Abstract
In this research, based on financial transactions between bank customers which extracted from bank’s databases we have developed the relational transaction graph and customer’s transactional communication network has been created. Furthermore, using data mining algorithms and evaluation parameters in social network concepts lead us for segmenting of bank customers. The main goal in this research is bank customer’s segmentation by discovering the transactional relationship between them in order to deliver some specified solutions in benefit of some policy about customers equality in banking system; in other words improvement of customer relationship management to determination of strategies and business risk management are the main concept of this research. By evaluation of Customer segments, banking system will consider more efficient and crucial factors in decision process to estimate more accurate credential of each group of customers and will grant more appropriate types and amount of loan services to them therefore it is expected these solutions will reduce the risk of loan service in banks.
Highlights
After you have introduced Using bank services and financial transactions by customers in various subsystems of banking, great amounts of data in databases of bank have been generated
To improve customer relationship management (CRM) process, customer behavior is evaluated in bank system and as customer behavior in bank system is transactions by them in interval, the collected data of customers is the data of financial transactions by them
Customer segmentation based on Customer Lifetime Value (CLV) is one of the new approaches regarding customers’ segmentation and is one of the efficient methods in segmentation of customers
Summary
After you have introduced Using bank services and financial transactions by customers in various subsystems of banking, great amounts of data in databases of bank have been generated. These databases can be important source to detect knowledge and behavioral models of customers of bank to take decisions in development of customer relationship management (CRM), determination of strategies and business risk management. One of the most important parameters given to banks or each economic enterprise is increasing awareness and knowledge of bank/ institution to financial issues between customers over time. As facilities service is one of the most important business sectors of banking industry, loan risk or risk of non-payment has special position in banking. The financial institutions and banks should measure the risk of credits to avoid such problem
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