Research on the Effects of Information Technology on Operational Efficiency in Vietnam Commercial Banks Using the Data Envelopment Analysis Method

Research on the Effects of Information Technology on Operational Efficiency in Vietnam Commercial Banks: Using the Data Envelopment Analysis Method ... The 4 th International Conference

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The 4 th International Conference on Finance, Accounting and Auditing (ICFAA 2021)

December 18 th , 2021 Hanoi City, Vietnam

Research on the Effects of Information Technology on Operational Efficiency in Vietnam Commercial Banks: Using the Data Envelopment Analysis Method

Submission date: 16/11/2021 Revision date: 26/11/2021

Abstract

The paper analyses the impact of information technology (IT) on the performance of Vietnamese commercial banks The study applies the random effects model (REM), the fixed effects model (FEM) and the regression analysis to the data of 30 Vietnam’s commercial banks in the period from 2016 to

2020 We employ the Data Envelopment Analysis on panel data to generate estimates of cost efficiencies and revenue efficiencies Measuring the impact of various categories of information technology (Technical infrastructure, IT human resource infrastructure, bank’s internal IT application, Online banking service) on banks efficiencies suggests that “the Productivity Paradox” does not affect all ormation technology investments Based on the findings, the authors give some recommendations

to Vietnamese commercial banks in case of investments in IT to improve performance.

Keywords: Bank’s performance, Commercial banks, Information technology

JEL code: M40

1 Introduction

This study examines the impact of information technology (IT) investment on performance in Vietnam commercial banks There are two reasons for this research topic to become an urgent study Firstly, the banking and financial sectors are considered the lifeblood of the economy Banking is an intermediary activity linking the movement of the entire economic sector and the influence of the banking industry on all socio-economic activities Therefore, the improvement of the bank performance brings widespread effects not only to the banking industry but also to other industries Secondly, the banking industry is one of the leading industries in

applying IT in management and operation Information gathering and processing is central to the banking industry, so the impacts of IT innovation can be far-reaching

Many companies in general and banks in particular have invested a lot of money in IT but have very little understanding of the impact of IT on operational efficiency Without scientific impact assessment measures, investment decisions will only be based on emotions Therefore, the development of measures to assess the impact between IT investment and performance will be of real value both academically and practically Research on the link between IT investment and performance began with Robert Solow (1987) in his statement as follows: “You can see the computer age everywhere except in in efficiency statistics" Then, there are a number of studies investigating the impact of IT on operational performance at different levels: entire economy, industry, company, division, and an individual application However, in this research, the author only focuses on company-level studies Previous studies had shown the mixed results on the relationship between IT and performance The researchs conducted in the first half of the 1990s by Strassmann (1990), Weill (1992), Brynjolfsson (1993) and Landauer (1995) showed that there was no link between investments in IT and performance However, the researchs conducted in the second half of the 1990s by Dewan (1997), Hitt (1996) concluded that there was a positive positive relationship between investment

in IT and operational performance Because the research results on the relationship between IT investment and performance in the world show many different results, moreover, this research topic in Vietnam is very small, so the author has chosen the topic "Research on the effects of Information technology on operational efficiency in Vietnam commercial banks: Using data envelopment analysis" as the research topic for this research

By interpreting the previous findings on "the productivity paradox", our research attempts to empirically validate the relationship between IT investment and performance in the context of the emerging country of Vietnam Our study is therefore devoted to examining the following key question: What is the impact of information technology on the performance of Vietnam commercial banks? To empirically validate the relationship between IT investment and the performance of Vietnam commercial banks, we use using the data envelopment analysis method Thus, the objective of this work is to evaluate the performance of banks during the period 2016–2020 while identifying the impact of different information technologies components introduced by banks on their performance The paper is organized as follows Section 1 provides the introduction Section 2 provides the literature review and methodological approach for our study Finally, Section 4 describes the empirical results, and Section 5 is the conclusion

