volume 58 article #7

A Management Game Providing Experiential Learning for Bankers

Chris A. Petermann, Harry P. Mapp, and Ross O. Love

Chris A. Petermann is Assistant Coordinator, Intensive Financial Management and Planning Support System (IFMAPS), and Harry P. Mapp is Regents Professor and Jean and Patsy Neustadt Chair, Department of Agricultural Economics, Oklahoma State University. Ross O. Love is Assistant Director, Oklahoma Cooperative Extension Service, Oklahoma State University. The authors gratefully acknowledge the Oklahoma Bankers Association for assistance, encouragement, and partial financial support in the development and implementation of the bank management game reported here.

Abstract

A bank management game designed to provide experiential learning for bankers is developed and tested in an Intermediate School of Banking. Primary and secondary data are used to estimate market volume and market share equations for five bank deposit categories and five loan types. These equations and other economic information provide the basis for the computerized game. Management decisions include interest rates on deposits and loans, advertising expenses, officer and employee salaries, service charges, and loan and investment strategies. Bank performance is measured in terms of income after taxes and market shares of deposits and loans.

Key words: bank game, bank management game, experiential learning, bank simulation model, bank management decisions.

Article <top>

Commercial banks face a serious problem in training new employees to understand the wide range of decisions made in different departments and how those decisions impact the bank’s performance. Employees in the loan department may understand that lowering interest rates charged on loans increases loan volume, and that loan volume is an important measure of performance in the bank. Yet, if new loans increase portfolio risk and result in greater loan losses, the bank’s net income and rate of return on assets may decline. Employees across departments may not understand that reducing interest rates charged on loans without reducing interest rates paid on time deposits, other things equal, reduces margins and lowers bank profitability. Understanding the interactions among decisions made by personnel throughout the bank requires training and experience. However, playing a bank management game that contributes to experiential learning can efficiently substitute for some training and experience.

Simulation and management games are effective in teaching agricultural economics concepts in farm and agribusiness management (Babb; Dahlgran; Schroeder, Tierney, and Kiser; Boehlje and Eidman; Boehlje, Eidman, and Walker; Schneeberger). Despite their usefulness, Oltmans reports that games related to financial management concepts are conspicuous by their relative absence in the professional literature. Games published in the finance area focus primarily on research applications, such as measuring risk attitudes and subjective probabilities (Nelson and Bessler). Bank management games are developed for and used in the classroom, but not necessarily published (Oltmans). An early bank management game developed by Fisher is similar in structure and complexity to the game reported in this article. However, Fisher’s game does not simulate the current economic and competitive environment in which rural commercial banks operate.

"Oklahoma Bank Simulation" is a commercial bank management game developed in the Department of Agricultural Economics at Oklahoma State University. The game is based on primary and secondary data for a number of rural banks in the state, and represents the current competitive environment for rural banks competing in market areas in which agricultural activity is important. Thus, the game can be adapted rather easily for use in bank schools and training sessions across the U.S. Results of a successful training session and evaluation of the game by a group of approximately 30 participants in the Oklahoma Bankers Association’s Intermediate School of Banking, conducted during June 1998, are reported in subsequent sections of this article.

Conceptual Framework <top>

The banking industry is undergoing tremendous change in structure and competitive environment. In some states, individual unit banks still exist, and in many states, individual banks, banks with multiple branches, and holding companies that own several banks co-exist. Regardless of structure, most individual bank offices compete with several other banks in a trade or market area. This management game represents a competitive environment with three competing banks in a market area that is heavily agricultural. Because much secondary data are available for counties as a political unit, the market area was defined as containing three competing banks within an agricultural county. However, for those playing the game, the market area for the three banks could be described as a town, city, county, or larger area.

In the game, three bank management teams in the market area compete for deposits and loans and purchase investments to maximize after-tax profits. Thus, each bank is assumed to maximize the following profit equation:

(1)

where NEAT is net income after taxes, LOI is income from loans, IVIE is income and expenses associated with the investment portfolio and purchase or sales of Federal Funds, DPIE is income and expenses associated with deposits, OE is other expenses paid by the bank, and TX is income taxes paid by the bank.

