“New Technology, Productivity and

8/3/2019 New Technology, Productivity and

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Second Conference ofINTERNATIONAL FORUM ON COMPARATIVE

POLITICAL ECONOMY OF GLOBALIZATION

New Technology, Productivity and

Contemporary Banking

Costas LapavitsasSchool of Oriental & African Studies, University of London

Paper presented at the Second Annual Conference of theInternational Forum on the

Comparative Political Economy of Globalization, 1-3 September 2006, Renmin

University of China, Beijing, China.


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Department of EconomicsSchool of Oriental and African StudiesThe University of London

Second Conference ofINTERNATIONAL FORUM ON

COMPARATIVE POLITICAL ECONOMY

OF GLOBALIZATION

To be held at Renmin University of ChinaBeijing, 1-3 September 2006

Paper title:

NEW TECHNOLOGY, PRODUCTIVITY AND

CONTEMPORARY BANKING

Author:

Costas Lapavitsas

School of Oriental & African [email protected]

August 2006First Draft Not to be Quoted


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New Technology, Productivity and ContemporaryBanking

Costas Lapavitsas

Abstract

This paper considers the impact of new technology (telecommunications, electronics

and information processing) on the operations and functions of commercial banks.

The focus of analysis is on the US banking system. The paper first examines the

impact of new technology on general productivity across the economy. There has

been significant acceleration of productivity growth since 1995 but not in banking.

Moreover, the mechanisms through which new technology affects productivity are far

from clear. The paper then turns to the impact of new technology on the money-

dealing and financial intermediary functions of banks. The introduction of ATMs and

e-banking have transformed the operations of banks at the branch level, but they have

not resulted in significant cost reductions and productivity increases. The adoption of

information technology, meanwhile, has allowed for technical assessment of risk

through credit scoring thus making it possible for banks to lend to large numbers of

individuals and small enterprises. The business of banking has become more

differentiated and focused on information processing.


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1. Introduction

Banking has been transformed during the last three decades due to two broad

trends: first, institutional and regulatory change associated with financial liberalisation

and, second, technological change. The former includes lifting of controls on prices

and quantities of credit, on the activities of financial institutions, and on international

capital flows. The latter includes introduction of new technology in electronics,

telecommunications and information processing. The two trends are closely connected

and continually interact with each other; nonetheless, they are also distinct and it is

analytically instructive to keep them separate. This paper examines some aspects of

the impact of technological change on banking.

The first issue considered in the paper, however, is the impact of new

technology on productivity in the economy as a whole. Banking is an intermediary

activity, the returns of which derive largely from industrial and commercial profits or

from private incomes. Consequently, for the sources of banking profit to grow in a

sustained way there must be systematic increases in productivity across the economy,

reflecting the general introduction of new technology. The attitude of banks toward

new technology depends, in turn, on its expected impact on bank profitability. A

complicating factor in this respect has been the pronounced effect that new

technology has had on the services sector, which includes banking. Thus, section 2

considers the impact technological change on general productivity during the last

three decades, focusing on the US economy. New technology has had complex and

ambiguous results, despite the upturn in productivity since 1995. Moreover, the

mechanisms through which new technology affects productivity are not clear.

In this light, section 3 examines the introduction of new technology in banking,

again primarily in the USA. The impact of technological change on banking has

inevitably been multifaceted. This makes it necessary to focus on selected aspects of

banking in this paper. Thus, analysis turns primarily to the key functions of banks as

money-dealers and financial intermediaries. The impact of technology is considered

through the introduction of ATMs and electronic payments as well as the adoption of

credit scoring techniques by banks. It appears that new technology has not

significantly reduced bank costs, or raised productivity in banking in these respects. In

view of the high profitability of banking in recent years, this creates an obvious

conundrum: if banks have failed to compress costs, how have they succeeded in


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making high profits? However, this topic cannot be dealt here and requires separate

treatment.

It should be mentioned, finally, that this paper is work in progress, part of a

broader study of the transformation of finance during the last three decades. Analysis

relies on a critical survey of the mainstream economics literature on this topic,

drawing primarily on the US banking system, which is also the most thoroughly

studied in the literature.

2. Technological change and productivity in the US economy

Technological change since the late 1970s has been most pronounced in

electronics, telecommunications and information processing. Despite the rapid

introduction of new technology - especially in the USA - there were no significant

productivity improvements at the aggregate macroeconomic level for at least two

decades after the mid-1970s. In mainstream economics this phenomenon has been

called the Solow paradox, namely that You can see the computer age everywhere

but in the productivity statistics (Solow 1987: 36). However, around 1995 the

outlook for productivity growth changed dramatically in the USA. It is important for

our purposes to consider the current relationship between new technology and

productivity as well as the debates that surround it.

