Irum AmjadMarko B PopovicOscar Moll

Problem

Traditional customer account information do not fully summarize the customer spending patterns E.g. most spent on Items, change in

habits etc Question: Is there more general

explanation to the phenomenon of customer transactions?

Goals

Identify modes of pathological spending behaviors from current and historical data

time patterns, resource allocations

Predict future spending pattern Plan and assist customers to prevent

delinquency Extract, classify and visualize spending

over long time periods to assist both bank customers and employees

Proposed Approach

Information needed

Healthy customer accounts data Data on specific allocation of

resources Track group of current users if historical

data unavailable or does not exist

Project Details

The customer profile is defined for each month

The horizontal bars represent the dollar amount which the customer spends based on a monthly pattern.

Then in each criteria a bubble highlights the most spent on Items.

The different colors in the Dollar amount bar are representative of the different criteria's

Customer Profile January

Customer Profile February

Customer Profile March

Customer Profile April

Customer Profile May

Customer Profile June (Current)

Behavior PatternTravel

Health

Real estate

Bank can collaborate by

Health: Helping the customer look into different

loans or health insurance policies for health

Travel: Provide incentives to collaborate with

the Bank of America airline customers Real Estate:

Look into buying real estate using Bank of America as a third party.

Future Applications

Alert system to warn customers when they exceed the “optimal” budget

Integrate the results with the Google maps to alert users each time a undesirable financial behavior is about to arise

Based on previous transactions associated with certain locations, routes, times

Importance of this approach Summarizing and classifying customer

expenditure can result in the following important steps Classify customer behaviors using

clustering Identify customer spending locations Identify customer spending pattern based

on time of the year Create customer guide to help customers

with credit and loans based on pattern of transactions

Real Estate

Transaction date:15-02-08 Place:5th Ave(www.googlemaps.com) Amount:$50 Time:18:05 Frequency:Alot

Starbucks

Transaction date:15-02-08 Place:5th Ave(www.googlemaps.com) Amount:$50 Time:18:05 Frequency:Alot

Macdonald’s

Transaction date:15-02-08 Place:5th Ave(www.googlemaps.com) Amount:$50 Time:18:05 Frequency:Alot

Target

Transaction date:16-02-08 Place:www.googlemaps.com Amount:$100 Time:18:25 Frequency: rare

American Airlines

Transaction date:15-02-08 Place:5th Ave(www.googlemaps.com) Amount:$50 Time:18:05 Frequency:Alot

Massachussettes General

Transaction date:15-02-08 Place:5th Ave(www.googlemaps.com) Amount:$50 Time:18:05 Frequency: lot