Five types of loans are represented in the game, including one-year agricultural production loans, 10-year agricultural real estate loans, 10-year real estate loans, two-year commercial loans, and two-year consumer loans. Each bank has an identical loan portfolio in the initial period of play. Loan losses occur randomly from the existing portfolio based on historic data on losses for each loan type. The volume of each loan type made by a bank in a given period depends upon the past loan volume, the interest rate charged by the bank, and the amounts spent for loan officer salaries and advertising. New loan volumes are also affected by the competing banks’ decisions on interest rates, advertising, and loan officer salaries. Thus, a bank’s income from loans (LOI) may be represented as:

(2)

where LMV is the market volume of the loan type, LBV is the bank volume of the loan type, LINT is the interest rate charged on the loan type, LOL is the random loan loss for the loan type in the current period, ADV is the advertising expense, LOOS is loan officer salaries, and CBD represents the decisions made by competing banks.

The volume of new loans of each type made by a bank during a decision period depends upon the volume of the loan type available in the market area and the amount of that loan type made by each bank. For example, only a limited volume of 10-year agricultural real estate loans is available to the competing banks due perhaps to limited economic growth in the market area, high interest rates charged by the competing banks, and the actions of nonbank competitors. While the factors that determine the market volume available differ somewhat for each loan type, a general relationship reflecting the volume of a loan type (LMV) available in the market area during the coming period is as follows:

(3)

where LVL is the volume of the loan type held by the competing banks in the market area at the end of the previous period, LAIR is the average interest rate for the loan type charged by the competing banks, CRS is county retail sales, SEF is a seasonal factor reflecting a larger volume for some loans available during the first or second half of the year, FPI is an index of farm prices received, ALOOS is the average loan officer salaries paid by the competing banks, LDPR is the average price of land in the market area during the current period, WFP is the Chicago Board of Trade futures price of wheat for the following July, and CBD is competing banks’ decisions.

Once the market volume of each loan type is determined, it is allocated to the competing banks. The factors that determine the allocation to a bank differ somewhat for the five loan types. However, a generalized relationship showing the market share of a loan type allocated to a competing bank (LBV) can be written as:

(4)

where LVP is bank loan volume the previous period, CHADV is the change in bank advertising expenses relative to the average change in the market area, AVLOOS is average loan officer salaries paid by the bank, CHNLO is the change in number of loan officers employed by the bank, CHAGI is the change in interest rate charged by the bank for a loan type relative to the change made by competing banks, CADV is the percentage change in advertising expense from the previous period, and CBD is competing banks’ decisions.

Each bank in the market area also competes for five types of deposits, including demand deposits, negotiable orders of withdrawal, money market deposit accounts, savings deposits, and certificates of deposit. Banks may impose a service charge on demand deposits and earn income. However, banks pay interest rates to attract deposits in the other four categories, and these expenses are significant components of their cost of funds. A generalized relationship for income and expense associated with deposits (DPIE) is as follows:

(5)

where DPMV is the market volume of the deposit type, BDVP is the bank’s market share of the deposit type the previous period, BDPIR is the interest rate paid by the bank on the deposit type relative to the average interest rate paid in the market area, ADV is the bank’s advertising expense, LOOS is loan officer salaries, AEMS is the average salary paid to all employees in the bank, and CSC is the change in bank service charge on demand deposits relative to the average change in service charge in the market area.

The market volumes of deposits available in the market area, and the allocation of those market volumes to the banks, determine bank deposits. Although the factors that determine the market volume of each deposit type differ somewhat, a generalized relationship for the market volume for a deposit type (DPMV) can be expressed as:

(6)

where DPL is market volume of a deposit type in the previous time period, DPIR is the average interest rate paid on the deposit type in the market area, ODPIR is the average interest rate paid in the market area on another deposit type, CCPI is the percentage change in county personal income from the previous time period, T is an increasing time trend, SEF is a seasonal factor to reflect changes in deposits in the first or last half of the year, and CRS is retail sales in the market area.