Productivity calculations by mainstream economists show that US labour

productivity began to rise rapidly around 1995 following two decades of relative

stagnation. Consider the following estimates by Oliner and Sichel (2000):

Table 1. Contributions to Growth, 1974-1999.

1974-90 1991-95 1996-99

Growth rate of output 3.06 2.75 4.82

Contributions from:

IT capital 0.49 0.57 1.10

Other capital 0.86 0.44 0.75

Labour hours 1.16 0.82 1.50

Labour quality 0.22 0.44 0.31

Multifactor productivity 0.33 0.48 1.16


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Table 2. Contributions to Labour Productivity

1974-90 1991-95 1996-99

Growth rate of labour productivity 1.37 1.53 2.57

Contributions from:

Capital deepening of IT capital 0.81 0.62 1.10

Capital deepening of other capital 0.37 0.11 0.14


Multifactor productivity 0.33 0.48 1.16

Much the same picture emerges from Jorgenson, Ho and Stiroh (2004):

Table 3. Sources of US Output and Productivity Growth

1959-73 1973-95 1995-2003

Private Output 4.21 3.06 3.90

Hours worked 1.36 1.57 0.85

Average Labour Productivity 2.85 1.49 3.06

Contributions from:

Capital deepening of IT capital 0.21 0.40 0.92

Capital deepening of other capital 1.19 0.49 0.83


Total Factor Productivity in IT 0.09 0.24 0.53

Total Factor Productivity in non-IT 1.03 0.10 0.61

The measured upsurge in productivity growth led initially to a debate on

whether the increase indicated a regime shift. Some argued that the change was long-

term and due primarily to the cumulative effect of new technologies (selectively,

Oliner and Sichel 2000, 2002, Jorgenson and Stiroh 2000, Jorgenson, Ho and Stiroh

2002, 2004, Stiroh 2001, Nordhaus 2001, Basu, Fernhald and Shapiro 2001, Triplett

and Bosworth 2001, Fernhald and Ramnath 2004). On the opposite side stood Gordon

(1999a, 1999b, 2000) who claimed essentially that the upsurge was due to rapid

growth within the Information Technology (IT) sector, and was contained within it.

To put it crudely, for Gordon, computers raised productivity but only in the business


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of making other computers. By the early 2000s, however, Gordon (2003, 2004) - see

also Dew-Becker and Gordon (2005) - acknowledged defeat, and a consensus

gradually emerged with the following features.

First, it is now generally accepted that in 1995 a structural break took place in

the trend of US productivity growth. Labour productivity, in particular, has

accelerated rapidly, registering growth rates similar to those of the golden era of the

1950s and 1960s. This is not a cyclical result, as was confirmed by even faster

acceleration of labour productivity after the burst of the technology bubble of 1999-

2000. Judging by productivity figures alone, this phenomenon represents the end of

the long downturn that engulfed the US economy after the first oil crisis of 1973-4.

Solows paradox has indeed vanished in the USA.

Second, the catalyst for this regime shift was provided by extremely fast

productivity growth in the microprocessor industry in the 1990s (Triplett 1996,

Jorgenson and Stiroh 2000). Rapid productivity growth in the microprocessor sector

caused a decline of price approaching 30% in the mid-1990s, inducing substantial

falls in computer prices and leading to a boom in IT investment in the second half of

the 1990s. The rise in IT investment led to productivity gains in the sectors producing

IT and less so in the sectors using IT. In time, a foundation was provided for

acceleration of productivity growth across a broad front of economic activities.

Third, rapid acceleration of Total Factor Productivity (TFP) was also observed

after 1995. As is well known, TFP purports to capture the effect of unknown, residual

factors on productivity, typically interpreted as a non-specific effect of technological

change. An easy blunder in this connection (not infrequently found in the pages of the

press) is to interpret the recent gains in TFP as evidence of the impact of IT change on

productivity. This is, of course, incorrect since TFP growth refers by definition to

factors unknown. Nonetheless, the acceleration of TFP growth after 1995 is further

evidence of regime change in productivity growth trends.

Fourth, productivity in the services sector seems also to have picked up,

eventually responding to growth in IT investment. The original slowdown of

productivity since the mid-1970s was very evident in services. This has been

sometimes referred to as Baumols disease, i.e. that the inherent nature of services

makes productivity gains less likely than in the primary or secondary sectors (Triplett

and Bosworth 2000). In this respect, it is important that the most significant gains in

productivity since the 1995 have been in services, mostly in wholesale, retail and


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financial trading (though in securities trading and not in banking, despite the fact that

banks have been leaders in introducing new technology). Within the mainstream this

is taken as evidence of the broad-based nature of the transformation in productivity

growth. There are, of course, very significant problems when it comes to measuring

the output of the services sector, but mainstream economists are now claiming that

Baumols disease has been cured (Triplett and Bosworth 2003a, 2003b, 2003c).

