Uncertainty and culture in bank loan decisions

OMEGA Int. J. of Mgmt Sci.. Vol. 17, No. 3, pp. 297-308, 1989 0305-0483/89 S3.00 + 0.00 Printed in Great Britain. All rights reserved Copyright ~C 1989 Pergamon Press plc

Uncertainty and Culture in Bank Loan Decisions

P C N U T T I

Ohio State Universi ty, USA

(Received June 1988; in revised form November 1988)

Simulations of loan applications were evaluated by senior bank executives in terms of their prospects for approval and risk to determine the influence of organizational culture and payback uncertainty on loan decisions. The influence of the participating banker's decision style, based on the Junglan typology, was also determined. Eight simulated loans were constructed that had four types of cultures and high or low uncertainty in pay back prospects. Evaluations of the ratings of these loans found that culture was a more important determinant of loan approval and risk assessment than either uncertainty or the banker's personal decision style. Bankers in an analytic culture were inclined to approve loans, in a consultative or speculative culture bankers were more apprehensive bat would make these same loans, in a charismatic culture bankers were unsure about the advisability of making the same loans. The implications of these findings for Improved practice in bank loan decision making are discussed.

Key words--behavioral decision making, uncertainty, culture, decision style

I N T R O D U C T I O N

THE RECENT RASH of bank failings have been widely reported, with predictions of more to follow. Fifty institutions have been merged or forced to reorganize in 1986. The US Govern- ment Accounting Office (GAO), a watchdog agency for Congress, estimates that 43% of the saving and loan institutions could be considered insolvent [31]. The federal insuring agency has asked Congress for $22 billion over the next five years to bail out these banks. According to the GAO, a key cause of failure has been question- able commercial loans, in which the banks took on unacceptable levels of risk in making loans. The widespread image of the 'conservative banker' is swept aside by these events, suggesting several interesting research questions con- cerning loan decision making practice. For instance, how do bankers react to loans with different levels of uncertainty? Also of interest is how bankers assess applicant motives and the

The author wishes to thank Robert Morse and Associ- ates, Charles Huntington, and Harry Blythe for their help in carrying out this study.

type of information that is preferred to make a loan decision.

To deal with these issues, this paper explores the influence of the banker's decision style, organizational culture, and payback uncertainty in loan decision making. Simulations of loan applications were constructed and given to senior bank officials for evaluation. These applications had either a low or high payback uncertainty and one of four cultures. Uncertainty was defined by the likelihood that a borrower's cash flow would not be large enough to repay the loan. Four cultures were constructed to capture types of arguments that loan applicants can use to justify a loan and modes of inference that loan officers use to assess a loan application [8, 17, 20]. The bank executives rated eight simulated loan applications, indicating their likelihood of approving each loan and their perception of its risk. Each participating bank executive filled out a questionnaire which was used to determine his/her decision style [20, 21].

Analysis of the loan's ratings was used to determine how uncertainty, culture, and the bank executive's decision style influenced loan

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298 Nutt--Uncertainty and Culture in Bank Loan Decisions

approval prospects and perceptions of risk. These analyses were used to answer four questions. First, they determined which culture, if any, is favoured by the US banking industry. Second, the approval and risk assessment ratings were linked to levels of uncertainty, to determine how bankers react to plausible changes in uncertainty as they make loan decisions. Third, the banker's personal decision style was linked to loan approvals to determine if bankers with a particular style were more likely to approve loans and to determine how bankers with each style assessed loan risk. Statistical interactions among these factors suggest how combinations of uncertainty and culture, uncertainty and decision style, and culture and decision style identify conditions that influence loan decisions. The culture- decision style interaction determines how each of the four cultures influences bankers with a particular style in their loan evaluations. The decison style-uncertainty interaction examines how bankers with a particular decision style respond to high and to low uncertainty during loan evaluations. Finally, the culture- uncertainty interaction assesses how high or low uncertainty combines with a particular culture to influence loan decisions.

CULTURE AND DECISION MAKING

Culture is defined as a set of beliefs, views, or ideas that are learned and then shared, which can be used to mark off a group as distinct from other groups [11, 18]. Culture is not an innate property of a work unit, organization, or industry. It evolves, adapting to changes that emerge, and is reinforced by successful use. Culture has symbolic significance for an organization, re- vealing ideologies that must be incorporated into decisions. For example, some banks rely on automated credit scoring using accounting data to make decisions which create an analytic culture.