Deposits are also affected by the actions and decisions made by competing banks in the market area. If the other banks offer higher interest rates on deposits, spend more for advertising, and pay higher loan officer and employee salaries, they will receive a larger market share of new deposits. The factors determining the bank volume differ somewhat for each deposit type. However, a generalized relationship for bank market share for a deposit type (BDVP) is:

(7)

where CSC is the change in bank service charge on demand deposits relative to the average change in service charge in the market area, CADV is the change in the bank’s advertising expense relative to the average change in the market area, NLO is the number of loan officers employed in the bank during the current period, AEMS is the average salary paid to all employees in the bank, CAEMS is the percentage change in average bank employee salary, BDPIR is the interest rate paid by the bank on the deposit type relative to the average interest rate paid in the market area, and CBD is competing banks’ decisions.

Funds that are not loaned out to a bank’s customers are available for several types of investments, including six-month, one-year, and three-year government securities, and two-year and five-year tax-exempt municipal bonds. Funds that are not allocated to new loans or new investments are swept automatically into the Federal Funds market and earn the interest rate paid on Federal Funds for the period. If a bank allocates more funds to loans and investment than currently available for the period, it must purchase Federal Funds at the current interest rate to satisfy Federal Reserve requirements. So, a bank’s income and expenses from investments (IVIE) may be represented as:

(8)

where IV is the dollar volume of the investments by type, IRI is the interest rate earned on the investments by type, and FFIE is the income or expense associated with selling or purchasing Federal Funds.

A bank’s income is also affected by the costs of buildings and equipment, overhead, and state and federal income taxes. The costs of buildings and equipment are assumed constant for each bank during the game. Other expenses vary as a percentage of total assets for the bank. The amount of income taxes paid is dependent upon income from loans, income from investments (excluding some income from tax-exempt municipal bonds), income and expenses associated with deposits, and other expenses. A bank’s income tax liability (TX) may be written as:  

(9)

where LOI is income from the loan portfolio, IVIE is income and expenses associated with the investment portfolio, DPIE is income and expenses associated with deposits, OE is other expenses paid by the bank, and TXR is the tax rate appropriate for the taxable income of the bank.

Data and Estimation of Model Equations <top>

The model is based on bank data from several primary and secondary sources. Each bank included in the study provided primary data from a survey. The data provided are specific to each bank, and include advertising expenses, distance to competing banks in the market area, service charge income, number of loan officers and their average salaries, interest rates charged on loans, and loan losses on several classes of loans. Much of the secondary data for the banks are from the Federal Deposit Insurance Corporation (FDIC) Consolidated Report of Income (call reports). These data include the dollar amounts of the various deposit and loan categories, income from deposits and loans by category, and the dollar amounts of loans greater than 90 days past due and nonaccruing.

The study includes a total of 32 banks from 12 rural Oklahoma counties in which agricultural activity and income are very important. FDIC call reports provide secondary data for each of the 32 banks. Original and follow-up mailings, as well as telephone interviews, are used to obtain primary data for 12 of the 32 banks. Sets of three banks in close proximity are grouped to represent market areas because the market share equations require market area averages for interest rates, service charges, advertising, loan officer and employee salaries, and the number of loan officers. This grouping defines four market areas, each containing three competing banks that responded to the survey.

Decisions in the management game are made for a number of six-month time periods. Thus, the equations are estimated using semiannual data for the period June 1990 through December 1994. The data set, which includes primary and secondary data for the 12 banks for each of 10 six-month time periods, contains 120 observations for each variable. However, because a lagged variable is used in each of the deposit equations, only 108 observations are used in estimating market volume equations for deposits.

Market Area Deposit Volume Equations <top>

The market area deposit volume equations are estimated to identify factors that determine the total supply of the various types of deposits available in the market area for the coming period. Equations estimated for demand deposits, negotiable orders of withdrawal, money market deposit accounts, savings deposits, and certificates of deposit are presented in Table 1, along with goodness-of-fit indicators and t-statistics (in parentheses). Deposits are relatively constant or tend to rise slightly during the period of the analysis. Interest rates paid on deposits decline significantly. The equations explain a high proportion of the variation in deposit growth from period to period, and many explanatory variables are significant at the 5% level. The variable reflecting deposits lagged six months is highly significant in each of the equations, as expected. Deposits do not generally change substantially over a single six-month period, and the future level should be closely related to the previous level. Interest rates, county personal income, and county retail sales are also significant in determining the market area deposit volumes. The time trend variable is significant, but some deposits decrease slightly over the sample period while others increase. The variable adjusting for differences in deposit growth for the first half versus the second half of the year is significant for all deposit types. Demand deposits tend to be higher in the second half of the year, while the other deposit types tend to be lower.

