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Decision Support Systems at SunTrust Banks - Assignment Example

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This assignment "Decision Support Systems at SunTrust Banks" focuses on a premier financial services company based in the Southeastern United States, that provides a wide range of services to meet the financial needs of its growing customer base through 700 full-service banking offices…
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Task 1: Business Goals SunTrust Banks, Inc., a premier financial services company based in the Southeastern United States, provides a wide range of services to meet the financial needs of its growing customer base through approximately 700 full-service banking offices in Florida, Georgia, Tennessee and Melbourne in Australia. SunTrust's primary businesses include traditional deposit and credit services as well as trust and investment services. Through various subsidiaries the Company provides credit cards, mortgage banking, credit-related insurance, data processing and information services, discount brokerage and investment banking services (Decisioneering Staff, 1998). A small segment of SunTrust's commercial loan department focuses on lending to the construction industry. SunTrust has recently used Crystal Ball to perform Monte Carlo Simulations on hotel construction loans. This helps quantify the risks involved in evaluating these types of loans. Formerly, bankers would do worst case and best case analysis on construction loans when deciding on providing financing or not. Using Crystal Ball, a method has been developed to obtain a risk adjusted return on investment. Using this finding and comparing it to the bank's cost of funds helps decision-makers determine if the profitability is worth accepting the risk of approving the loan (Decisioneering Staff, 1998). The primary business goal of SunTrust is to analyse the risks associated with giving commercial loans and undertake decisions based on the risk assessment parameters. The changing scenario in the business environment has prompted SunTrust to undertake such a risk assessment process (Eppen et al, 1993). The economic recession and the sub-prime crisis were the major reasons for the company to re-look at their policies and access the risk factors properly, so that the company does not suffer any financial loss during such economic crisis. Need to improve business performance SunTrust already provides traditional deposit and credit services as well as trust and investment services. Thus, providing commercial loans become a natural extension to its business portfolio. The real estate growth in the US and Australia is phenomenon in the recent past and the company is trying to leverage this growth by expanding its business into commercial loans. However, in order to improve its business performance in this segment, it has to access the risk areas significantly and thereafter take the right decision (Evan & Olson, 2002). Requirements for decision making Thus, the company requires a robust decision making system which can help SunTrust to undertake decisions based on risk-analysis. The company may also leverage the system in its other services as well. For instance, if it plans to issue a credit card to a customer, based on the past credit history of the person, the bank may be able to understand the risks associated with giving a credit card to the customer and thereafter take an appropriate decision. However, in case of commercial loans, the risks associated are manifold as the sum of money given would be too high and would be dependent on the success of the project and the credibility of the client. Thus, the company plans to invest into a decision making system that would help in understanding the business environment, risks associated with a project and the returns expected from the services (Rothfeder, 2003). Business operations Currently, the company is using Crystal Ball method to obtain a risk adjusted return on investment. Using the findings from this method and comparing it to the bank's cost of funds helped the bank to determine if the profitability is worth accepting the risk of approving the loan (Eom, 1999). However, this system needs to be computersised and automated if the bank needs to implement it into a larger format. The system should be able to analyse the following data: Pro-forma income statement on a spreadsheet including calculations for debt service coverage Projected floating interest rate on the loan, Simulation to determine the probability that the DSC will fall within the level required by the take-out lender Calculate the expected return on investment, and Compare the calculated ROI with the cost of funds to determine if the spread is large enough to warrant accepting the loan. Task 2: Characteristics and capabilities of current DSS Presently, the bank uses the Crystal Ball method for generating risk adjusted return on investment. Using the findings from this method and comparing it to the bank's cost of funds helped the bank to determine if the profitability is worth accepting the risk of approving the loan. This helped the company to find out whether the commercial loan the bank has received application for is worth giving, whether the risks associated with the project is calculable and worth taking. The present system also helps the bank in finding the return on investment on the loan (Marakas, 2003). Decision problems The kind of decision support system (DSS) that SunTrust requires needs to be dynamic and flexible, using advanced computer technology. As DSS is an integral part to the company’s planning and strategy, it is important to create a roadmap that can provide SunTrust with important decision-making tools. The DSS to be designed for the company should be integrated with the other applications of the organisation and should be created in such a manner that it is being used at the planning and strategy stages itself. The DSS should provide a structured decision support (SDS) system, helping the managers to take strategic decisions after analysing the risks involved in a certain project (Power, 2002). DSS would help the company to identify, categorise and solve various business issues through an assimilation of technology, economics and human perceptions (Keen and Scott Morton). DSS may provide the following solutions to the company: Assisting the management to take decisions regarding various semi-structured issues Supporting and supplementing various managerial decisions, instead of negating them all together Improving the efficiency of the decision making process Assessing the risks factors associated with a particular loan Finding out the ROI on a loan DSS implemented in SunTrust SunTrust implement Crystal Ball 2000 decision support system, a simulation program that helps the company to analyse the risks and uncertainties associated with a certain project through the use of Microsoft Excel spreadsheet. Crystal Ball is added to Excel to help in producing a simulation result. As excel only provides fixed results, due to the nature of allowing the input of fixed values into the spreadsheet, Crystal Ball was inserted into Excel to help in generating results as per the changing scenario. Task 3: Case study The manager of SunTrust Banks has been entrusted with not just the problem of understanding the loan requirement and its possible outcome, but also to recognise the business opportunity in the project. First and foremost, the manager needs to analyse the past financial data of the company that has requested for the