Several approaches have been proposed to study culture that call for the study of 'forms' on the one hand and 'substance' on the other. Forms can be studied by observing an organization's rites, rituals, or ceremonies [28]. Retire- ment parties, newspaper announcements of promotions, the company picnic and the like are offered as events that can be profiled to capture attributes that make up a culture. To examine

substance, the researcher must study standard operating procedures (SOPs) and decisions made by an organization to infer the values evoked. Values that express core ideals seem to have more importance in organizational decision making than those derived from the company picnic. However, the difficulty in specifying the values that lie behind decisions has made cultural studies based on substance largely unsuccessful [4, 11, 18].

Mitroff and Kilmann [17] suggest a way around this problem by using the notion of cognitive style, as defined by Jung [9]. A close correspondence between a manager's ideals and his/her preferred cognitive style has been ob- served in several studies [e.g. 4, 21], suggesting that core ideals about decision making can be captured by the Jungian archetypes. Each of the Jungian types has a clearly defined and vali- dated structure to draw inferences and collect data pertinent to decision making [25]. These preferences can be used to sort organizations according to their dominant decisional culture and to measure the impact of views about this culture.

The Jungian typology

The MBTI (Myers-Briggs Type Indicator) was developed to measure Jung's cognitive types [19], and has been found to have conceptual, construct, and predictive validity [2, 12, 30]. The MBTI creates classification categories based on Jung's theory of psychological types [9, 10]. An individual's preferences for kinds of data and ways to process the data provide a way to identify the core values that are used to reach decisions [27]. Either sensing or intuition can be used to acquire information. A sensing (S) individual prefers hard data that deal in specifics. The intuitive (N) individual prefers qualitative and subjective information that de- scribes possibilities. The sensing person looks for 'what is' while the intuitive looks for 'what might be'. Thinking and feeling approaches can be used to reach a decision. Thinking (T) stresses logic and formal modes of reasoning, while feeling (F) considers the decision in personal terms, the personal stakes of people affected. Thinking generalizes, while feeling per- sonalizes. According to Jungian theory, people develop a preference for one of these data types and data processing approaches which defines their cognitive style.

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Researchers have made logical extensions of Jungian theory to suggest how a manager with each style would prefer to make decisions [e.g. 1, 3, 13, 15, 20, 22, 26]. Drawing on this reasoning, four styles of decision making sug- gestive of a culture can be defined:

(a) Managers with a ST (sensation-thinking) style have preferences for careful analysis with hard data. This creates a dependency on formal analysis and suggests an analytic decision culture.

(b) An NT manager has intuition-thinking preferences. This suggests a speculative decision culture, in which information is sought to discover the influence of external factors, such as demand or utilization, speculating about plausible outcomes to make a decision.

(c) The SF (sensation-feeling) manager has preferences that suggest a consultative culture. The need for objective data and consideration of people calls for .talking with others using tactics, such as bar- gaining, to sort and reconcile data.

(d) Managers with a NF (intuition-feeling) preferences cater to people with track records and the organizations they represent, using politics and mutual adjustment [14] to balance the conflicting claims of people with power [5]. These preferences suggest a charismatic culture.

Culture in banking

Approaches used by banks to manage risk illustrate the development of cultures in the banking industry. These risk assessment approaches were identified by Robert Morse and Associates: as different examples of how successful banks deal with risk in their loans. A review of these practices shows how Jung's cognitive types can be mapped to cultures in the banking industry.

The Wachonia Bank and Trust used procedures that were associated with a ST or 'analytic culture'. Wachonia's approach treated risk in the same way as extending credit, in which loan decisions were justified through

2 This information was drawn from a report prepared by Robert Morse and Associates; (1986) Four Risk Man- agement Approaches.

financial analyses. Daily monitoring of indicators was carried out using three day moving averages to measure Wachonia's 'total exposure'. Automated systems were used to alert management whenever indicators fell into zones labeled potentially troublesome.

The Northwest Bank of Minneapolis used a generic process of operating procedures and steps to identify risk in their loans. With this inventory as a guide, loan officers worked with troubled companies to take remedial steps that minimized the bank's risk exposure. Norms were set for exposure. Periodic credit review reports were prepared to allow the bank to deal with broader issues, relevant to minimizing the chance of a loss. The NT or 'speculative culture' seems apparent in Northwest through its generic process designed to identify possibilities.

The Philadelphia National Bank charted a committee to identify risks and develop procedures to manage these risks. The committee met regularly to review presentations by respon- sible managers for each type of loan they make, called product lines. The committee rated each product (loan type) using 19 criteria along a five point scale, from minimal to critical risk. Weights were established for each criteria. This reliance on S data and the F logic in groups is similar to SF tactics, suggesting that a 'consultative culture' was used to draw inferences.

The Chase Manhattan Bank assigned risk management to account managers because these individuals were thought to have the experience and judgment needed to identify questions and answer them. Councils were set up to reduce the likelihood that an important issue would be overlooked. The councils brought unit managers and functional specialists together to review on-going loans and report their recommendations to the appropriate manager. The council could advise, but decisions were left to senior managers. This reliance on judgment and delegation based on experience suggests an NF or 'charismatic culture'.