2 Literature Review/ Theoretical Framework and Methods

2.1 Literature Review

Besides the traditional approach when evaluating performance, the world now uses the data envelopment analysis method This method calculates a relative efficiency index based on

comparing the distance of units (banks) with a marginal best performing unit (this margin is calculated from the dataset because in practice) This tool allows us to calculate the overall performance index of each bank based on their performance and allows to rank the performance

of the banks the data envelopment analysis method will calculate TFP composite factor productivity, cost effectiveness and profit efficiency of each company Therefore, recent studies have evaluated the effect of IT investment on operating performance according to performance measures from the data envelopment analysis method for two reasons First, studies that evaluate the impact of IT on traditional performance measures may underestimate the impact

of IT because computer use is often associated with large changes in output quality It is difficult

to measure accurately Second, the use of technology can take time to adjust to the organization and the skills of employees Therefore, the recent studies trying to explore and evaluate the impact of IT on changes in corporate organizations and in corporate performance, traditional performance measures such as ROA, ROE do not reflect these changes Therefore, in this study, the author will focus on studies that analyze the relationship between IT and performance based

on the data envelopment analysis method

Gopal, Wang and Zionts (1992) conducted a study on the firm-level performance of 36 banks The author used the data envelope analysis (DEA) method to measure performance

They used the adjusted DEA model because the pure DEA model did not consider intermediate manufacturing processes and did not provide the detailed information about the effects of specific variables Data sources were obtained from Computerworld Premier 100, Standard and Poor's Industry Surveys and Standard and Poor's Compustat The first stage output variable was the total amount of deposits The stage one input variables were IT assets, staff and budget The second stage output variables were Profit and loan percentage recovered The authors conclude that there was a positive relationship between operating results and the intensity of capital use for IT The downside of that study was that it didn’t factor in the possible time lag between IT investment and operational performance Furthermore, in the authors' model it was assumed that the only intensive use of IT is in the deposit sector; however, IT was used intensively in at least two other areas - loan approval/collection and loan management Therefore, the author had not studied the impact of IT on performance in these areas

Courtney (1993) studied performance at the firm level in several industries based on the DEA method suggested by Gopal (1992), using least squares regression and discriminant analysis The author studied a sample of 325 companies from the same data source as in Gopal (1992) using Computerworld Premier 100 for intermediate variables, while higher-level variables were used from Standard and Poor's sources, Industry Surveys and Standard and Poor's Compustat The information system investment variables in the research were: Budget for information system, budget for information system staff, training budget for information system staff, terminal equipment/staff, processor value, year, sector The performance variables

in the study were ROA and stock price The DEA method was used to determine the effective classifier for each company The numerical discriminant analysis uses the output of the DEA

to determine if a relationship exists between the performance classification and IT investment

Finally, the least squares regression method compares the DEA and the discriminant analysis

results The authors did not find a direct relationship between IT and operational performance for all industries, although a positive relationship had been noted in the paper, chemical, and oil refining industries

Beccalli's study (2007) expanded on previous studies on IT investment and performance

of 737 banks in Europe (specifically in France, Germany, Italy, Spain, UK) for the period from

1995 to 2000 The independent variables were IT investment in hardware, software, and other

IT services The dependent variables were ROA, ROE, cost effectiveness and profit efficiency The author uses the following methods: OLS regression, two-stage regression (2SLS) and SFA The research results showed that although banks invest large in IT, there is a small relationship between total IT investment and operational efficiency at the bank, confirming the existence of

a productivity paradox The impact of different types of IT investments was different: while investments in hardware and software reduced the efficiency of banks, IT services from outside providers had a positive effect to ROA, ROE and profit efficiency This study of the author had overcome some limitations of previous studies by using both a traditional accounting profit measure (ROA, ROE) and a more advanced measure of operational efficiency, which called X-efficiency Moreover, the author did not study investment in IT as a single variable like previous studies but had specifically divided into three components of IT investment namely hardware, software and IT services to consider the different IT areas

