P K Panigrahi


P K Panigrahi
Faculty, Loyola Institute of Business Administration (LIBA),
Loyola College, Nungambakkam, Chennai, State- Tamilnadu, Pin-600 034, India
Email: [email protected]

P. Vijay Sagar
EGIS Solutions Private Limited, Chennai, India,
Email: [email protected]

P. Ronald Raajesh
Sr. Area Executive, TVS Motor Company Ltd., Vijayawada, State: Andra Pradesh, India
Email: [email protected]

The Collection Process:
When a customer avails a loan or a credit card from a Multi National Bank, he is instructed to pay the installments or the due amount via cheque or cash by either depositing it at collection boxes placed at various ATM centers, the bank’s branches or at certain shopping centers. When a customer defaults the payment the Tele-Collection Officer reminds the defaulter over phone that his payment is due and fixes an appointment with the customer. The Field Collection Officer visits the defaulter to ensure that the customer repays the loan amount or the credit card due via a cheque which is deposited in the nearest collection box or branch.

Issues of Concern in the Collection Process:

  • The Bank is unable to decide in which area it has to place collection boxes so as to facilitate the deposit of cheque and cash so that the number of defaulters are reduced.
  • The location of the customer can change over a period of time. Hence a collections officer who has visited the customer once again has to search for his location.
  • The Bank is unable to find in which geographic location the number of defaulters is more.
  • The easiest route through which a collection officer can travel so as to meet the maximum number of defaulters is not known.
  • Difficult in assessing the demographic patterns of defaulters in certain regions like living within 3 km of a collection center or living more than 2 km away from all collection centers and located in one zone, etc.
  • Difficulty in finding the main geographic area in which a particular type of defaulter is not present.

Methodology

  • Preparation of zonation map of Chennai City
  • Preparation of road map of Chennai City
  • Location of ATM Centers using GPS data
  • Location of customers using Geocoding a module developed using Map Objects and VB
  • Classification of defaulters based on type of defaulters viz., Credit Card, Housing Loan and Personal Loan.
  • Analysis of the defaulters, to find the location of the defaulters, method of collection, with respect to the Bankers, similarly from the point of view of the defaulters suggestions are made to learn the exact location of the ATM etc.

Preparation of Zonal and Road network map of Chennai City
The zonal map of Corporation has been utilized to prepare the zonal map of Chennai city and the road network map was digitized with zonal map as the base. The attribute data pertaining to the road map has also been updated.

Locating ATM Centers:
GPS has been used to find the exact location of the ATM centers of the bank as it is desired to make measurements in the study. This would also help to locate new centers


The above figure shows the various zones in the city, along with roads, and the ATM Centers.
 
Customer address table

 

Locating Customers:
The number of address changes submitted to a large bank is about 95 per day. This makes the job difficult for the Collections Department which has to relocate the customer every time. An integrated GIS approach would ensure that every customer’s location is geocoded so that locating a customer even after a series of address changes would be easy. This should be done atleast for persons who have obtained Loans and Credit Cards. Then the customers have been classified as loanees and account holders with the loanees further divided into different types of defaulters as well as shown in the following figure.

 
 Map showing different types of defaulters

 
 Analysis of defaulters:
The demographic and socio economic characteristics of defaulters in a particular geographic location in comparison to other non-defaulters would throw light into some patterns that would be useful for Banks in deciding whether to grant loans to other customers who fall into a similar pattern and if granted what are the methods that they should employ to minimize risk. GIS facilitates this analysis to find finer details by enabling analysis like assessing the demographic patterns of defaulters in certain regions like living within 3 km of a collection centre or living more than 2 km away from all collection centres and located in one zone, etc.
Location Based Information
In this module the user is given an option to select the customer based on location as well as the distance.

If the user select the spatial select the following window will be displayed prompting him to select the zone, the feature using a specific method.

Based on the selection made that particular feature will be selected as in the above case the ATM centers in the North Central zone will be selected.

Assessing the Geographic Concentration Areas:
The concentration areas of a particular type of customer can be easily identified using GIS. For example the concentration area of Credit Card defaulters can easily be assessed. Even the zones in the city can be classified according to a particular theme.

Distance based analysis of defaulters
To select different types of defaulters depending upon the distance from an ATM, the ‘distance’ facility may be used.


The distance may be entered in the following window, to create a buffer around the ATM center for a distance of 3000m and using the boundary select we can select all the types of defaulters.


The above figure shows the buffer, around the ATM center (shown in yellow). The following table shows the various defaulters, which has been listed. Some more details may also be displayed if necessary, however, it requires input of data which can be done at any stage which is an added advantage in GIS.
 
  Finding the shortest route an ATM center given the ‘from’ road ‘to’ road.
Many a times it will be necessary to know the shortest distance from any given ATM center for the account holder to deposit his cheque etc.

Based on the ‘From’ and ‘To’ road an ATM center is selected as shown below indicating the Center in green colour.
 
 Conclusion:
From the above study it is very clear that GIS is an effective tool in any discipline with relevance to space, it can be used to identify the location of ATM centers, location of customers, classification of defaulters, and so on. This is an attempt to ustilise GIS technology and Software for Banking sector.

In today’s fast paced mode of operations it is totally impossible for banks to neglect even a single customer by not providing the service that he asks for. This is magnified by the fact that the switching costs have become very less and banks are not able to encash on the various differentiation strategies that they were adopting because the services provided by them are becoming more of a commodity day by day. Hence it would be considered intelligent for banks in not losing a single rupee as defaults in payments. This can be achieved only through proper strategic planning and good operations management that the collection department follows through the latest technology like GIS for revolutionizing their collection process it self.