However, the nature of the cure has not been specified.

These are, in my view, the salient features of the current mainstream

consensus on productivity change and new technology in the US economy. Yet,

despite the emergence of consensus, the issue of the relationship between new

technology and productivity since the 1970s cannot be considered fully settled. A key

problem in this respect is that most of the contributions to this debate (whether for or

against the consensus) are macro-level, econometrics papers. These studies (including

those whose results were summarised in the tables above) normally engage in growth-

accounting, decomposing output growth in the standard Solow (1957) manner:

dY/Y = dA/A + s dL/L + (1-s) dK/K (1)

Where Y is output producing according to the production function Y = AF(L, K) and

A, L and K are a multiplicative factor, labour and capital inputs, respectively. The

ratio dA/A captures Total Factor Productivity (or Multi Factor Productivity) and can

be estimated as a residual from (1). MFP is typically used to account for a bag of non-

specified factors including, technological innovation, managerial innovations and

knowledge spillovers.

Consequently, the opposing views on the trend of productivity growth are

based entirely on econometric theorising at the macro level. It follows that the various

contributions offer little insight into how new technology affects the manner in which

labour is undertaken, including the impact of computers and other IT on the labour

process. Supporters of the consensus certainly believe that new technology has had a

pronounced effect on productivity, especially in the services sector, but the literature

leaves us in the dark regarding the mechanism through which productivity

improvement has taken place. This is not surprising, given the macroeconomic

outlook, the methodology adopted and the data employed by the studies concerned.


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The uncertainty regarding the actual mechanisms of productivity improvement

is made worse as the productivity miracle at the macro level appears to be confined

to the USA. Thus, while IT has spread in Western Europe along similar lines to the

USA, productivity growth in the former (including TFP) has slowed down during this

period (OMahony and van Ark 2003, Gordon 2004). Britain presents the most

awkward problems in this regard, since it has registered substantial IT investment in

the late 1990s and can hardly be accused of eurosclerosis (the usual culprit in

mainstream explanations of worse performance by Europe compared to the USA). Yet,

British productivity growth has declined during this period. 1

Similarly problematic, though for different reasons, is the further observation

that US productivity growth actually accelerated after the end of the New

Technology bubble, 1999-2000, despite the ensuing collapse in IT investment.

Indeed, productivity has continued to improve in the USA even though IT investment

had not reached the levels of 1999-2000 even by 2006. Thus, if new technologies are

behind the productivity upsurge in the USA since 1995, the process is clearly deeper

and more complex than it appears at first sight.

For more detailed answers, therefore, it is important to look at micro (firm)

level studies. There has been a modest output of such studies in the USA, which

broadly agrees that new technology has indeed wrought a productivity transformation.

However, it is notable that no paper has succeeded in putting forth a generally

accepted explanation for the putative transformation of productivity. The strongest

argument in this respect is that IT has favoured the employment of highly skilled

college graduates, thus leading to changes in work and organisation practices within

companies and resulting in productivity improvements (Brynjolfsson and Hitt 2000,

2003, Brynjolfsson, Hitt and Yang 2002). These effects are sometimes captured with

the term intangible capital, which presumably increases through the introduction of

new technology and lies at the disposal of corporations. 2 In similar spirit, it has been

argued that new technology has resulted in intangible output, such as better services

and more varied choice for customers. The implication of these unconvincing

1Recent attempts to account for this paradox have resorted to the rather desperate argument that UScorporations somehow deploy new technologies more effectively than British ones (Bloom, Sadunand van Reenen 2005, Sadun and van Reenen 2005). It is hard to know what to make of this claim abetter cultural fit between contemporary Americans and computers, perhaps?2

It has even been argued that the stock market somehow succeeded in capturing the effect of thismysterious capital (also called e-capital) in the valuation of New Technology stocks in the late 1990s,i.e. just before the crash (Hall 2000, 2001).


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arguments is that the acceleration of productivity has been going on for some time

since the late 1970s, but was badly measured.

It is worth stressing in this connection that there are indeed horrendous

difficulties regarding the measurement of productivity, as has been explained by

Griliches (1994). These difficulties are ineluctable when economists attempt to

distinguish between the value and the material sides of production. Moreover, US

productivity measurements use hedonic indices to deflate price series, unlike

European countries, though this practice appears not to have caused a systematic

measurement difference in favour of the USA. Nonetheless, hedonic indices could

still conceal a major problem for which there is no clear answer in the literature.

