International Journal of Computer Engineering and Applications, Volume XII, Issue IV, April 18, ISSN

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1 International Journal of Computer Engineering and Applications, Volume XII, Issue IV, April 18, ISSN BEHAVIOURAL ANALYSIS OF BANK CUSTOMERS Preeti Horke 1, Ruchita Bhalerao 1, Shubhashri Tasare 1, Vijaya Shendre 1 Rajeev N. Verma 2 1 Student, Department of Computer Technology, YCCE, Nagpur, India 2 Asst. Prof., Department of Computer Technology, YCCE, Nagpur, India ABSTRACT: Banking fraud comes primarily in mind these days when we discuss the fraud that occur in day to day life. In recent years banking fraud has been increasing extremely. Every year the accidents of in banking sector is rising. Fraud causes significant cost to our economy. By using user history means detail information of transaction of money we can reduce the fraud detection. Simply by using analysis of user s data we can predict the behavior of user. More fraudulent actions are being detected and reported these days with the help of various data mining techniques. Keywords: Analysis, domestic transaction, sanctioning of loan [1] INTRODUCTION The development in the business sector has lead to a tremendous change in the banking sector throughout the world. With the recent development and implementation with the help of development lifecycle, greater acceptance and usage of electronic banking, the capturing of transactional data has become easier and simultaneously, the volume of such data has grown considerably because of the huge increase in the transactional data. The analysis of this huge raw data and the transformation of the data into useful knowledge for the organization is beyond human capability. Data Mining can help by contributing in business problems by solving them using various techniques like finding patterns, associations and correlations which are hidden in the business information and data stored in the huge data bases. By using data Preeti Horke, Ruchita Bhalerao, Shubhashri Tasare, Vijaya Shendre and Rajeev N. Verma 243

2 BEHAVIOURAL ANALYSIS OF BANK CUSTOMERS mining to analyze patterns and trends, bank executives can predict with the help of training data set, with increased accuracy, how the customers will react to data mining and how it can be used in the banking industry and also in fraud detection. Being able to detect fraudulent actions is an increasing concern problem for many businesses as they are the people to be affected the most; and with the help of data mining more fraudulent actions are being detected and reported and solved. Two different approaches have been developed by financial institutions to detect fraud patterns. In the first approach, a bank taps the data warehouse of a third party (potentially containing transaction information from many companies) and uses data mining programs to identify fraud patterns. The bank can then cross-reference those patterns with its own database for signs of internal trouble adjustments in interest rates, which customers will be likely to accept new product offers, which customers will be at a higher risk for defaulting on a loan, and how to make customer relationships more profitable. [2] TECHNIQUE The techniques used are almost same in all the banks. The banking sector provides various services, advantages to the regular customers and allowance of the loan is an important aspect to be discussed in the perspective of the formation of this system. Classification is a classic data mining technique used to classify each item in a set of data into one of predefined set of classes or groups, based on machine learning. The methods of classification fall back on mathematical approaches including statistics arena, linear programming methodology, neural networks, and decision trees. Fraudulent cases detection and credit risk appliance are well suited to this analysis. Learning and Classification are the main steps included in data classification. Learning analyzes dataset using classification algorithms whereas Classification on the test data are used to estimate the accuracy of the classification rules, that allows implementation of rules to the new data tuples. Fraudulent applications are traced by detecting complete records of frauds and invalid activities.j48 classifier allow simpl implementing of the classification features for accounting for decision trees pruning, absent values, continuous attribute value ranges, rules derivation. In the WEKA data mining tool, J48 is an open source Java implementation. [2.1] HOW BANKS WORK Banks work by paying its customers to lend them money. When a person deposits money into their bank account, the bank can then lend other people that money. The depositing customer gains a small amount of money in return (interest on savings), and the lending customer pays a larger amount of money to the bank in return (interest on loans). To make money for itself, the bank keeps the difference. It can be quite difficult to understand banking, since banks are very different from most other businesses. For one thing, they are highly leveraged, with more than $20 in debt for every $1 of equity. Also, it can be hard to understand what banks actually do, since they don t make any real products. And a lot of people seem to think that banking is free, probably because banks keep advertising free checking accounts, free direct deposit, free bill payment, etc. Preeti Horke, Ruchita Bhalerao, Shubhashri Tasare, Vijaya Shendre and Rajeev N. Verma 244