S T U D Y D E S I G N

Both field and laboratory studies have been used to capture how decisions are made. A laboratory investigation with students was ruled out for this research because such studies lack external validity. Naive participants, such as students, cannot draw on their experience to

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role play loan decision making in a bank. The participation of experienced bank managers seemed essential. Field studies can capture these views, but proved to be impossible to carry out, for several reasons. First, banks were reluctant to allow researchers the access required to study their loan decision process. Such access can be quite time consuming, potentially disruptive, and likely to reveal practices and policies the bank wants to keep confidential. Second, research calls for redundancy, repeating the same loan decision to measure error. Banks are not apt to have loan applications sufficiently alike to be treated as replicates. Finally, no single bank or banks locally available could provide a rich cross-section of views. A random sample of banks was infeasible because there was no way to ensure that the top executives of the selected banks could be enticed to par- ticipate. Non-respondents in such studies are often high, creating serious threats to internal validity.

Faced with the need for field research and real limitations in collecting the required data, simulations provide a compromise that captures several attributes of the field study. The participation of top bank executives is a key require- ment of field research. To tap the views of top bank officials, participants were drawn from bank executives who attended training programs offered by Robert Morris and Associates, a well-known organization that offers executive level training for bankers. This approach had two virtues. First, it ensured that diverse banks and a broad cross-section of viewpoints would be represented. Data for the study were drawn from three classes, or cohorts, taken over a three year time period from top bank executives who worked in 38 banks across the United States. The data base is not large, but does deal exclu- sively with top executives; unlike many studies of decision making. Second, by having the managers with executive level positions make simulated decisions in a classroom environment, experimental control could be exercised. Ex- perimental control was needed to ensure that respondents followed instructions and did not consult with others as they made their loan decisions. These precautions allowed the bankers' responses to be treated as independent observations. Finally, controlled conditions ensured that questions would be clarified in a consistent manner, and allowed for debriefing.

The simulation

Banks periodically consider loan applications identified by their loan officers. These applications are prioritized to form a plan to let out available money for loans. To make the simulated loans realistic, several bank executives, identified by Robert Morris and Associates, were asked to describe their loan decision process. These descriptions were analyzed to identify common types of commercial loan applications and information available when a loan decision was made. These steps were taken to ensure that the decision simulations created situations that an experienced bank manager would have confronted.

The loan application in the simulation called for a $600,000 loan to finance the purchase of a computer controlled robotic welder costing $750,000. The loan was secured by a lien on the equipment. Payback was scheduled for three years with quarterly payments of $50,000, or $200,000 per year, plus interest. The interest was set at 110% of the prime rate. To capture the impact of factors that may influence the loan decision, two factors, uncertainty and culture, were systematically varied in the simulated loan applications.

Uncertainty. Interviews with bank executives that had considerable experience in loan decision making were used to identify the key considerations in making loans. All agreed that repay prospects was the single most important concern and that loan size was relatively un- important. Using this guidance, high and low levels of uncertainty were created using the likelihoods of various cash flow outcomes that could be realized by the loan applicant to repay the principal obligation. All of the dollar values used in the cases were suggested by bankers.

In the simulations, a 'low' level of uncertainty had a 90% chance of a cash flow of $280,000.00 and a 10% chance that the applicant's cash flow would be $180,000, or $20,000 below that needed to repay the loan. As a result, the low uncertainty situation had only a small chance of a default. The 'high' level of uncertainty had an 80% chance of a $300,000 cash flow and a 20% chance of a $150,000 cash flow, or $50,000 below that needed to repay the loan. For this condition there would be a higher chance of a default, which was used to represent a 'high' level of uncertainty.


By defining uncertainty in this way all loans had the same expected value for cash flow:

0.9 ($280,000) + 0.1 ($180,000) ffi 0.8 ($300,000) + 0.2 ($150,000) ffi $270,000

This array of outcomes has two implications. First, the expected value of cash flow exceeds the principal obligation suggesting that all loans would be approvable, disregarding the banker's views about uncertainty. Second, the cash flow expectations for each of the simulated loans was identical. This creates a series of loans that differ only in terms of the study factors of uncertainty and culture. As a result, all of the simulated loans were approvable, but not uniformly desirable.

The loans differed in terms of their risk implications. The low uncertainty loan had a 10% chance of a $20,000 cash flow shortfall and a high uncertainty loan had a 20% chance of a $50,000 shortfall. The high uncertainty loan also had an 80% chance that the applicant would make a 50% return, making the organization a good long term customer. The low uncertainty load had a high chance (90%) of a smaller return (40%), making this applicant's prospect as a future customer a bit poorer.

