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The Effect of Heterogeneous Risk on the Adoption of Remote Banking Technologies Keldon J. Bauer Illinois State University Scott E. Hein Texas Tech University Introduction Bankers are adopting remote banking technologies for two primary reasons: It enhances their competitiveness.
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The Effect of Heterogeneous Risk on the Adoption of Remote Banking Technologies Keldon J. Bauer Illinois State University Scott E. Hein Texas Tech University
Introduction • Bankers are adopting remote banking technologies for two primary reasons: • It enhances their competitiveness. • Customers can access their account anytime/place. • Customers can be served further from the bank. • Hannan and McDowell (1990) ATMs. • Bouckaert and Degryse (1995), and Degryse (1996) Phone-banking, and remote banking in general.
Introduction 2. They hope to reduce costs. • Technology in general has improved the cost structure of banks. • Daniel, Longbrake and Murphy (1973). • Hunter and Timme (1986, 1991). • Humphrey and Pulley (1997). • Wheelock and Wilson (1999). • With remote banking technologies, successful adoption means customers must also adopt. • What are the important variables to the customer?
Theory • We assume that the customer derives utility from having a bank account, designated f(x). • We assume that adding a remote access technology to the account adds utility to the overall function, designated dihi(x). • The “i”s represent different remote banking technologies. • d is an indicator variable.
Theory Under Certainty: Under Uncertainty: or where
The Optimal Configuration • The f(x) is the cost of the base bank account. • The gi(x) represents the cost of the ith added remote access.
Theory • From the consumer’s perspective adoption depends on three things: • Added utility offered – the more utility the more likely they will adopt. • Marginal cost to the consumer – the cheaper the more likely they will adopt. • The risk premium. • A function of subjective probability, and utility from remote banking technology.
Data • We used the 1998 and 2001 Surveys of Consumer Finance (SCF). • To proxy for utility: • # of checking accounts, • # of savings accounts, • $ amount in those accounts.
Data • To proxy for risk premium: • Risk aversion variable. • Take substantial financial risks expecting to earn substantial returns. • Take above average financial risks expecting to earn above average returns. • Take average financial risks expecting to earn average returns. • Not willing to take any financial risks.
Data • To proxy for budget constraint: • Age (of head of household), • Log of Income (household), • Education (a series of dummy variables), • Using other forms of internet financial management.
Data • Interaction with budget variables. • There are two reasons why there might be interaction between risk aversion and budget constraint variables. • In the adoption decision, the risk aversion variable only captures the shape of the utility function, not the budget constraint as well. • Most of these variables also might capture heterogeneous risk assessment.
Methodology • Base Adoption Logit Model:
Methodology • Conditional Logit is Based on the following Multinomial Logit:
Methodology • Conditional Logit:
Table 2 - Conditional Logit P(Internet|Phone Banking)
Table 3 - Conditional Logit P(Phone Banking|Internet)
Conclusions • Risk perception is not homogeneous. • If the new technology is relatively new, a familiar technology should be offered as a parallel remote access choice until the consumer is comfortable with the new technology. • Any market expansion (defense) is short-lived, since the subjective risk assessment disappears quickly.