Namely, if the output of the IT sector is considered to have risen due to the greater

power of computers (even if the same volume of computers is actually produced), it

follows that the measurement of output by wholesalers and retailers would also

automatically rise. However, it is possible that wholesalers and retailers might have

continued to do exactly what they have always done, i.e. sell x boxes of (more

powerful) computers per period. In other words, the data would be registering an

improvement in the productivity of retailing and wholesaling without any actual

changes in work organisation and use of technology having taken place. This is a far

from negligible problem given that the current productivity upsurge is supposed to

draw its strength mostly from wholesaling and retailing. 3

Concluding this brief discussion, there is little doubt that a new phase of

substantially faster productivity growth has emerged in the USA after 1995. The bulk

of the gains in productivity have been in the services sector (with the exception of the

banking sector), while manufacturing productivity has not registered significant

improvement (with the exception of the IT sector). Mainstream economics attributes

the change in productivity to the introduction of new technology, mostly

telecommunications and information processing. By deploying growth accounting at

the aggregate macro level, mainstream economists claim that the long-awaited

beneficial effect of computers on the functioning of capital (especially in the sphere of

circulation) has at last taken place.

3 The usual example for the transformation that has been apparently wrought on retailing/wholesaling

by new technology is WalMart and its big box system. It is notable that the appalling labourconditions at WalMart that have been well-documented in the press and elsewhere are typically ignoredby academic papers.


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It is also notable that there have been no strong explanations of the

microeconomic mechanisms through which new technology might have raised

productivity. A prevalent assumption - often implicitly made - is that new technology

improves the efficiency, organisation and range of individual work effort (particularly

within the services sector) thereby inducing a regime shift in productivity growth. But

the mechanisms and characteristic features of this putative change are rarely specified,

particularly for office work that is typical of much of the service sector. The most

influential argument in this context links the productivity transformation to a nebulous

intangible capital, presumably placed at the disposal of corporations by new

technology. This intrinsically weak argument is not strengthened by the observation

that new technologies have apparently produced this mysterious capital only in the

USA, or even only for US corporations.

The difficulty of finding a persuasive microeconomic link between

productivity and new technology no doubt derives from the complex and non-specific

character of current new technologies, especially when compared to technological

transformations of the past. The introduction of new technologies in production of

steel and chemicals in the late nineteenth century, for instance, improved productivity

for these basic commodities and thus had broader beneficial effects for productivity

across the economy. But information technology is a diffuse, general purpose

technology that applies across various fields of labour in a non-specific way

(Bresnahan and Trajtenberg 1992). Its impact is thus slow, complex and indirect,

along lines similar to the introduction of electricity and the telephone, rather than to

introduction of specific production technologies (David 1990). Consequently, it might

not be easy to differentiate between the effect of contemporary new technology on the

productivity of labour as opposed to its effect on the intensity and effective duration

of labour.

Neoclassical studies of productivity growth typically ignore the possibility that

new technologies might have raised the intensity of labour, especially in the services

sector. It could be, for instance, that the rise in output per worker in recent years owes

much to information technology eliminating gaps and breaks in the work effort during

normal working hours. This seems more plausible than the notion that new

technologies have created a nebulous intangible capital placed at the disposal of

corporations. The putative effect of new technologies on productivity might also be

related to the gradual colonisation of private time by computer-related work. The


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beneficial effect on output could be the result of new technology prolonging the

effective duration of labour, both through unpaid overtime and through the invasion

of family or personal time. On casual evidence alone, it seems plausible that

information technology has had a strong impact on the intensity and duration of

service labour. The efforts of neoclassical economists in explaining the recent

productivity shift might have borne better fruit had they also addressed the issue of

whether new technologies have forced workers to labour harder and for longer hours.

3. New technology and banking

The general context within which US banks have operated since the mid-

1970s, therefore, has been that of productivity slowdown for two decades followed by

rapid growth since 1995, though not in banking itself. Broadly speaking, the

introduction of new technology has resulted in more favourable profitability

conditions for banks only since the mid-1990s. Throughout this period banks have

been at the forefront of introducing new technology with complex and multifaceted

effects on their operations.

Ascertaining the impact of new technology on banking requires, in the first

instance, a theoretical framework for analysis of bank functions and profits. In this

paper, banks are treated as capitalist enterprises that specialise in the following three

related activities: first, money-dealing, which includes facilitating foreign exchange

transactions, transmitting, providing access to and safe-keeping of money as well as

clearing money-related obligations, and so on; second, financial intermediation, i.e.

collecting spare money and lending it as money capital, in the course of which banks

also advance their own credit to borrowers. Third, what might be called financial

market mediation, i.e. facilitating participation in financial markets by non-financial

corporations, for instance, through underwriting of bond issues or providing

information-related services to borrowers and others. In recent years banks have also

begun to undertake several other activities, above all, provision of insurance, but the

theoretical classification given here is broad enough for most purposes.