Tam (2015) researched the impact of technology investment on the performance of the commercial banking system in Vietnam, thereby assessing the impact of technology investment

on banks At the same time, give recommendations to commercial banks on the level of investment in technology to improve the operational efficiency of Vietnamese commercial banks Using the GMM method for one-year lagged dynamic panel data of 15 commercial banks in Vietnam with data for six years (2009-2014), the study analyzed the impact of IT on ROE and ROA The resulting research showed that when other factors held constant, increasing IT (ratio

of technology investment on fixed assets) by 1% will increase ROA (rate of return on total assets)

by 10% In addition to IT, the operational efficiency of the commercial banking system in Vietnam was also affected by factors such as the ratio of liquid assets to total assets (liquidity) and macro factors such as economic growth rate (GDP), consumer price index (CPI) and exchange rate change (tygia), but the level of impact of these factors was quite low in the model

Huong and Nhu (2018) researched the influence of information and communication technology on Vietnam commercial banks through the Vietnam ICT Index The author researched the data of 24 commercial banks from 2006 to 2017 according to the linear regression model Research results show that there is a positive relationship between ICT index and operational performance From there, the author makes recommendations that banks should strengthen policies to improve ICT indicators and combine with strategies to expand bank scale, loans and deposits However, this study only focuses on the composite index of IT without further research on the specific component indexes of ICT index

Currently, there are very few studies on the relationship between IT investment and operational efficiency at banks using the marginal efficiency analysis in the world so the imperial studies are also essential Moreover, according to the author's knowledge, the studies between the

relationship between IT investment and the performance of banks in Vietnam have only mostly researched in the direction of evaluating the direct relationship between IT and operational efficiency according to the traditional assessment method is (ROA and ROE) (Tam, 2015; Huong and Nhu, 2018) but very few studies have evaluated the relationship between IT and the performance of Vietnam commercial banks according to the method of marginal efficiency analysis (DEA method), the author finds that this is a research gap that needs to be filled

2.2 Methodology

In this research, the author uses a regression method to evaluate the impact of IT on the performance of X-efficiency

Performance (X-efficiency) = f(IT)

In which, X-efficiency will be approached according to the method of marginal efficiency analysis This method calculates a relative efficiency index based on comparing the distance of units (banks) with a best performing unit on the edge (this compile from the data files because on the reality of compile results to the theory is not know) The marginal efficiency analysis method has two approaches: parametric approach and non-parametric approach The requirement parameter approach needs to have a specific form of function for the efficient frontier and has a specified random error or inefficient distribution Therefore, the outcome of the parametric approach is greatly influenced by the choice of the functional form The non-parametric approach does not need to specify a particular form of function and does not constrain the distribution of inefficiencies like the parametric approach, except that the efficiency indices must be between 0 and 1, and assume there is no random error or measurement error in the data Therefore, the main limitation of the non-parametric method is that it is very sensitive, so if there is a random error in the data, it will affect the results

In this research, the author uses a non-parametric approach, namely the data envelopment method DEA is a linear programming technique to evaluate a decision-making unit (DMU or bank) how does it perform relative to other banks in the sample? This technique generates a marginal set of efficient banks and compares it with inefficient banks to measure efficiency The author chooses the DEA method because the banking industry is a complex service industry and there are many relationships between inputs and outputs Therefore, when evaluating the performance of a bank, it is necessary to consider simultaneously many inputs and many outputs Whereas the parametric approach has to specify a specific form of function between the input and the output, so it is very likely that it will give wrong results if the choice

of the function form is not correct

The key point of this approach is to specify the bank's inputs and outputs appropriately

According to research results on bank performance, there are five approaches in determining outputs and inputs (Hung, 2008)

 Production approach: considers banks as service providers, so deposits are

considered outputs and interest payments on deposits are not included in banking costs (Ferrier and Lovell, 1990)

 Intermediary approach: considers banking as financial institutions that mobilize and

allocate loans and other assets so that deposits are treated as inputs and interest payments are part of total expenditures banking fee

 Asset approach: consider liabilities as inputs and assets as outputs

 Value added approach: treat all balance sheet items as outputs if it attracts the

respective contributions of capital and labor hence deposits are considered outputs

