Business Intelligence with Data Mining

Topics: Data mining, Risk, Customer service Pages: 9 (2794 words) Published: May 5, 2013
Business Intelligence with Data Mining

Banking and finance institutions are growing very fast in this globalization era. Mergers, acquisitions, globalization have made these institutions bigger. No doubt, the data also grow real huge and more varied. Big data storage such as data warehouse and data marts are provided to give a solution on big data storage. On the other sides, those data are needed to be analyzed. Business intelligence finally comes in as a solution in analyzing those huge data. Business intelligence especially with data mining can create a solution in further decision making. With various tools and techniques, data mining has been proven in many aspects of business. Hidden informations that stored inside either data warehouse or data marts can be gained easily. In example, those hidden informations are market and economy trens, competitor trends, competitive price, good products and services and also can provide better customer relationship management. There is still one benefit in business intelligence with data mining that this paper will focus on, i.e. risk management and frauds and losses prevention. One of product from banking and finance institutions is credit loans. It is really a high risk business, but with business intelligence with data mining especially classification and clustering techniques, it can be maintained and implemented safely and of course with low risks, minimized frauds and losses and increased profits and revenues.

Keywords : Banking and Finance, Business Intelligence, Data Mining, Risk Management, Credit Loans

Banking and Finance institutions are growing rapidly nowadays. For one institution, there are more than one offices or branches in one country or even in different country. Globalization, mergers, acquisitions, competitions, market changes are some of the reasons behind why are they growing fast. As those banking and finance institutions grow, so do the data. In this case, banking and finance institutions probably have much more data than other institutions. Every single customer or people has one or more accounts in one institution or more. The challenge is how to maintain those data easily, how to make good decision among those data, how to create good product for customers and how to retain good customers that can bring much more profits and increase revenues.

For those that can not maintain data and make a decision for further movement without analyze the data before will find it hard to be success or even lose in competition with other banking and finance institutions. Some of key success factors in banking and finance institutions, such as : 1. Customer satisfaction

Good customer management and good product are the key to satisfy customer. If the institution could manage the customer well and offer good product that can produce benefit to both sides then it will guarantee customer will be very satisfied. 2. Customer loyalty

There is no guarantee that satisfied customers will be loyal. Strategies and tactics are needed to retain those customers. 3. Increased profit & revenue
Similar with business institutions, gaining profit and increase revenue are the most important thing. 4. Minimal risk
With many customers, banking and finance institutions need to analyze the risks that probably could happen. Not all of customers are good customer. Fraud or loss might happen. 5. Readiness for new markets to increase customer

Markets are changing rapidly. Winning the competition means winning the customer. Offered products are the key here such as higher interest, free admin cost etc. 6. Efficiency of operations
Since banking and finance institutions have several branches and many customers, the challenge is to make operations in daily transactions become efficient.

Problems in Banking and Finance Institutions
Similar with other institutions in business, banking and finance institutions also have some of problems...

References: Journals:
[1] Dass, R. (2006). Data Mining In Banking And Finance: A Note For Bankers. Indian Institute of Management, Ahmedabad .
[2] Katarina Curko, M. P. (2007). Business Intelligence and Business Process Management in Banking Operations. Information Technology Interfaces .
[3] Muhammad Nadeem, S. A. (2004). Application of Business Intelligence In Banks (Pakistan). CoRR .
[1] Bhasin, M. L. (2006). The Chartered Accountant, Banking and Finance, Data Mining: A Competitive Tool in the Banking. Oman.
[2] Larissa T. Moss, S. A. (2003). Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications. Addison Wesley.
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