loan. In case the company does not have any past data than the manager should look into the credentials of the firm, the financial positioning of the founders and the estimated revenue that the firm is going to earn in the next five years. This will help in determining the financial health of the company and whether in case of default the promoters would be able to repay the loan amount (Wells & Hess, 2002). The manager needs to thereafter look into the project and analyse the investment potential in the project. The initial data suggests that the place where the company is planning a shopping town is an upcoming area and has noted a substantial growth in population during the last four years. Further, it is being predicted that the population in the area would become thrice the present population by 2020. After the through analysis of the given data, the ROI on the project can be arrived at. Nonetheless, after conducting an initial analysis, it can be said that the project is a profitable one. The population of Australia is growing at a rapid pace, with the coming of migrants into the country. This is also resulting in populating the bigger cities like Melbourne and therefore, people are looking at suburban areas for alternatives. Therefore, real estate is on a boom in these regions and is expected to continue the surge even in the near future. Thus, the manager may decide to approve the loan based on the given business scenario (Applegate, 1999). The manager should also leverage the data presented in this project to sell other products and services of the bank in the region. For instance, the growing number of people residing in Point Cook indicates that the people are also in need of other financial tools and products as well. The bank may tap into potential customers in the region and sell them various other products and services such as credit cards, mortgage banking, credit-related insurance, discount brokerage and investment banking services (Eppen, 1993). The project should not be seen in isolation; instead the manager should try to leverage the project data for selling other services and products in the region. It can also provide an excellent opportunity to come out with co-branded products. The bank may decide to partner with the construction company to provide mortgage and loans to the shop owners who would buy stores in the upcoming shopping town. Therefore, the project is not just a loan application but can provide new business opportunities for the bank as well. Task 4: DSS technologies used in SunTrust Banks Presently, the company is using Excel to undertake the risk analysis for a certain project and has inserted Crystal Ball to produce a simulated result. However, such a decision support system is totally data driven and can only produce result based on the fixed data put into the system. This system is not able to take into account various variables. Therefore, the system would not be able to calculate the risks if the economy gets into recession or is hit by situations such as sub-prime crisis. The manager has to calculate such risk factors on his own to arrive at a decision. The present system can only provide raw results based on the data provided by the company, which majorly comprises of the balance sheet, the projected profit and the investment requirement of the firm. Based on this information, the return on investment (ROI) is calculated on the project. After analysing the result, the manager takes the decision whether or not to approve the loan. However, there are other variables as well that needs to be taken care of while undertaking a decision, especially in a construction project. For instance, not only the estimated profit from the project needs to be analysed but the development of the area in the near future also needs to be taken into account. Further, the system should be developed in such a manner that it provides the flexibility of taking into account various variables as well. The DSS should be designed in such a way that not only it would access the risk associated in the project, but would also understand the opportunities and gap areas in the project. This will help in undertaking a well-rounded decision, taking care of all the loopholes and opportunities areas (Evan & Olson, 2002). DSS need to used in SunTrust Banks Therefore, it can be suggested that the company should try to shift from data-based DSS to a simulation-based DSS. As it already using a simulation system, it would be easier for the bank to implement it in a full-fledged manner. A simulation model would help the bank in capturing not only extensive data and detail about the project into the system but would also help in conducting various tests and experiments using the data to come out with a simulated scenario, which would be closer to the real environment. Thus, the business outcome of a project would be presented in a much more tangible format than in a data-based DSS (Evan & Olson, 2002). Further, a simulation model would be able to provide diverse scenarios for the same project, using different variables. Also, any change in data, such as investment figures or profitability, would provide different results as well. As the model has the capability to capture and save the results, the company would be able to present various scenarios to the management and take the right decisions by analysing the project from various angles (Evan & Olson, 2002). A simulation based model may help the company to undertake either dynamic or static analysis of the system. Therefore, the company would not just be able to analyse static data but also dynamic data based on the changing business scenario. The software used in this model may also provide time sequenced results and provide a prediction of the project on a timeline. Simulation is known as a descriptive tool which may be used not just for predicting the business scenario and analysing the risk factors but also for exploring other variables such as consumer behavior, market trends that might affect the project as well. Thus, this type of complex simulation model would help the bank to undertake decisions based on planned and strategic activities, understand the resources allocated for the project and analyse the results of various variables (Evan & Olson, 2002). Reference: Applegate, L. M., McFarlan, F. W., and McKenney, J.L. “Corporate information systems management: Text and cases”, Boston: Irwin/McGraw-Hill, 1999. Decisioneering Staff, "SunTrust 'Banks' on Crystal Ball for assessing the risk of commercial loans", Decisioneering, Inc., November 1998. Eom S. B. “Decision support systems research: current state and trends,” Industrial Management & Data Systems, 99(5), 213-220, 1999. Eppen, G.D., F.J. Gould, and C.P. Schmidt. Introductory Management Science (Fourth Edition), Englewood Cliffs, NJ: Prentice Hall, 1993. Evan, J. R. and D. L. Olson, Introduction to Simulation and Risk Analysis (2nd Edition), Upper Saddle River, NJ: Prentice Hall, 2002. Marakas, G. M. ”Decision support systems in the 21st century (2nd ed.)”, Upper Saddle River, NJ: Prentice-Hall, 2003. Power, D. J. “Decision support systems: Concepts and resources for managers”, Westport, CN: Quorum Books, 2002. Rothfeder, J. "Expert Voices: Icosystem's Eric Bonabeau," CIOInsight.com, June 16, 2003. Wells, J. D. & Hess, T. J. “Understanding decision-making in data warehousing and related decision support systems: an explanatory study of customer relationship management application,” Information Resources Management Journal, 15(4), 16-32, 2002. Read More
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