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LaddawanSombut, SupeechaPanichpathom, and AtcharawanNgarmyarn, Thammasat Businees School, Thammasat University
The Impact of Perceived Process Technology Fit on
Loan Origination Process Performance
LaddawanSombut, SupeechaPanichpathom, and AtcharawanNgarmyarn
One of core business process in banking industry is loan approval process which needs to be agile to support turbulent environments, market volatility, and adaptation to changing regulation related to loan origination tasks. Without these capabilities, banks are unable to compete effectively or to sustain their lending business. The fit between process and information technology and its impacts on business process performance is a process-level fit model that provides a greater understanding of business process than models focusing on group or task-level assessments.This study proposed perceived process technology fit (PPTF) framework which incorporated technology acceptance model variables in predicting loan origination process performance. The highlight of this research is the importance of perceived fit between loan origination process and business process management technology composing of process engine, business analytics and contents management which impacts on business process performance. Questionnaires were administered to a convenience sample of 283 current employeesworking in commercial loan origination process in Thai commercial banks. Their responsibility is related to end-to-end lending process starting fromapplication pre-qualification, credit approval, account initiation and activation. This extant framework provides better understanding of independent variables having an impact on business process performance. The perceived process technology fit on loan origination process performance has both direct and indirect effects on business process performance. These results are indirectly through intention to use technology and IT utilization. Based on the results of this study, executive is able to apply the business process management technology which provides business process automation based on pre-defined rules, real time information analytics and storing electronic documents to enhance loan origination process performance with efficiency, effectiveness, productivity, timeliness, loan quality, shorter time to market and meet customer expectation.
Keyword: Perceived process technology fit, Loan Origination Process, Business Process Management (BPM) Technology, and Business Process Performance.
Code: 433
1. Introduction
In turbulent environments, banking agility is the ability of firms to sense environment change and respond rapidly in adapting to deep regulatory change and continued economic volatility. IT is an important determinant of firm successful. One of core business process in banking industry is loan approval process that needs to be agile to support turbulent environments. Technology flexibility plays an important role to
launch new lending product rapidly, transform loan origination process and meet customer expectation. Without these capabilities, banks are unable to compete
effectively or to sustain their lending business. This study is attempt to identify the fit between process and information technology and its impact on business process performance are a process-level fit model that provides a greater understanding of business process than models focusing on group or task-level assessments(Gribbins, Subramaniam, & Shaw, 2006).
This study attempts to identify the impact of perceived process technology fit on loan origination process performance based on the theory of process and technology fit combined with technology acceptance model. We examined the fit between loan origination process and business process management technology composing of process engine, business analytics and contents management. Quantitative research method was conducted and 283 questionnaires were collected from credit analyst, under writer and credit staff who relate on end to end lending process.Regression analysis and factor analysis using principle axis factoring extraction and varimax rotation were used to test the research model and hypotheses.
This research evaluated the impact of perceived process technology fit on loan origination process performance. First, perceived process technology fit had a positive significant to intention to use. Second, perceived process technology fit and intention to use had a positive significant to utilization. Finally, perceived process technology fit and IT utilization had a positive significant to business process performance.
2. Literature Review
The reviewed literature includes the studies of Loan Origination Process, Business Process Management Technology, Task-Technology Fit (TTF) Theory& Extending Model,Process-Technology Fit (PTF) Model and business process performance which are shown as follows:
2.1 Loan Origination Process
The process is an activity or group of collaborative activities that transform input to output with value added activities (Crowston&Osborn, 2003; Melville N., Kraemar K., &Gurbaxani V., 2004). There are composing of the ―Activities‖ are a tasks or events of processes, ―Resources‖ are materials or other assets that are transformed to produce benefit and in the process and ―Actors‖ who use resources to operate their work. In the banking, The Loan Origination includes all the processed involved in a retail or commercial borrower applying for a loan through the disbursal of funds. Gartner, 2011 identified five main processes related on secured loan and unsecured loan composing of First, ―Customer Investigation‖ is the process that customer identifies the need for loan and conducts a search and due diligence. Second, ―Application and Pre-Qualification‖ are the process that customer or bank identifies product to satisfy need and bank gathers information from borrowers to determine appropriate loan funding and provides initial pricing. Third, ―Account processing and underwriting‖ are the process that customer completed full application and bank gathers data (i.e. credit checks, covenant compliance and anti-money laundering (AML)) after that account underwriting executed approval on loan.Fourth, ―Account Initiation‖ is a process that loan documents are generated. Customers sign a contract and funds confirmation. Finally, ―Account
Activation‖ is a process that customers draws down on loan or carries out first transaction.
2.2 Business Process Management Technology
The Business Process Management Technology is defined as supporting business processes using methods, techniques and software to design, control and analyze operational process involving humans, organization, applications, documents and other sources of information (Ryan, 2009). It promotes business effectiveness and efficiency while striving for innovation, flexibility, and integration with technology. There are composing of ―Process Engine‖is a robust platform for modeling and executing process-based applications, including business rules, ―Business Analytics‖ enable managers to identify business issues, trends, and opportunities with reports and dashboards and react accordingly,―Content Management‖ provides a system for storing and securing electronic documents, images, and other files(Underdahl, 2011).