These values allowed several kinds of risk preferences to be expressed. Loans could be favored that had the largest cash flow or the best prospect for a favorable cash flow. Alterna- tively, decisions could have been made to avoid loans with the smallest cash flow or the greatest prospect of an unfavorable cash flow. Prefer- ences regarding these options were collected using a survey in the debriefing that followed the cases. The bankers, using a one to four scale (1 =most important, to 4=leas t important) rated each of the four kinds of risk in the simulated cases. These ratings were used to determine if bankers preferred loans with the largest cash flow, avoided loans with the smallest cash flow, sought loans that had the most certainty in favorable estimates, or rejected loans with the largest uncertainty in unfavorable estimates. This information was used to elaborate the preferences expressed in the simulations. For example, bankers may try to avoid the chance of a loss or seek long term viable customers. Note that a bank's losses are direct (costs of a default) and their gains indi- rect, based on future business prospects.

The rationale behind the uncertainty factor stems from behavioral studies that have ex- plored how people deal with decisions that have the same expected value [23]. Some executives prefer low uncertainty-low return options and others prefer high uncertainty-high return options, when these options have the same expected value. For instance, some corporations, such as Lockheed and TRW, have followed a policy of seeking department of defense sub-contracts (low uncertainty-low return), suggesting a preference for certainty. At the same time, corporations, such as Boeing and General Dynamics, have pursued a policy of seeking prime contracts from the department of defense (high uncertainty-high return). In re- lated studies, middle managers were found to be risk averse, preferring low uncertainty-low return options [24]. These views suggest that a banker's attitude toward uncertainty may be an important factor influencing how loan decisions are made.

Culture. 'Cultural scenes' that offer sufficient content to capture 'insider language' that has salience to a participant must be used in simulated decisions [18]. Varying key features in this language provided a way to capture aspects of culture and measure its effects. Following this logic, culture was based on the Jungian cognitive types, as shown in Table 1, using descriptions and ideas drawn from the literature [6,8,15,17,20,25]. The culture factor was specified using both loan applicant characteris- tics and the bank's loan assessment process. A loan application offers two types of information: purpose, in this case indicating the value of the equipment to the applicant, and the arguments used by the applicant to make a case for the loan. The loan assessment process was described in terms of the analysis and validation steps that were taken by the loan officer, as shown in Table 1.

The ST or analytic culture was captured by loans for equipment to cut the applicant's operating costs. The equipment was expected to reduce manufacturing expenses and thereby improve profit. To make a case for the loan, the applicant submitted financial statements for the past five years, attempting to show a stable record of profitability. The loan officer cited a careful analysis of the applicant's financial position, in which calculations and details were checked to ensure that the profitability track

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record was accurate, to support making the loan.

The SF or consultative culture was captured by loans that were sought in response to the demands of the applicant's best customers. To make a case for the loan, the applicant demon- strated the depth of loyalty of customers, offering client lists and testimonials. The loan would allow the firm to be responsive to the needs of its best customers. The loan officer also cited support from members of the bank's board of directors who believed that the applicant had an excellent future to support making the loan. Other loan officers were described as concurring with these assessments and preliminary reviews of a loan committee were cited as supportive.

The NT or speculative culture was represented by loans from an applicant attempting to increase capacity to meet a forecasted increase in demand. The applicant cited a strong three-year growth record in sales to make a case for the loan. To justify making the loan, the loan officer had made favorable and unfavorable assump- tions about sales in the application, finding that the equipment would allow the firm to capitalize on apparent trends.

The NF or charismatic culture was captured by loans that permited the applicant's CEO to develop new product ideas. The applicant made a case for the loan by giving illustrations of the firm's record of innovation. To justify making the loan the loan officer had checked on the firm's business prospects by seeking out and consulting with trusted people who knew the firm and its product such as its key customers, suppliers, and competitors who were also bank customers. These investigations suggested that the equipment could improve the visibility of an innovative product in the marketplace.

Construction of the simulated loan applications

A 2 x 4 experimental design was used. Each of the simulated loans had one of the four cultures and one of two levels of uncertainty, as shown in Table 2. All combinations of these two

factors (culture and uncertainty) define how the eight loans considered by the bank executives differed. The orthogonal nature of the culture and uncertainty factors eliminates multicolin- earity and allows unfettered estimates of factor effect sizes to be made. The loans were summar- ized as a report which described a loan officer's assessment and contained two rating scales. The simulation for loan application 1 (Table 2) is shown in Table 3.