On this theoretical basis, there are three broad sources of bank revenue: first,

profits out of money-dealing activities, second, the interest spread of financial

intermediation and, third, fee income from mediating financial transactions. It is

certainly true that in practice bank revenue also results from other sources, for


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instance, participation in financial transactions on a banks own account. However,

the three categories noted above are sufficient to capture recent trends in bank

revenue.

An important point to make before proceeding with the analysis refers to the

applicability of the concept of productivity to banking, given that banks are

intermediaries which provide services to borrowers and lenders but do not produce

any well-defined output. However, banks certainly employ large numbers of highly-

skilled workers whose salaries and wages are the bulk of bank costs. Consequently,

the efficiency with which bank workers undertake their tasks and the impact of

technology on completing these tasks are prime concerns of banks. The concept of

productivity has heuristic value in this respect, providing insight into changes of bank

costs.

Below I discuss the impact of new technology on banking by considering the

money-dealing and financial intermediation activities of banks, and bearing in mind

that productivity appears not to have risen in banking in recent years. The impact on

the third source of revenue, i.e. fee income, is broad and complex enough to warrant

separate treatment. It should be noted, however, that the major transformation

wrought by new technology with regard to fee income relates to asset securitisation.

Some of the parameters of this change are indirectly considered below in connection

with the financial intermediation function of banks. Fee income is connected to

securitisation which, after all, has its origins in financial intermediation, specifically

in the mortgage business. Moreover, securitisation involves techniques of risk

management that in all essentials are also used in lending to individuals as well as to

small and medium firms. The impact of new technology on these techniques is

examined below.

a. Money-dealing and new technology

It is commonplace that the foreign exchange market has expanded enormously

during the last three decades. The foreign exchange operations of banks have been

significantly affected partly due to the acceleration of the speed of transactions and

partly due to introduction of financial derivatives that rely on information technology.

However, foreign exchange will be left out of account in this article because it is too

broad a topic to discuss here but also because key aspects of it will be touched upon


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below, especially regarding risk management. Clearing has also been dramatically

affected by new technology but this too will be left out of discussion as it merits

extensive separate treatment. The main concern of this section is the profound effect

of new technology on the rest of the money-dealing activities of banks, including

transmission, safe-keeping and ready access to money. Analytical focus is again on

the USA but the trends appear to have general applicability.

The most important effect of new technology in this respect has been the

introduction of Automated Teller Machines (ATMs) since the 1970s. There has been

no let up in the introduction of ATMs in the USA despite the passage of more than

three decades:

Table 4. ATM Terminals in the USA

1996 139134

1997 165000

1998 187000

1999 227000

2000 273000

2001 324000

2002 352000

2003 371000

2004 383000

2005 396000

Source: ATM & Debit News

It is notable that, contrary to initial expectations, the spread of ATMs has not

led to a decline in the number of conventional bank branches. The figures for the USA

are clear:

Table 5. Bank Branches in the USA

Commercial Banks Savings Institutions Credit Unions Total

1990 62346 21609 10160 94115

2000 71784 14112 10316 96212

2001 73027 14136 9984 97147


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2002 73454 13940 9688 97082

2003 74518 13866 9369 97753

2004 76974 13691 9014 99679

Source: Federal Insurance Deposit Corporation; National Credit UnionAdministration

Some of the increase in the number of bank branches is due to the decline in

the number of savings institutions since the Savings and Loans crisis of 1991, leading

to absorption of their branches by banks (Osterberg and Sterk 1997). Concentration

has been pronounced within the US banking system during the last two decades.

Given the rapid decline in the number of commercial banks, there is no doubt that the

underlying trend for the number of braches per bank has been upward:

Table 6. Number of Banks and Savings Institutions in the USA

Commercial Banks Savings Institutions

1990 12329 2815

2000 8297 1589

2001 8062 1534

2002 7870 1466

2003 7752 1411

2004 7614 1345

Source: Federal Insurance Deposit Corporation; National Credit Union

Administration

The conclusion is clear: advancing automation in the provision of money-

dealing bank services has coincided with a second wave of branch banking in the

USA (the first was more than one hundred years ago). Banks have now penetrated

geographical areas and sectors of the US economy from which they were previously

absent. But that has not also meant an expansion of their money-lending activities, as

will be seen below.