 

 

Market Area Loan Volume Equations <top>

Market volume equations are also estimated for agricultural production loans, agricultural real estate loans, real estate loans, commercial loans, and consumer loans. The data set for these equations combines the banks in each of the market areas for each of the 10 time periods. Because the call reports do not provide the interest rates charged on loans, data from the bank surveys are used. Once the lagged variable is removed, a total of 36 observations are included in the estimation process. Agricultural production loans show a definite seasonal trend over the June 1990 through December 1994 period. The other loan classes are relatively stable, with a slight increase in the second half of the study period. Interest rates charged on loans decline substantially during the period used in the analysis. Each of the market area volume equations is presented in Table 2, along with goodness-of-fit indicators and t-statistics (in parentheses). The equations explain much of the variation in loan volumes from period to period, and a number of variables are statistically significant.

Variations in market shares of each deposit type and each loan type received by the three competing banks in the market area are explained in another set of 20 equations. Space does not permit presentation of the market share equations in this article, but interested readers are referred to Petermann for additional detail.

Components of the Simulation Model <top>

The market volume and market share equations provide the basis for the bank management game. The simulation model is written in the C programming language to run on a microcomputer in Windows 95. Figure 1 presents the general flow of the game. The model uses information contained in a history file to generate the beginning set of financial statements that are identical for the competing banks in each market area. Participants estimate the amount of funds available for new loans and investment during the coming six-month period and make a set of decisions for that period. The program administrator enters those decisions for each bank in each market area.

Once all necessary data are contained in memory, the program calculates market area average interest rates, service charge, advertising, loan officers, loan officer salaries, and employee salaries. These and other economic data combine to determine the new market area volumes of deposits and loans. Then, based on the market share equations, the program allocates the new deposits and loans to each bank. Mature assets and loans that are charged-off are removed from the portfolio and the history file is updated. Net income after taxes is calculated and a revised set of financial statements is produced. Finally, the program writes the revised output for each bank to a text file and saves it for the next period of play.

 

 

Figure 1. Flow of Model

The beginning output of the model, including the bank’s financial statements, loan and investment portfolios, and economic information for the next period of play, are presented in Tables 3­7. The statement of condition or balance sheet for each bank is shown in Table 3. Assets include cash and due from, five categories of government securities, and Federal Funds sold (if appropriate) the previous period. Assets also consist of five classes of loans and the value of bank premises and equipment. Liabilities include the five classes of deposits and the amount of Federal Funds purchased (if appropriate) last period. Capital and surplus does not change over time. Net income after taxes is accumulated in the retained earnings account. Selected financial ratios based on the bank’s balance sheet data are shown below the statement of conditions.

Table 4 shows the income statement for the previous six-month period and summarizes all income and expense items on a six-month basis. Loans and investments earn interest on the outstanding balances each period, and income is posted to the six-month income statement. Service charge income is based on the service charge decision made by each management team and the level of demand deposits, negotiable orders of withdrawal, and money market deposit accounts during the period.

Table 5 shows the decisions made by the management team for the previous six-month period, and which resulted in the current set of output. The maximum new loan volumes desired and the new loans made during the last six-month period are presented by loan type. The bottom portion of Table 5 shows the schedule of maturing assets during the next four years, first for investments and then for loans.

Table 6 provides current period data, as well as economic and statistical information relevant to decisions for the next six-month period. The top portion of the table presents county economic and market data for the last six-month period. Economic data include county per capita income, county retail sales, the average land value, an index of new housing costs, a farm price index, and the futures price for wheat. A comparison of the actual values in the current period with the range of values expected for the next period indicates the likely direction of change for each variable. Table 6 also shows the average interest rates paid by the three banks in the market area on each deposit account, the average interest rates charged on each type of loan, average service charges, and average advertising expenses. Also shown is market share information on deposits and loans for each bank in the county at the end of the previous period. After the initial period of play, these percentages differ for each bank.

Table 7 presents the bank’s portfolio of outstanding loans and securities. The loan or investment type is identified in the column heading and the outstanding balances and corresponding interest rates are displayed by period. The year heading indicates the period during which the loans were made or securities purchased.