Data collection procedure

Participants were drawn from bank executives who attended Robert Morris and Associ- ates executive training sessions, given in part by the author, over a three year period. The participants came from banks across the United States and its possessions. Information was taken from application forms to determine each participant's organizational level. A review of job title was carried out to insure that all participants included in this study were senior level bank executives. Each of the 38 bankers included in this study met this test.

The bankers were given the simulated loan applications and asked to treat them as candi- dates for commercial loans. They were told that the purpose of the exercise was to learn about their views, and that there were cut right or wrong decisions. No lectures or handouts were provided until after all data had been collected. (Each banker received an analysis of his/her decisions as a part of the training program.)

Two dependent variables were used to capture each banker's evaluation. Prospect of loan approval and perceived loan risk were used to provide separate aspects of a loan assessment. Bankers oriented toward approving a loan may or may not perceive it as risky: some perceived risk may be present in the mind of a banker whether a loan is approved or not. Thus, approval and risk represent two distinct ways to view a loan decision. The rating scales devised to measure approval prospects and perceived risk are shown in Table 3. The scales were

Table 2. Construction of simulated loan applications

CULTURE UNCERTAINTY ^

ST or Analytical NT or Speculative SF or Consultative NF or Charismatic

I Low Loan application Loan application Loan application Loan application I 3 5 8

High Loan application Loan application Loan application Loan application 2 4 6 8


Table 3. Loan application I

You are considering a loan application from a new hank customer. The firm is asking for a loan of $600,000 to finance a purchase of computer controlled robotic welders costing $750,000, to be secured with a lien on the equipment. The equipment is expected to reduce manufacturing expenses and thereby increase the company's profit. The firm has asked for a loan of 3 years to be repaid with quarterly payments of $50,000, or $200,000 per year, plus interest. If you approve the loan you will set the interest at 1 IO% of the prime rate.

Financial statements for the past five years are available and indicate a stable, consistently profitable, organization. Analysis of the applicant's financial position suggests that there will be a 90% chance that the firm's cash flow wiRE be as high as $280,000 annually and a 10% chance cash flow will be as low as $180,0OO annually to repay the $200,000 principal obligation. The calculations and the details of the data acquisition process were carefully checked and found to be accurate. Assume that other factors are favorable.

Please rate your likelihood of approving this loan on the following scale:

Lean toward Reject rejecting Uncertain

II1111111111 0 25 .50

Lean toward adopting Adopt

75 I00

Please indicate the level of risk you believe is associated with making this loan on the following scale:

Little Typical Considerable No risk risk risk risk

0 25 50 75

I I

Unacceptable risk

'1

reversed to force the rater to read the scale anchors and discourage them from marking both scales at the same location. The scale anchors had two purposes. First, anchors per- mit the average ratings of the participants to be interpreted in terms of an expected action. Second, the anchors help to create a common perception of scale increments and the zero point in the mind of bankers as they rate the loan applications. When all raters perceive the same zero point and scale increments these ratings have an interval scale and parametric statistical methods can be used to analyze the results.

The bankers were asked to review the eight loan applications and indicate their view of each loan's approvability and its risk by marking the rating scales provided at the bottom of each loan summary. They were instructed to check the point on each scale that best represented their views (see Table 3). Data was recorded as a value from 0 to 100 in increments of one unit from each scale. The bankers were asked not to review previous ratings as they made their decisions. To make this comparison difficult, the loans were prepared on separate pages. These precautions were taken to try to keep the bankers from comparing the loans. If an explicit comparison between loans is made, a dependency can result. Such a dependency calls for the use of analytic techniques that require large data bases to find statistically significant differences [32].

After completing their evaluation of the loans, the bankers filled out the MBTI to determine each bank executive's decision style [19]. The MBTI scoring rules were used to place the bank executives into the ST, NT, SF, and NF style categories. Decision style is the final explanatory variable considered in the study.

Reliability Reliability was tested to determine consist-

ency in the banker's ratings of the simulated loans. The same set of loan decisions were made at two separate points in time by ten bankers who were given the same eight loan applications to rate after six months had elapsed. This provided a test-retest reliability measure. Re- liability was measured by a factor with two levels (first and second rating of the loans). A one-way fixed effects ANOVA was used to test whether the reliability factor was significant. The error variance in the ANOVA measures individual differences (e.g. capriciousness) and measurement error, such as perceived scale am- biguity [32]. The ANOVA compared the test- retest reliability factor, measured by variation between the first and second set of decisions made by each banker, against the unexplained variance, using an F test of statistical significance. A statistically significant difference would indicate that the first set of ratings differed from the second set, implying that the bankers' choices were unstable and thus difficult to capture using the simulations developed for


this research [21]. This test was not significant, suggesting that the simulations provided a reli- able way to capture the views of bankers.