 Usage-cost approach: considers the net contribution to a bank's revenue as an input

and output, hence deposits as an output

According to Berger and Humphrey (1997), there is no perfect approach that reflects all the activities and roles of a bank, but the intermediary approach may be the most appropriate when assessing the bank's performance because it is concerned with interest payments, which often account for ½ to 1/3 of a bank's total operating costs Moreover, the intermediary approach

is also concerned with the profitability of the bank because minimizing costs is a necessary condition for profit maximization Therefore, in this research, the author also uses an intermediary approach that considers deposits as an input to create outputs such as lending, investment, interest income and non-interest income According to Hung (2008), the author chooses the input and output variables in the DEA model as follows:

 Input variables include: Total net fixed assets (K.TSCD), total expenses for employees (L.ChiNV), total mobilized capital (W.TGKH)

 Outputs: Interest and future income (Thulai) and Non-interest income (Thungoailai) After estimating the efficiency measures by the DEA method, the author will obtain the technical efficiency of banks according to the revenue maximization function under CRS (CRSTEmax) and VRS (VRSTEmax) conditions and the author will obtain the technical efficiency of banks according to the cost minimization function under CRS (CRSTEmin) and VRS (VRSTEmin) conditions These results are used by the author as a dependent variable to evaluate the performance of banks

Next, a regression model is used to analyze the impact of IT on these performance measures In which, the independent variable IT is obtained by the author from the report on readiness for development and application of IT and communication in Vietnam (ICT index) dedicated to the banking industry The Vietnam ICT Index report was developed by Vietnam Association for Information Processing according to the standards of E-Government Development Index (EGDI) of the United Nations The Vietnam ICT Index is calculated on the basis of statistical reports of central and local state management agencies, that is, an internal assessment and hardly depends on the subjective feelings of digital providers (Report of 10 years of implementation of Viet Nam ICT index) The ICT index has been correlated with other sets of socio-economic indicators of Vietnam (PCI provincial competitiveness index; PAR administrative reform index, governance efficiency index and Provincial public administration (PAPI, e-commerce index EBI) all show a high degree of correlation This proves both

academically and practically that the ICT index data is reliable From 2016, the ICT index adjusted according to the standards of the E-Government Development Index – EGDI will include 4 sub-indexes: infrastructure technology (HT), human infrastructure (NL), internal banking IT applications (UD) and online banking services (DV)

Variable Definition Indicator Measure

HT Technical

infrastructu

re

1 Server and workstation infrastructure

- The ratio of Virtual Servers/Total Servers

- The ratio of workstations (PC/Laptop) in the last

3 years/Total Workstations

2

Communication infrastructure

- The ratio of workstations running proprietary and manufacturer-supported operating systems/Total workstations

- The ratio of Internet bandwidth providing Internet Banking services/Total number of Internet Banking customers

- Ratio of Internet bandwidth provided to internal users/Total number of computers connected to the Internet

- Ratio of wide area network bandwidth/Total number of terminals

3 ATM and POS

- The ratio of POS machine/Total payment cards

- The ratio of (mPOS and wireless POS)/Total POS

4 Deployment

of information security and data safety solutions

- The ratio of workstations with anti-virus software installed/Total workstations

- The ratio of servers installed anti-virus software/Total servers

- Rate of database installed on SAN + Rate of database installed at TTDPTH + Rate of database backed up to hard disk + Rate of database backed

up to magnetic tape

- ATTT (TTDL, TTDPTH) = Total of main solutions + 0.2 x Other solutions

Variable Definition Indicator Measure

- ATTT(CN) = Sum of main solutions + 0.2 x Other solutions

- ATTT(UDKH) = + 5x(%Customers use (Digital Signature + Advanced OTP + U2F+UAF)) + 4x(%Customers use (Biometrics + Basic OTP)) + 3x(%Customers customers using SMS OTP) +2x(%Customers using Matrix Card) + 1x(Username, Password +CAPTCHA)

- CCATTT = Total number of bank's security certificates + 10 x Total number of BCP drills + Total number of individual BCP drills for each system