 

 

 

 

 

 

Making Bank Management Game Decisions <top>

Estimating the amount of funds available for new loans and investments during the coming six-month period and making a set of management decisions are two key elements of the game. These game components, which should be explained in more detail during a teaching or workshop session, are discussed briefly in the following sections.

Estimating Funds Available for Loans and Investments <top>

Prior to making decisions regarding new loans and investments, participants must estimate the amount of money that will be available for the coming period. The information provided in Tables 3­7 and an available funds form are used in estimating funds available for new loans and investments.

Table 8 contains an estimate of funds available for loans and investments for participants’ initial set of decisions, but will differ for each bank in subsequent periods of play. Item (1), maturing assets, and item (2), cash and due from (the initial entries in Table 8) can be located in Tables 5 and 3, respectively. The anticipated change in deposits, item (3), is merely an estimate based on economic conditions presented in Tables 3 and 6 for the coming six-month period. In future periods, teams will have a history of deposit changes based on their decisions and those of their competitors. However, deposits are constant or increase slightly during the time period on which the model is based. Investments currently in the portfolio can be sold, but decisions to sell must be made by bank management teams. Cash received from Fed Funds, item (5) in Table 8, is shown in Table 3. Net income after taxes from last period, item (6), is shown in Table 4, and may or may not increase during the coming period. The amount of cash and reserve requirements, item (7), is calculated using data in Table 3, and the percentages are shown in Table 8. Based on the estimates presented in Table 8, participants have $19,107,638 available for new loans and investments in the coming period. If new loans and investments exceed the funds available, Federal Funds will be purchased automatically to satisfy Federal Reserve requirements. If new loans and investments are less than funds available, Federal Funds will be sold automatically.

Key Management Decisions <top>

Next, each bank management team makes a set of management decisions for the coming six-month period. A completed decision form for the previous six-month period is provided in Table 9. These decisions, which are identical for each bank, result in the financial statements shown in Tables 3­7.

As noted earlier, participants make decisions on loan interest rates, deposit interest rates, advertising expenses, loan officer and employee salaries, the volumes of new loans desired, and the volumes of investments to purchase and sell. Interest rates to be charged on new loans of each type must be expressed as an annual percentage rate. From Table 9, ag production is a one-year agricultural production loan with one lump-sum principal payment at the end of one year, ag real estate is a 10-year agricultural real estate loan with 10 equal principal payments, real estate is a 10-year real estate loan with 10 equal principal payments, commercial is a two-year loan with one-half of the principal repaid at the end of each year, and consumer is a two-year loan with one-fourth of the original principal repaid each six-month period.

For the deposit accounts (Table 9), participants enter the average interest rates they wish to pay on negotiable orders of withdrawal (NOWs), money market deposit accounts (MMDAs), savings deposit accounts, and certificates of deposit (CDs). No maximum deposit interest rates are specified in the model, but the bank must be able to loan or invest the funds at rates above those paid on deposits in order for the decisions to be profitable.

Other decisions (Table 9) include the service charge expressed as a percentage of total transaction deposits. There is no restriction on the rate, but a typical range is from 0.0% to 1.0%. Advertising should be expressed as a dollar amount to be spent by the bank on advertising and promotion during the coming six-month period, and influences the level of new loans and deposits obtained by a bank. Number of loan officers to be employed by the bank is expressed as a whole number, and influences the level of new loans obtained. However, the magnitudes of these effects differ for each type of loan. Average loan officer salary should be expressed as an annual dollar amount, with half paid in each six-month period. Higher salaries reward loan officers for increased productivity, so banks with salaries higher than the county average are likely to increase loans relative to their competitors. There is no maximum salary specified for the game, but if salaries increase more than earnings, net income for the bank will decline. Average employee salary should also be expressed as an annual dollar amount. Higher employee salaries have a positive effect on the level of deposits attracted by the bank, but must be balanced by increased earnings.