The introduction of ATMs might not have reduced the number of bank

branches but its impact on banking operations has been extensive. It was initially

expected that ATMs would reduce bank costs due to the difference between the costs


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of individual transactions completed by ATMs and those completed in person by bank

employees. Kimbal and Gregor (1995), for instance, estimated that the per-transaction

cost for ATMs was $0.27 compared to $1.07 for tellers. However, things have turned

out differently. The frequency with which customers use ATMs is higher than

obtaining similar services from tellers, and the sums withdrawn tend to be smaller

(Stavins 2000). Thus, the introduction of ATMs seems to have led to a change in the

demand for money-related services: access to cash is required at all times and in

geographical places that were previously out of bounds for banks. This has

contributed to steadily rising ATM numbers and increased pressure on banks to

expand ATM investment. Whereas banks initially provided ATMs at or near existing

bank branches they now have to provide clusters of ATMs in new places, such as

shopping malls. The latter are significantly more expensive to operate than ATMs

placed at branches (Stavins 2000). At the same time, there has remained a strong

demand for teller services provided in person by bank employees, perhaps in relation

to more complex operations than cash withdrawals and deposits. The continuing

demand for personal services has contributed to the steadily rising number of bank

branches.

These combined trends have meant that the costs of providing money-dealing

services through ATMs for a given deposit base have been persistently high. Banks

have attempted to deal with this problem in a variety of ways, typically through

imposing charges on ATM use. Moreover, larger banks are imposing higher charges

than smaller ones (Stavins 2000). Banks have also imposed institutional obstacles

between customers and tellers by placing the latter away from the front desks, or even

by charging customers more for transactions completed through tellers as opposed to

those completed through ATMs. Yet, success in reducing costs has been elusive. It

appears that the introduction of new technology in the form of ATMs might have

increased the costs of providing money-dealing services for a given deposit base

instead of lowering them.

Generalised introduction of ATMs, however, has been only one part of the

impact of technology on the money-dealing functions of banks. The adoption of the

internet and the spread of electronic communications will probably prove even more

significant for the money-dealing functions of banks in coming years. This process -

commencing in the 1990s and still in its infancy - is typically captured by the term e-

banking or e-finance (Allen, McAndrews and Strahan 2002). Leaving aside clearing


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and inter-bank payments (in which electronic communications have been in use for

several decades), e-banking refers to a host of banking services, such as computer

banking, debit cards, electronic bill payments, smart cards, stored-value cards, and so

on. Several of these are forms of e-money and replace ordinary bank money or small-

denomination Federal Reserve banknotes from circulation. The proportion of US

households banking by computer grew fivefold between 1995 and 2001, and the

proportions using debit cards and smart cards more than doubled (Anguelov, Hilgert

and Hogarth 2004). Meanwhile, the proportion of households using non-electronic

banking methods of payment has declined.

There can be little doubt that this is the direction that bank money-dealing

services will take in the future. Nonetheless, the adoption of the new forms of

payment will also face delays, while country-specific peculiarities in the use of paying

methods are likely to remain, as is evidenced by the continuing prevalence of cheques

as means of payment in the USA. There are complex problems attached to this

phenomenon relating to the role of money in a capitalist economy and the requisite

trust in particular forms of money. The spread of computers among different social

groups and the familiarity of different age groups with computer practice are

important in this respect. Not least is the matter of security in making payments online

which require placing personal details at the disposal of unknown persons. These

problems are likely to persevere thus limiting the spread of e-banking.

For banks, one key attraction of internet banking is the low cost per-

transaction. The consulting firm Booz-Allen & Hamilton Inc. estimated that average

variable costs per transaction were about $0.01 for the internet compared to $1 or

more for transactions completed through tellers (Bank of Japan, 2001, p.27). It

remains to be seen, however, whether the internet and new electronic technology will

succeed where ATMs failed. For one thing, the investment costs of internet banking

are high, making banks the heaviest spenders on new technology within the financial

sector. This raises average costs and requires a large number of accounts before

internet banking begins to pay. It appears, moreover, that computer banking is more

prevalent among individuals who hold higher balances and use more bank services

(Hitt and Frei 2002). It is conceivable, therefore, that banks will find themselves

obliged to provide new money-dealing services - requiring heavy capital investment -

without a substantial decline in other services. Money-dealing costs might prove

persistent, as they have for ATMs.


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More broadly, however, the introduction of e-banking will accelerate the

transformation of the internal organisation of bank branches, a process that has been

under way for some time also due to ATM introduction (Hughes and Bernhardt 1999,

Hunter, Bernhardt, Hughes, and Skuratowicz 2001, Autor, Levy and Murnane 2000,

2003, Frei, Harker and Hunter 1998, Frei and Harker 2000). The role of tellers has

already changed in line with increasing reliance on automated teller services. A

significant proportion of tellers now have to provide more complex services which

include sophisticated assessments of individual client data as well as overall economic

data. Significant numbers of bank employees that used to be tellers have increasingly

become sellers of banking services. The skills required by the latter are

correspondingly advanced, often involving the use of information technology. By the

same token, other tellers largely have to input data and to undertake simple

mechanical manipulations using information technology. Therefore, banking jobs at

the level of the branch have undergone a considerable upgrading as well as

downgrading. While the back office employs more skilled staff to undertake complex

tasks, the front desk has become relatively deskilled.