Analysis

ANOVA and repeated measures techniques were used to analyze the data. The repeated measures approach may be needed in spite of the precautions to ensure independence in the ratings assigned to loans. Participants may re- tain an image of salient aspects of past loans in their mind and use this image to make subse- quent ratings, making the loan ratings dependent. A repeated measure ANOVA deals with these dependencies by blocking for the respondent and computing the residual to account for the dependent ratings. In an analysis of this type, the respondent serves as a block, and experimental units (e.g. loan application factors and decision style) within a block represent different instances of a treatment. These precautions proved to be unnecessary. Both analyses produced the same results, suggesting that the loan ratings could be treated as independent and that standard ANOVA techniques could be used.

The ANOVA was used to determine whether the decision style, culture, or uncertainty factors and their interactions influenced the approval and risk ratings of the eight loan applications. An ANOVA was run for each dependent variable, treating the 38 bank executives with a particular decision style as replicates. For factors with three or more levels, ANOVA results do not identify which of the factor levels pro-

duce significant differences. To make this deter- mination, each factor level that make up culture or decision style factor must be compared to the remaining levels using the equivalent of a t test. For instance, there are four decision styles and four cultures calling for six comparisons (four things taken two at a time) of the effects of these four cultures and four decision styles. A statistical technique called the Duncan Multiple Range Test or DMRT was used to make these comparisons. The DMRT makes a posteriori test of the differences between the dependent variables (approval and risk ratings) for the decision style and culture categories [32]. The DMRT com- pares the approval and risk ratings for all combinations of a factor's categories, two at a time, using a t test with a 0.05 level of significance. The test automatically adjusts significance levels to account for the number of non-independent tests being conducted.

DISCUSSION OF RESULTS

As shown in Table 4, decision style, culture, and uncertainty influenced the prospects of loan approval and risk perceptions of the bank executives. These findings make a strong case for these three variables as explanator3." factors in the loan decisions of bankers. Table 4 also summarizes the results of the Duncan Multiple Range Test (DMRT). When the same letter code for two or more categories occurs these categories produced the same result. Categories with different letter codes were dissimilar (P ~< 0.05). The results of the Duncan test and

Table 4. The effects of culture, decision style and uncertainty on the loan decisions of bankers

Approval Risk prospects DMRT assessment DMRT

Culture Analytic 75 A 51 A Speculative 62 B 62 B Consultative 67 A/B 57 B Charismatic 54 C 69 C

P ~ 0.0002 P ~ 0.0001 Uncertainty

Low 69 A 56 A High 60 B 63 B

P ~ 0.0002 P ~ 0.003 Decision Style

ST executives 17 67 A 60 A NT executives 5 53 B 61 A SF executives 5 66 A 56 A NF executives 11 65 A 61 A

(38) P ~ 0.046 NS Interactions

Uncertainty*Decision style NS NS Culture, Decision style NS NS Culture • Uncertainty NS NS


the anchored rating scales help to interpet the findings.

Culture The culture variable was the most significant

factor in the study. Culture influenced both the approval (P ~<0.0001) and risk ratings (P ~<0.0001). The DMRT found that loans stemming from an analytic culture were seen as the most desirable (with an average rating of 75) and had the lowest risk rating (51). Using the anchored rating scales in Table 3 to interpret these results, the bankers 'lean toward accept- ing' loans in analytic cultures and find these loans to have 'normal risk'. By way of contrast, loans in a NF or charismatic culture were adoption rated at 54 and risk rated at 69. This suggests bankers were 'uncertain' about loaning money for innovative projects and assessed the risk in such a loan application as 'approaching considerable'.

The bankers reacted to the NT or speculative culture and the SF or consultative cultures in a similar manner. The prospects of adoption in a SF culture was rated at 67 and the risk assessed at 57. In a NT culture adoption was rated at 62 and risk at 62. The bankers saw these cultures as producing a bit more than normal risk and were somewhat positive about approval prospects.

Decision style

Decision style determines how the bankers' personal views influenced their decisions. These views may differ from the prevailing culture, which captures the nature of the organization's decision rules. The decision style factor was significant for approval (P ~< 0.05) but was not significant for risk assessment. The bank executives with a ST, SF, and NF style rated the approval prospects of the loans nearly alike (65 to 67). The NT bankers rated the loans at 53. The NT bankers were unsure about the loan's approvability as compared to ST, SF, and NF bankers who viewed these same loans somewhat favorably.

These findings suggest that the personal decision style of bank executives has less impact on their decision making than the culture in which they operate. The bankers responded to loan decisions in ways that swept aside their personal preferences. Differences in loan decisions were far more explainable by cultural than

personal style preferences. The exception seems to be the NT bank executive. Bankers with an NT style were more conservative, possibly indicating an inability of forecasts and 'what-if' analyses to render loan decisions tractable. NT bankers were less apt to buy into any rationale offered by a loan application, compared to bankers with a ST, NF, or SF decision style.