Participants enter the maximum dollar amount of new loans in each category that the bank would like to make in the coming six-month period (Table 9). These figures do not represent the amount of new loans the bank will make, but set the maximum desired by the bank. The bank may receive fewer new loans than desired, particularly if other banks have lower interest rates, more favorable loan officer salaries, and higher advertising expenses. Participants also enter the dollar amount of each investment that their bank will purchase in the next six-month period. The initial $300,000 of income earned each year from municipal bonds is exempt from state and federal income taxes. Income above that amount is taxed at corporate income tax rates. Participants can also enter decisions to sell any investment currently in the bank’s portfolio. The bank is a corporation, and income is taxed using the federal corporate income tax schedule for 1997.

 

 

Playing the Bank Management Game <top>

Development and implementation of this bank management game is due, in part, to the encouragement, assistance, and partial financial support of the Oklahoma Bankers Association (OBA). The OBA is actively involved in developing and conducting educational programs and training sessions for employees of commercial banks throughout the state. One such session is the Intermediate School of Banking conducted over a five-day period each June on the Oklahoma State University campus. This bank management game was introduced during the 1997 school, and played for the second time in 1998.

The Intermediate School of Banking begins on Sunday evening and concludes at noon on Thursday. With an enrollment of 25 to 30 bankers, the school involves lecture, discussion, and experiential learning. Training sessions generally include discussion of topics such as asset and liability management, lender liability, bank investments, nondeposit investment products, branch management, selling bank services, bank financial analysis, bank regulations, new technology, and the changing banking environment. Most sessions involve a speaker or discussion leader. An examination is conducted and the Intermediate School of Banking concludes with a luncheon and graduation ceremony.

The bank management game is played in a two-hour session each day for five days, and provides experiential learning as part of a training session rather than being the entire focus of the school. Those enrolled in the Intermediate School of Banking receive the bank management game instructions and beginning financial statements about two weeks prior to the initial session. They are asked to read the instructions prior to the first bank game session, and to come to that session prepared to make an initial set of management decisions.

The two-hour opening session focuses on the game instructions, estimating funds available for loans and investments, and decisions to be made. The bankers are grouped into nine bank management teams, each containing three bankers, to represent the three market areas or counties. Each market area is independent, so three banks (referred to as Bank 1, Bank 2, and Bank 3) in each county or market area compete directly for loans, deposits, and income. The three teams managing competing banks sit in different parts of the room for their discussion and decision making to ensure that their respective strategy discussions cannot be overheard by competing teams.

Team members discuss their strategies, calculate the amount of funds available for new loans and investments, and make an initial set of management decisions. Each team submits a decision form (see Table 9) that is reviewed for accuracy and clarity by a member of the group administering the game. Once decisions are reviewed, the team is free to leave for the evening. Following submission of the decision forms by all teams, the game administrators return to the microcomputer containing the bank game and enter the decisions, one team and one county at a time. Entries are verified and the results are reviewed on the screen for accuracy prior to printing.

The results are summarized prior to the second bank game session. Net income after taxes is an important measure of success resulting from the management decisions, and the banks are ranked from top to bottom according to net income after taxes for the initial period. Other measures of success for the period include the change in deposits, new loans made in each category, the volumes of municipal bonds purchased, and other factors. Transparencies are prepared to show the economic conditions expected to occur during the coming period and to present the interest rates available on new investments. Copies of the bank’s financial statements are made for each team member.

Participants have an opportunity to review the revised financial statements at the beginning of the second session and the results are discussed. The discussion focuses on the ranking of the nine banks in terms of net income after taxes and the volumes of new loans made by the banks. Some bank management teams fail to emphasize agricultural loans in their primarily rural and agricultural market area, and thus fail to serve the community. Some discussion of loan-to-deposit ratios across banks is useful because of the difficulty that many agricultural banks actually have in increasing this ratio. Some banks fail to purchase new tax-exempt municipal bonds, or sell bonds from their portfolio, and fail to support local public services, the aged, or the school children in the county.

The results, and specific decisions made by certain bank teams, typically produce some pointed humor during the discussion period. To make a specific teaching point, the game administrators often indicate that an "unidentified team" took certain actions, and do not embarrass team members. Once the discussion of results has been completed, the game leaders present changes in the economic conditions for the coming period and interest rates available for investment alternatives. Then each team estimates the volume of funds available for new loans and investments for the coming period and makes a new set of decisions. After all teams have completed their decisions, the game administrators return to the microcomputer, enter the new decisions, and prepare for the session the following day.