5 Data Center (Data Center) and Disaster

Prevention Center (TTDPTH)

5 x Data Center Level +3 x TTDPTH + TTDPTH CARD

NL Human

resource infrastructu

re

- The ratio of specialized IT staff/total employees

- The ratio of officers in charge of information security/Total employees

- The ratio of IT staff with specialized international certificates IT/Total number of specialized IT staff

UD Bank's

internal IT application

1 Deploy core banking

SLMD + SLKN + PTKN + XLGD + XLĐC Inside:

1) SLMD: Total number of Corebank modules deployed 2) SLKN: Total connection of Corebank and other systems (ERP, ATM/POS, Internet Banking, SWIFT, CITAD, Reporting Systems ) 3) PTKN: Connection method between Corebank and other systems (1: file interface, 2: Database, 3: Message Queue, 4: ESB integration axis, 5: Other form)

4) XLGD: The degree of automation when processing transactions between Corebank system and other systems (0: non-automatic, 1: semi-automatic, 2: automatic)

5) XLĐC: Process and reconcile data between

Variable Definition Indicator Measure

CoreBank and other systems (0: no reconciliation, 1: with manual reconciliation, 2:

with partial automatic reconciliation, 3 with full automatic reconciliation)

2 Deploy basic applications

Basic IT Applications + 0.2 x OTHER

3 Deploying electronic payments

Interbank e-commerce + SWIFT + Other (Bilateral payment

DV Online

banking service

by the formula+ Daily update: TSCN = 3+

Weekly update: TSCN = 2+ Monthly update:

TSCN = 1+ Irregular update: TSCN = 0

2 Internet Banking for individual customers

Formula: MTCH + 0.1 x MTKH MTCH: Total number of main items available (listed in the survey form)

MTKH: Total number of other items (if any)

3 Internet Banking for corporate customers

Formula: MTCH + 0.1 x MTKH MTCH: Total number of main items available (listed in the survey form)

MTKH: Total number of other items (if any)

4 Other banking

e-services

Formula: MTCH + 0.1 x MTKH MTCH: Total number of main items available (listed in the survey form)

MTKH: Total number of other items (if any)

5 Other banking

e-services

Formula: TLTHEGD + TLGDDT + TLGDATM/POS

TLTHEGD: The ratio of cards with transactions

in the year/Total number of individual customers TLGDDT: The ratio of electronic transactions/total transactions

TLGDATM/POS: The ratio of transactions via ATMs and POS machines/Total transactions

Source: Vietnam ICT index 2016, 2017, 2018, 2019

The author chooses such IT investment variables to overcome two limitations in previous studies First, the previous studies assumed that all firms are converting their IT investments into outputs with the same degree of success (Huang, 2002) Previous studies were based on data on IT investment costs, but the results of the IT investment process could not be clarified Therefore, the use of IT investment performance indicators will overcome this limitation These are the general indicators developed by the Ministry of Information and Communications of Vietnam for the general assessment of commercial banks, so the indicators are comprehensive in terms of IT aspects and are quite reliable Second, many previous studies assume that all investments in IT are treated equally by using only one aggregate IT variable (Huang, 2002) In the study, the author uses four IT variables namely technical infrastructure,

IT human resource infrastructure, banking internal IT application and banking online services,

so the specific impact of each type of IT investment will be measured on bank performance

To consider the impact on performance of the various categories of IT investments, the estimated equation is:

Table 1 The banks list during 2016 -2020

1 Tien Phong Commercial Joint Stock Bank TBP 4

2 Nam A Comercial Join Stock Bank NAB 5

3 JSC Bank for Investment and Development of Vietnam BID 5

4 VietNam Technological and Commercial Joint Stock Bank TCB 5

5 Military Commercial Joint Stock Bank MBB 5

6 JSC Bank for Foreign Trade of Vietnam VCB 5

7 Vietnam Thuong Tin Commercial Joint Stock Bank VBB 3

8 Orient Commercial Joint Stock Bank OCB 5

9 Sai Gon Joint Stock Commercial Bank SCB 5