3 International Journal of Computer Engineering and Applications, Volume XII, Issue IV, April 18, ISSN [2.2] THE IMPACT OF DEREGULARISATION The wave of de-regulation, beginning in the late 70s, changed this relationship. Main street companies discovered that they could borrow from the bond markets more cheaply than they could from banks, putting the 6 part of the model under pressure. And lots of new consumer products such as interest bearing checking, credit cards, money market accounts, home equity loans, student loans, etc became available. Banking became a lot more complicated, so bankers couldn t just head to the golf course at 3 pm; they had to actually work for their money. Two things ended up happening: banks realized that the bigger they were, the more loans they could make. With deregulation, the big banks grew even bigger by acquiring smaller banks. Banks also realized that the easiest way to make more money was to simply charge consumers more fees. In fact, the best way to make money was to call a product free by eliminating any monthly fees, and then charging lots of fees on transactions. [2.3] ABOUT ONLINE BANKING Online banking is simply a way to access and manage your bank, mortgage, credit card, loan or other account information via the Internet instead of visiting the bank in person or using the telephone. Most banks, credit unions, credit card companies, mortgage companies, and other financial institutions now offer online banking, which allows you to use a computer with an Internet connection to: -View balances in real-time - View and search transactions - Download monthly statements - Transfer money between accounts - Set up electronic bill pay - Set up an automatic savings plan - Open a new account - Apply for a loan [2.4] HOW DOES ONLINE BANKING WORK [2.4.1] INITIAL STEP Online banking is easy to use, but it requires a one-time registration or set-up on your financial institution's website. To do this, look for "Home Banking" or "Online Banking" log in, typically located prominently at the top of your bank's website. You'll typically need to enter the name on the account, your account number, and your social security card number for verification. Then you'll create a user name, enter your address (so you can be notified when your monthly statement is available), and set a password. A few banks require you to register in person or over the phone in order to set-up online banking, so if you can't find the online banking registration info on your bank's website you may need to contact them for instructions on how to set it up. [2.4.2] LOGGING IN After the initial set-up and registration, you can log in and access your account any time by entering your username and password at the online banking section of your bank's website. Typically, once you're logged in you'll come to a summary page which shows you an at-a-glance Preeti Horke, Ruchita Bhalerao, Shubhashri Tasare, Vijaya Shendre and Rajeev N. Verma 245

4 BEHAVIOURAL ANALYSIS OF BANK CUSTOMERS look at your accounts and their balances, the most recent transactions, and any items that are pending. [2.4.3] USE THE TOOLS YOUR BANK OFFERS Each financial institution offers a variety of online banking tools, including automatic savings, transfers between accounts, bill pay, and more. On your first log in, you'll want to take the time to familiarize with these features, and which ones would benefit you the most. Features vary, so if you don't see what you're looking for, contact your bank for information. Many offer live chat with a customer service representative online, but you can also contact them by phone for more information. [2.5] THE BENEFITS OF ONLINE BANKING [2.5.1] 24-HOUR ACCESS TO YOUR ACCOUNT You can get the account information you need whenever you need it in the privacy of your own home. Better yet, if you travel a lot like I do, you can access your account anytime, anywhere. [2.5.2] REAL-TIME INFORMATION SYSTEM You'll stay up-to-date on the status of your account, including your current balance, pending items, most recent transactions, etc. [2.5.3] HELP PREVENT OR MINIMIZE FRAUD With online banking, you can check your account regularly and notify your bank immediately when you see a transaction that isn't familiar to you. [2.5.4] AUTOMATIC SAVINGS PLAN You can make account transfers any time you want. Many banks will also allow you to set up an automatic savings plan to transfer money from your checking account to your savings account each month. [2.5.5] PLANNING TOOLS Many banks offer financial planning tools to help you set and meet savings goals, pay off loans early with extra payments, and more. These tools vary, so be sure to check your bank for availability. [2.5.6] FINANCIAL ANALYSIS Some banks or credit unions offer you financial incentives for using online banking. The credit union I use offers a 3% APY on balances up to $15,000 and a $15 refund (per month) on any ATM withdrawal surcharges. To qualify for these financial bonuses, you need to have direct deposit, make a minimum of 10 debit card purchases per month, make at least 4 log ins to online banking, and sign-up to receive your monthly bank statement by instead of the postal service. Preeti Horke, Ruchita Bhalerao, Shubhashri Tasare, Vijaya Shendre and Rajeev N. Verma 246