Similar bank game sessions are conducted during subsequent days of the school. The presentation of net income and discussion of other results is an important component of each session. Once the teams begin to estimate funds available for new loans and investments and make decisions, those administering the game visit with each team to answer questions. During the final decision period on Wednesday, some teams attempt new, different, and even desperate strategies to improve their income for the final ranking. For example, teams may fire several loan officers, cut employee salaries, or make significant increases in interest rates on all loan types. The final period decisions are reviewed carefully by the game administrators to ensure that all teams "play by the rules." Changes in the interest rate paid on certificates of deposit are limited to ý% in a six-month period because this rate is an average for all CDs in the bank. Teams may forget or ignore this limitation and attempt to drop the interest rate paid on certificates of deposit by a full percent or more.

During the final bank game session, discussion focuses on the results from the previous period’s decisions and the final net income rankings. Awards for outstanding performance are presented to each team member of the banks that have the highest accumulated income after taxes, the largest increase in income from the initial to the final period of play, the largest volume of agricultural loans, and the largest volume of municipal bonds. A top overall bank is also identified based on a formula that considers accumulated income, total loan volume, agricultural loan volume, municipal bond purchases, and other factors.

The game administrators also discuss the individual equations on which the game is based—identifying the variables that determine the volumes of deposits and loans available within a market area, and the variables that determine the market shares of deposits and loans attracted by the competing banks. Then the members of three bank management teams competing in a market area are asked to reveal their decisions for the final period on interest rates, loan officer salaries, advertising expenses, service charges, and loan and investment strategies. Participants are asked to predict, based on the equations of the model and the decisions made by competing banks, which of the three banks should have made the most new loans, attracted the most deposits, and earned the highest level of accumulated income. Next, bank teams provide the outcomes of those decisions in terms of market shares of deposits and loans, new loans made during the period, and net incomes. In general, participants are able to predict the bank that made the most income, generated the largest volume of new loans, and had the largest market shares of deposits.

Evaluating the Learning Experience <top>

An OBA Intermediate School of Banking participant questionnaire regarding the experiential learning offered by the bank management game provides a preliminary evaluation, and the results are very positive. The questions and responses are presented in Table 10. About 84% of those completing the survey feel that playing the bank management game enhances their learning experience at the school, and 84% feel that the game is highly effective in teaching key bank management concepts. About 88% of the participants feel that the game represents the current competitive environment in banking, and 100% of the participants feel that the game relates well to other sessions in the Intermediate School of Banking. The value of the bank management game as an experiential learning device is clearly evident in these responses.

The questionnaire also asks participants to indicate the relative importance of a number of factors in their learning from and enjoyment of the management game. Those factors and the participants’ rankings are shown in the lower portion of Table 10. All participants (100%) report that both the excitement of anticipating the results and the interactions with their team members are very important in their learning from and enjoyment of the game. About 96% of those responding feel that listening to the summary of results is very important, and 92% feel that linkages with other school topics are very important in learning from and enjoying the game. All participants (100%) feel that the competition with other teams is an important component, while 92% feel that both developing management strategies and making management decisions are very important factors in learning from and enjoying the management game. About 96% of the respondents value the game highly as a different type of learning experience. Finally, 88% and 84% of participants, respectively, indicate that interactions with other teams and discussion after the sessions ended are very important in learning from and enjoying the bank management game.

Participants also are asked to provide information about the primary strengths and weaknesses of the bank management game. Regarding weaknesses, one or more participants indicate that interest rates, particularly on agricultural production loans, are "a little high" in some cases. One participant would like more decisions to make, including perhaps the technical expertise of employees. Another would like more one-on-one instruction during the initial decision-making session. Several suggest that the discussion of the variables and equations presented in the final session would be useful during the initial session. Two participants indicate that the economic outlook data are limited. One feels that there is not enough conclusive data on which to base decisions.

 

 

Regarding the primary strengths of the game, several participants report that the game helps them learn more about how certain decisions affect bank profitability. Another strength is getting people who do not work in these areas to think about their decisions and the impacts on margins. The game is credited with teaching management skills and key bank concepts. Participants get to experience the effects of margins on profits. Several indicate that the game is educational and is an "eye-opener" in terms of factors that affect income and market share. The game shows the importance of management decisions and having to plan out strategies. One participant comments that the game teaches junior management the significance of senior management decisions.