Taken together these findings suggest that an analytic culture dominates the decision making of bankers. Strong financials were the key factor in loan approval. Innovative projects cannot demonstrate this attribute so they were avoided. Buy-in by key people and forecasts of business prospects were viewed as useful, but less likely to gain approval than a track record of profitability. Bankers seem to stress historical data and disregard data depicting future prospects in their loan decisions.

Uncertainty As one would expect, the bankers were more

apt to approve the low uncertainty loans and found them to have less risk than the high uncertainty loans (P ~< 0.05). Loans that had low uncertainty were adoption rated at 69, compared to a rating of 60 when uncertainty was high. These same loans were risk rated at 56 when uncertainty was low and 63 when uncertainty was high. These differences merit in- terpretation. First, loans regardless of their uncertainty were seen as approvable. This posture is logical because of the expected value arguments described in the study design section. The most likely outcome produces a cash flow large enough to repay the loan. Second, the views of loans with low and high uncertainty were more alike than one might expect. Using the anchored rating scales to interpret the ratings, the bankers 'leaned toward approving' loans whether they had high or low uncertainty in pay back prospects. Both the low and high uncertainty loans were rated as having a bit more than normal risk. The banker's ratings of their risk preferences confirmed these findings. There were no differences in the preferences for low uncertainty-low pay off and high uncertainty-high pay off loans. These findings suggest that bankers tend to be risk takers in granting loans.

These conclusions have several implications. First, the simulated cases produced judgments that were logical, suggesting that the loan simu-

Omega, Vol.

lations presented realistic and understandable cases for the bankers to consider. Second, bankers saw loans with any prospect of a loss as producing m o r e than normal risk. This implies an unrealistic posture toward loan risk. Loans with perfect certainty (one hundred percent assurances of pay back) will never occur. The notion of expectancy, which allows a realistic treatment of stochastic properties in key parameters for a loan decision, may be lacking in bank decision practice. Third, bankers were apt to approve loans justified by analysis and tend to disregard all other justifications. This preference for the analysis of historical financial data may be another weakness in the loan decision making process.

Interactions

None of the interactions proved to be significant. This finding has several implications. First, bankers did not alter their views of a loan when their personal style matched (or failed to match) a given culture. Bankers with a particular style did not favor cultures that matched their style. For instance, bankers with a ST style did not react any more positively to a ST (analytic) culture than any other culture. This suggests that the dominant (ST or analytic) culture in banking sweeps aside personal con- cerns. It also may suggest weaknesses in bank decision making because innovative projects tend to be ruled out and service and expansion arguments for a loan were viewed as nonper- suasive. Second, neither the effects of culture nor decision style influenced uncertainty. High uncertainty, for instance, did not lower a loan's acceptability or increase its risk when it occurred in a particular decision style or culture. These findings suggest that the effects of culture and decision style generalize across the uncertainty conditions considered in the study.

C O N C L U S I O N S

Thirty-eight senior bank officials rated simulated loans, constructed to vary in terms of culture and uncertainty. The approval and risk ratings of these loans were correlated with the culture and uncertainty factors in the cases and with the cognitive make up of the bankers. Analysis revealed that bankers preferred an analytic culture. Loan applicants with carefully constructed financials and a profitability tract

17, No. 3 307

record were more apt to be approved than applicants attempting to serve the needs of key customers or applicants seeking to meet fore- casting demand increases, and far more apt to be approved than applicants with innovative ideas. This preference for analysis may be sweeping aside viable rationales for loans based on service needs, forecasts, and innovation. Organizations that have realistic projected increases in sales and a tract record for innovation may identify new loan customers that can be profitability cultivated by banks, with low risk.

Culture dominated the other factors considered in this study. In particular, culture was far more important than a banker's decision style in making loan decisions. Bankers responded to loans in ways that swept aside their personal views of how the loan decision should be made. The speculative, or NT banker, however, seems to have reservations about this practice. Bankers with a NT style were less apt to approve a loan, suggesting that they may be frustrated in carrying out their preferred means of decisional assessment. This suggests that emphasis on what-if like questioning, norm development, and search for loan options may be practices that can reduce the number of loan defaults currently threatening many banks with failure.

Bankers treated uncertainty in estimating pay back in a somewhat idealistic manner. They seem to want loans that produce no chance of a loss, a circumstance that can never occur. Bankers may not understand the inherent stochastic properties of decision parameters, suggesting that a greater emphasis on dealing with expectancy in training programs may be needed. The use of confidential psychological testing, to entice bankers to reflect on their personal style and the bank's culture, may also be useful.