5 International Journal of Computer Engineering and Applications, Volume XII, Issue IV, April 18, ISSN [2.5.7] FASTER ACCOUNT BALANCING With online banking, your account statement is typically available to view online or download on the first day of the month, so there's no waiting around three to five days after month-end for your statement to arrive. If you use personal finance apps like YNAB, Mvelopes, Mint, or others, you may be able to import your bank account information into that app, making balancing your accounts a snap. [3] PROPOSED MODEL This system makes use of the database that is stored in the server. It can be analysed by the administrator only and the report is authorized to be viewed by only the administrator. The user performs various transactions and the data of the transaction is created accordingly as the amount that is involved in the transaction, the range of the transaction, whether it is domestic transaction or an outer transaction and various other attributes that are to be included in the transaction features. The various transactions that can occur during this process are: -View balances in real-time - Download monthly statements - Transfer money between accounts - Open a new account - Apply for a loan The administrator can view the report and decide whether to sanction a requested loan to the customer or to not sanction the loan to the customer. The Allowance will depend completely on the amount for which the customer demands the loan and the transactions he has done in the bank during the whole time period. Thus, allowing the administrator to completely decide whether the loan should be sanctioned or not. Figure 1 explains the design and working of the system in the architectural view. [3.1] SYSTEM ARCHITECTURE Figure: 1. Design of the system for the behavioral analysis of bank customers. Preeti Horke, Ruchita Bhalerao, Shubhashri Tasare, Vijaya Shendre and Rajeev N. Verma 247

6 BEHAVIOURAL ANALYSIS OF BANK CUSTOMERS [4] RESULT AND ANALYSIS The system formed helps in the analysis of the behavior of the customer with the help of the transaction data created by the user himself. The administrator himself gets to decide with the help of the report whether to sanction the loan or not. The report is used as an input to help the administrator decide in the form of the graphs of status and success of the transactions done till date. Also, the previous loan amounts and the loan amounts of the other seeking for permission for sanction. [5] CONCLUSION Data mining is a technique used to extract vital information from existing huge amount of data and enable better decision-making for the banking and retail industries. They use data warehousing to combine various data from databases into an acceptable format so that the data can be mined. The data is then analyzed and the information that is captured is used throughout the organization to support decision-making. Data Mining techniques are very useful to the banking sector for better targeting and acquiring new customers, most valuable customer retention, automatic credit approval which is used for fraud prevention, fraud detection in real time, providing segment based products, analysis of the customers, transaction patterns over time for better retention and relationship, risk management and marketing. REFERENCES [1] K. Chitra, B.Subashini, Customer Retention in Banking Sector using Predictive Data Mining Technique, International Conference on Information Technology, Alzaytoonah University, Amman, Jordan, [2] K. Chitra, B.Subashini, Fraud Detection in the Banking Sector, Proceedings of National Level Seminar on Globalization and its Emerging Trends, December [3] Behrooz Noori, An Analysis of Mobile Banking User Behavior Using Customer Segmentation, International Journal of Global Business, 8 (2), 55-64, December [4] Chen, C.S. (2013). Perceived risk, usage frequency of mobile banking services, Managing Service Quality, 23(5), [5] Zuccaro, C., & Savard, M. (2010). Hybrid segmentation of internet banking users. Preeti Horke, Ruchita Bhalerao, Shubhashri Tasare, Vijaya Shendre and Rajeev N. Verma 248