Institution: Bangladesh University of Engineering and Technology (BUET)
Project Name: Artificial Agent for Better Banking
Team Members:
Mohiuddin Abdul Qader, Department of Computer Science and Engineering, BUET
H. M. Sajjad Hossain, Department of Computer Science and Engineering, BUET
Md. Mesbahul Islam, Department of Computer Science and Engineering, BUET
Md. Enamul Kabir, Department of Industrial & Production Engineering (IPE), BUET
Project Manager:
Abdullah-Al Mamun, Lecturer, Department of Industrial & Production Engineering (IPE), BUET
Bank is an important institution and Mechanism for any country. Efficient banking industry greatly contributes to the overall economic growth of a country. Banks are now becoming automated and are continuously taking advantages from new technologies and softwares. An economist named Rene T. Domingo has expressed in one his journal that “ Future banking will be knowledge based, rather than traditional asset based ” This motivation has led BUET- Snipers to develop a knowledge based system for banks and the result is the product “ Artificial Agent for better Banking ”.
Banks have huge amount of transaction data in their database. Maximum of these data remain idle over years. Banks have to take the burden to store these data and not able to use their resources. More over the banks servers remain idle most of the time at night. So banks are not also not using their resources efficiently. On the other hand most of the data stored in the bank database is not structured. Most of the analyses in the banks are manual and time consuming. Our software will help bank analysts for performing various bank analyses. Our software will first structure all the historical data and then save it in the data warehouse. The software will analyze all kinds of structured historical data according to analyst’s requirements. Our product uses data mining techniques for analyzing historical data. After performing data mining over historical data, the software will try to identify patterns in the data and notify the results to the bank analyst. Initially our main purpose is to perform data mining techniques for identifying –
• Valued customers in the banking system: The software will also identify potential valued customers. Banks can then take necessary steps to satisfy their valued customers.
• Bank sales / Loan statistics: The software will identify what types of loans are popular over a certain time period in any branch. Banks can then promote those popular loans.
• Liquidity demand: The software will perform various trend analyses over the historical data and display the statistics to the bank analyst. The bank analyst can then choose the best result.
By introducing “Artificial Agent for Better Banking” in the banking system will surely reduce valuable time for all the manual works performed by bank analysts and it will also ensure greater prosperity.