REFERENCES

1. Blaylock BK and Rees LP 0984) Cognitive style and the usefulness of information. Mgmt Sci. 15, 74-91.

2. Buros OK 0978) The Eight Mental Measurement Year- book, I. The Gryphon Press, NJ.

3. Churchman CW (1971) On the Design of Inquiring System: BaMc Concepts in Systems and Organization. Basic Books, New York.

4. Dandridge TC, Mitroff II and Joyce WF (1980) Organ- izational symbolism: A topic to expand organizational analysis. Acad. Mgmt Rev. 5, 77-82.


5. French J Jr and Raven BH (1959) The bases of social power. In Studies in Social Power (Edited by Canwright D.), Institute for Social Research, Ann Arbor, MI.

6. Hellriegel D and Slocum JW Jr (1975) Managerial problem-solving styles. Busin. Horizons, December, 29-37.

7. Hellriegel D and Slocum JW Jr (1978) Management: Contingency Approaches, 2nd edn. Addison-Wesley Reading, MA.

8. Hellriegel D and Slocum JW Jr (1980) Preferred organizational designs and problem solving styles: Interesting companions. Hum. Syst. Mgmt 2 (2), 151-158.

9. Jung CG (1923) Psychological Types. Routledge and Kegan Paul, London.

10. Jung CG (1970) Collected Works: Sic Psychological Types (Edited by McGuire W). Princeton Univ. Press, NJ.

1 I. Jelinek M, Smirchich L and Kirch P 0983) A code of many colors. Admve Sci. q. 28 (3), 331-338.

12. Keen P and Bronsema G (1981) Cognitive style research: A perspective for integration. In First Inter- national Information Systems Conference Proceedings, Boston, MA.

13. Kilmann R and Thomas KW (1975) Interpersonal conflict handling behavior as reflections of Jangian personality dimensions. Psychol. Rep. 37, 971-980.

14. Lindblom CE (1965) The Intelligence of Democracy: Decision Process Through Adjustment. Free Press, New York.

15. Mason RW and Mitroff II (1973) A program for research on management information systems. Mgmt Sci. 19 (5), 475-487.

16. Mitroff II and Kilmann R (1975) On evaluating scientific research: The contributions of the philosophy of science. Technol. Forecast. Social Change 8, ! 63-174.

17. Mitroff II and Kilmann R (1975) Stories managers tell: A new tool for organizational problem solving. Mgmt Rev. 64, 18-28.

18. Morey MC and Luthans F (1985) Refining the displace- ment of culture and the use of scenes and themes in organizational studies. Acad. Mgmt Rev. 10 (2), 219-229.

19. Myers IB (1963) Manual: The Myers-Briggs Type Indi- cator. Educational Testing Service, Princeton, NJ.

20. Nutt PC (1979) The influence of decision styles on the use of decision models. Technol. Forecast. Social Change, 14, 77-93.

21. Nutt PC 0986) Decision style and its impact on managers and management. Technol. Forecast. Social Change 30, 39-62.

22. Robey D and Tasgert W (1981) Measuring managers" minds: The assessment of style in human information processing. Acad. Mgmt Rev. 6 (3), 375--383.

23. Slovic P, Fischhoff B and Lichtenstein S (1977) Behav- ioral decision theory. A. Rev. Psychol. 28, 1-28.

24. Swalm RO (1967) Utility theory--insights into risk taking. Hart,. Bus. Rev. November-December, 123-137.

25. Taggert W and Robey D (1981) Minds and managers: On the dual nature of human information processing and management. Acad. Mgmt Rev. 6 (2), 187-195.

26. Torbert WR (1983) Executive mind, timely action. Persuasion 6 (2), 3-21.

27. Toulmin S (1979) Knowing and Acting: An Invitation to Philosophy. Macmillan, New York.

28. Trice HM and Beyer J (1984) Studying organizational culture through rites and ceremonials. Acad. Mgmt Rer. 9 (4), 653-669.

29. Trice HM, Belasco J and Alutto J (1969) The role of ceremonials in organizational behavior. Ind. Labor Relations Rev. 23, 40-51.

30. Tzeng O, Outcalt D, Boyer S, Ware R and Landes D (1984) Item validity of the Myers-Briggs type indicator. J. Personality Assessment 48 (3), 255-256.

31. US Government Accounting Office (1986) Publication Number GAO 86-114, October.

32. Winer BJ (1971) Statistical Principles in Experimental Design. McGraw-Hill New York.

ADDRV_.SS FOR CORnESPONOI~CE: Professor Paul Nutt, Gradu- ate Program in Hospital and Health Services Adminis- tration, The Ohio State University, 1583 Perry Street, Columbus, OH 43210, USA.

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Uncertainty and culture in bank loan decisions