In view of these complex changes, it is hardly surprising that the introduction

of new money-dealing technology banks over the last three decades has not resulted

in measurable productivity improvements, as was mentioned in section 2, and nor has

it lowered costs. The banks have found themselves in the position of having to

provide additional and unforeseen services that require heavy initial investment. The

mix of labour skills needed at the branch level, meanwhile, has become considerably

more complex. New technologies appear not to have reduced costs significantly in

these respects. 4

b. Financial intermediation and new technology

It hardly needs stating that technological change in recent years has affected

all aspects of financial intermediation. However, the strongest impact has been on the

asset side of bank balance sheets, as well as off-balance-sheet. These changes cannot

4 Since clearing has not been examined, it is not possible to arrive at firm conclusions with regard tomoney-dealing as a whole. It should be mentioned that Bauer and Ferrier (1996) and Hancock,

Humphrey and Wilcox (1999) have found that the costs of Automated Clearing House (ACH) andFedwire services have high elasticity relative to total number of transactions. This could be an avenuethrough which new technology is successfully reducing bank costs.


19/28

be disentangled from the broader transformation of finance during the same period.

Most prominent has been the broad decline of the share of commercial banks (and

savings institutions) in total borrowing in the USA. The tendency for banks (all

depository institutions) to lose share relative to pension funds and mutual funds has

been well documented for some time (see, for instance, Edwards and Mishkin 1995).

Moreover, large corporations rely heavily on retained profits and other internally

generated funds, while obtaining external funds increasingly through the securities

markets, i.e. through direct finance. However, the decline in the share of banks has

not meant that they have become less important for the financial system, as was

pointed out by Boyd and Gertler (1994).5

In the new environment, banks have been earning fees by facilitating access to

securities markets for large corporations. Consequently, the relationship between

banks and large corporations has assumed an aspect of financial market mediation.

Lending to individuals has acquired a new significance for banks. Moreover, banks

have also strengthened their off-balance-sheet activities, including derivatives trading.

In all these respects, new technology has been of key importance. In the remaining

part of this article off-balance-sheet activities will not be directly considered.

Nonetheless, the analysis of credit risk management and information processing also

applies in good part to off-balance-sheet activities.

Lending to individuals primarily for mortgages and consumption loans,

including credit cards has become an increasing part of bank lending. Such lending

has traditionally posed enormous informational problems for banks, resulting in risks

that limited its scope. Ascertaining the creditworthiness of individuals and securing a

reliable flow of interest payments are potentially very costly processes when large

numbers are involved. Things have changed dramatically with the introduction of new

techniques of credit scoring that rely on new technology, particularly on enlarged and

cheap computer power.

Credit scoring by banks was extensively introduced in the USA in the 1990s,

the original spur coming from the earlier standardisation of individual mortgages. The

technique involves the creation of borrower profiles by collecting information on a

range of attributes/variables, including income, type of job, age, and credit history.

5 It is equally untrue that the decline in the share of banks in total borrowing indicates the decline of

financial intermediation in general. Pension funds and money funds (as well as insurance companies)are, of course, financial intermediaries. What has changed is the dominant form of financialintermediation.


20/28

Each of the attributes is split into several classes with scores attached. Individual

data on the attributes is then collected and a total score is assigned to each individual

that serves as an index of riskiness. Banks typically employ a cut off point in

assessing individual applications: failure to meet the threshold results in withdrawal

of credit. The bank can also establish aggregate risk measurements for its balance

sheet by organising the mass of the available information around a few variables

(typically between seven and ten). The bank can then calculate the risk attached to its

assets in relation to the sector as a whole (as distance from the sectoral averages).

Using fairly complex econometrics, the bank can manage the volume and composition

of its individual loans to attain a desired level of risk. 6

The introduction of credit scoring has already affected the practices and

operations of banking capital in several ways. First, the enhanced ability of banks to

ascertain risk levels has increased their capacity to adjust risk premia and therefore to

present borrowers with a broader range of interest rates, i.e. banks are increasingly

able to practice differential charging of interest rates. Second, credit scoring, other

things equal, implies a lowering of the administrative costs of extending loans, thus

raising the profitability of banks. Third, banks are better able to discriminate among

borrowers. Given that this takes place on the basis of information collected from the

existing pool of borrowers, it is possible that selection bias arises against individuals

whose personal conditions are not captured by the range of variables included in risk

monitoring. Fourth, the internal organisation of banks has been altered along similar

lines to those mentioned in section 2. Specifically, banks have increased demand for

platform staff that are familiar with information technology and can engage in

technical assessment of credit.