Participants also report that the game gives them "the big picture" of working in a bank. Most feel that it provides a good learning experience and is enjoyable. Several note that the game is fun and competitive, and one says that "the game is great." A number of comments focus on the advantages of hearing the teams talking about their decisions and loan losses and wondering if they made any money. Some of the final comments offered by participants include: "this was the most fun learning experience of the Intermediate School," "great simulation," and "cool game!"

Summary <top>

Oklahoma Bank Simulation is a computerized bank management game that can be played in classroom or workshop settings. Participants experience the potential impacts of a wide range of management decisions on the overall performance of the bank. The simulation model is based on county market volume and market share equations. Data to estimate the equations are collected from a mail survey of rural Oklahoma banks and FDIC call reports. The equations identify factors that explain variations in the county market volumes of five classes of deposit accounts and five types of loans. Equations also explain variations in bank market shares for each type of deposit account and each loan type. These equations are programmed into the simulation model and provide the basis for determining the county market volumes of deposits and loans and the banks’ market shares of deposits and loans.

Bank management teams make a set of decisions, including the interest rates to pay on each deposit category, the interest rates to charge on each type of loan, advertising expenses, the number of loan officers and their salaries, salaries for other bank employees, service charges, the volumes of new loans desired for the coming period, and the amounts to invest in government securities and municipal bonds. Once the teams make their decisions, the data are entered on the microcomputer and the simulation model is run for the current period. Results of the decisions are summarized in five tables of output for each bank. The bank’s portfolio is updated to reflect the new loans and investments made in the period.

The bank management teams’ performance is based on net income in the current period, accumulated net income, increase in deposits, volume of new loans, loan-to-deposit ratio, volume of agricultural loans in the portfolio, purchases of municipal bonds, and market shares of deposits, loans, and investments. Decisions are made for and performance is evaluated over four six-month periods. Several awards are given for outstanding performance by the management teams.

Participants in the OBA’s 1998 Intermediate School of Banking evaluate the experiential learning provided by the bank management game. Most of the participants feel that playing the game enhances their learning experience and indicate that the game represents the current competitive environment in banking. All of the respondents feel that the game relates well to other sessions of the school. Key factors contributing to learning and enjoyment are the excitement of anticipating the results, and the interactions with team members in making management decisions.

References <top>

Babb, E.M. "Agribusiness Simulators for Management Training." S. J. Agr. Econ. 17,2(1985)193­97.

Boehlje, M.D., and V.R. Eidman. "Simulation and Gaming Models: Application in Teaching and Extension Programs." Amer. J. Agr. Econ. 60(1978):987­92.

Boehlje, M.D., V.R. Eidman, and O. Walker. "An Approach to Farm Management Education." Amer. J. Agr. Econ. 55(1973):192­97.

Dahlgran, R.A. "Management Simulates: A Tool for Fostering Experience-Based Learning of Agribusiness Management Concepts." Agribus.: An Internat. J. 3(1987):403­12.

Fisher, G.D. "The Development of a Management Game for Oklahoma Rural Banks." Unpub. M.S. thesis, Dept. of Agr. Econ., Oklahoma State University, Stillwater, December 1973.

Nelson, R.G., and D.A. Bessler. "Subjective Probabilities and Scoring Rules: Experimental Evidence." Amer. J. Agr. Econ. 71(1989):363­69.

Oltmans, A.W. "The Leverage Game: Teaching Growth, Leverage, and Risk in a Dynamic, Experiential Framework." Agr. Fin. Rev. 55(1995):100­17.

Petermann, C.A. "Factors Affecting Rural Bank Performance in Oklahoma." Unpub. M.S. thesis, Dept. of Agr. Econ., Oklahoma State University, Stillwater, May 1997.

Schneeberger, K.C. "Gaming as a Farm Management Teaching Device: A Development and Analysis." S. J. Agr. Econ. 1,1(1969):53­58.

Schroeder, T.C., W.I. Tierney, Jr., and H.L. Kiser. "Experiential Learning Through Trading Agricultural Commodities." Agr. Fin. Rev. 55(1995): 89­99.

 

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