The broader significance of these developments, which are still in their

infancy, cannot be underestimated. Banking capital appears to have acquired the

means with which to reach sources of profit that were previously out of bounds. These

sources lie within the circuit of private revenue of workers and others, rather than

within the circuit of industrial and commercial capital. Techniques have been devised

that allow banks to treat individual borrowers as units of an effectively homogenised

mass, thus enabling risk calculations that so far appear to be reliable. This process

would have been impossible without new technology allowing for quick and cheap

6 For an early and informative summary of the technique of credit scoring see Mester (1997).


21/28

processing of huge volumes of information. But it is also apparent that compiling the

necessary information is neither easy nor cheap. Banks might be able to collect

information fairly easily as far as their own customers are concerned but this is, by

definition, a small part of the borrower pool with concomitantly unreliable statistical

properties. Thus, one of the most pressing problems for banks currently is to create

reliable databases covering the personal details of enormous numbers of individuals.

Moreover, a new line of capitalist business has emerged as these databases are often

run privately and information is sold commercially to banks.

Credit scoring practices that were originally developed for individuals have

recently begun to spread to bank lending to SMEs. The techniques are essentially the

same, i.e. SMEs are treated as units of a homogenised mass to which econometric

techniques are applied in order to ascertain risk relatively to sectoral averages.

However, it is apparent that the logic applied to individuals cannot be directly and

immediately applied to SMEs. An important problem is that SMEs differ significantly

from each other in terms of the industry in which they are engaged, unlike individuals

for whom the basic conditions of wage labour exhibit substantial similarities.

Nonetheless, there are still sufficient similarities in practice among SMEs to allow

banks increasingly to apply credit-scoring techniques. A further difficulty is the lack

of reliable databases for SMEs, which is pronounced even for countries with well-

developed financial systems, such as Japan. Much of the necessary information for the

databases comes from SME income statements which tend to be understated by firms

due to their tax implications, while being unsatisfactorily audited for very small firms.

Nonetheless, the availability of credit scoring has meant that banks can more

extensively engage in transactions-based banking, that is, extend loans on the basis

of numerical and broadly quantitative information, thus treating borrowers as

impersonal units at arms-length from the bank. Banks can readjust their relationship

lending toward SMEs, that is, change the practice of extending loans on the basis of

information collected through regular contact over long periods of time, which relies

on the personal judgement of the borrower by the loans officer involved. (Berger and

Udell 1995, 2002, 2003). It is apparent that these trends taken together have

implications for the character of the financial system as a whole as they strengthen the

arms-length, market-based aspect of bank lending.

It is still far too early to draw firm conclusions regarding the significance of

these developments for banks but note the following two important points. First, the


22/28

emergence of these practices has already led to diversification of the banking firm

itself: banks have begun to specialise in providing and trading information suitable for

processing by other banks. Such diversification, however, creates new competitive

dangers for banks as there might be firms outside the financial sector that can also

collect and assess financial information. Giant corporations that have skills in

collecting and processing information, such as Microsoft, could enter the banking

business and pose a threat for incumbents. Second, there are broad social implications

from the construction of these databases, including for political democracy. The reach

of financial capital into the private life of the population as a whole has never been

broader and deeper. The enormous data banks that have already been constructed and

placed at the disposal of banks are as nothing compared to those that are likely to

emerge in the next ten years containing personal and private information that is then

traded among financial institutions.

4. Conclusion

Several points made in this article are worth restating in the conclusion. First,

banks in the USA have been operating within an environment of rapidly rising

productivity since 1995, and hence have had broader opportunities for profit making.

Second, the connection between new technology (mostly telecommunications,

electronics and information processing) and rising productivity across the economy is

still not clear, especially regarding the mechanisms through which new technology

affects production and labour at the microeconomic level. Third, productivity in

banking has not increased despite banks investing heavily in new technology. Fourth,

adoption of new technology in performing the money-dealing functions of banks -

primarily ATMSs and e-banking - has certainly transformed the way in which banks

operate. But it has also imposed high investments without delivering significant

savings in the costs of banks and without visible improvements in staff productivity at

the branch level.

Fifth, adoption of new technology has also wrought substantial changes to the

function of banks as financial intermediaries. New technology has been introduced

while US banks have been losing share in the total borrowing across the economy.

Banks have shifted their lending activities in the direction of individuals, drawing

profits out of the circulation of private revenue. Banks have also increased the


23/28

proportion of fee income earned through mediating the entry of others in the financial

markets. In this context, the introduction of new technology has altered the way banks

operate in so far as it has allowed for new techniques of risk management and credit

scoring. Information processing has emerged as a major new activity of banks, and

banks have become more arms-length from their borrowers. But the possibility has

also been opened for new competitors of banks arising outside the financial sector.


24/28

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