2.3 Task-Technology Fit Theory& Extending Model
The core of a Task-Technology Fit (TTF) Model is a constructs which are matching with the capabilities of the technology to support a task (Goodhue and Thompsan, 1995). TTF models have four key constructs; Task Characteristics, Technology Characteristic which together affects the third construct Task-Technology Fit, which in turn affects the outcome variable, either performance or utilization (Dishaw, Strong &Blendy, 2002). TTF model indicated that IT will be used when the functions available to the user support the activities of user. The TTF Model is studied in various levels; there are individual level, group level, and process level starting from individual level; the actors may use IT to assist them in the performance of their work as long as it fit with their tasks.TTF is the correspondence between task requirement, Individual abilities, and the functionality of technology(Goodhue and Thompsan,1995). The studies TTF in group level that effect group performance is a fit between a group’s task and IT to support it. Finally, the study of the fit between process and IT and its impacts on business process performance is a process-level fit that incorporates process-related, IT-related, and IT-use context predicting process performance (Gribbins,Subramaniam, & Shaw, 2006).The technology-to-performance chain (TCP) Model helps end users and organizations to understand and make more effective use of information technology. The TPC model combines insights from research on user attitudes as predictors of utilizations and task-technology fit as a predictor of performance (Staple&Seddon, 2004).The Task-Technology Fit model and Technology Acceptance model(TAM) were combined into the comprehensive model that capture two different aspect of user’ choices to utilize IT. TAM is behavior model that describe users’ beliefs and attitude of using IT (Dishaw, Strong &Blendy, 2002). In General, Users attempt to use IT because it improves their job performance. TTF Model suggested that user choose to use IT because it is compatible with their tasks and improve job performance (Goodhue and Thompson, 1995). In the combined model, the construct perceived usefulness, perceived ease of use and intention to use tool is direct effects on IT utilization. The result of combining the two models provided a better model of IT utilization that either an attitude or a fit model provided separately (Dishaw and Strong, 1999).
2.4 Process-Technology Fit Model
The TTF Model indicating in process level is a Process-Technology Fit (PTF) Model that investigates the fit between process and information technology and its impact on organizational process performance. A process-level fit model provides a greater understanding on IT than models focusing in group or individual level. Poor fit of IT can lead to non-usage and impede process performance goals.The core of a PTF Model is a constructs which are matching with the capabilities of the technology to support a collection of activities or tasks in the process. The PTF Model have 5 key constructs; ―Process Feature‖ , ―IT Feature‖,― Process-Technology Fit‖,―IT Context Use‖, ―Process Performance‖. The PTF Model is in determining the level of appropriateness between process and it feature are equally important to indicated process performance (Gribbins, Subramaniam, & Shaw, 2006).
2.5 Business Process Performance
The Business process Performance is a capability to operate activity that achieve process objective and deliver efficiency, effectiveness and quality results ( Gribbins, Subramaniam, & Shaw, 2006; Melville, Kraemer &Gurbaxani, 2004). The business performance measurement can be grouped into 5 categorizes; ―Effectiveness‖ is a process characteristic indicating the degree to which the process output (work product) conforms to requirements. ―Efficiency‖ is a process characteristic indicating the degree to whichthe process produce the required output at minimum resource cost. ―Quality‖ is the degree to which a product or service meets customer requirement and expectation. ―Timeliness‖ is a unit of work was done correctly on time. ―Productivity‖ is a ratio of production output to what is required to produce it (inputs). The measure of productivity is defined as a total output per one unit of a total input.
3. Model and Hypotheses
Figure1: Conceptual Framework
The perceived process technology fit (PPTF) framework which incorporated technology acceptance model variables in predicting loan origination process performanceis developed from various supported researches. Fig.1 shows the conceptual model for this study.The independent variables in the model are 1) Perceived Process-Technology Fit 2) Intention to use and 3) IT Utilization. These four
independent variables are hypothesized to have an effect on dependent variable, namely, the Business Process Performance. The questions and the measures for each of variable are shown in Table 1 listed below.
3.1 Measurement
TABLE 1
QUESTIONS AND MEASURES FOR EACH OF VARIABLES
Factors Questions (Measures) items
Perceived Process Technology Fit
The functionalities of BPM Technology were veryadequate for loan origination process.
PPTF1
The functionalities of BPM Technology were very appropriate for loan origination process.
PPTF2
The functionalities of BPM Technology were very useful for loan origination process
PPTF3
The functionalities of BPM Technology were very compatible with for loan origination process.
PPTF4
The functionalities of BPM Technology were very helpful for loan origination process.
PPTF5
The functionalities of BPM Technology were very sufficient for loan origination process.
PPTF6
The functionalities of BPM Technology made task easy for loan origination process.
PPTF7
In general, the functionalities of BPM Technologywere best fit the task.
PPTF8
Intention to use
I intent to use BPM Technology to operate my task on loan origination process.
IU1
I expect to use BPM Technology to operate my task on loan origination process.
IU2
I plan to use BPM Technology to operate my task on loan origination process.
IU3
IT Utilization How frequencies using BPM Technology to operateyour tasks on loan origination process in last few months.
( < 1 Hr./Week , 1-8 Hr./Week, 9-16 Hr./Week, 17-24 Hr./Week, > 24 Hr./Week)
UT1
How frequenciesusing BPM Technology to operate your tasks on loan origination process in present.
( < 1 Hr./Week , 1-8 Hr./Week, 9-16 Hr./Week, 17-24 Hr./Week, > 24 Hr./Week)
UT2
How frequenciesusing BPM Technology operate your tasks on loan origination process in next few months.
( < 1 Hr./Week , 1-8 Hr./Week, 9-16 Hr./Week, 17-24 Hr./Week, > 24 Hr./Week)
UT3
Business Process Performance
I can efficiently operate my tasks on loan origination process. BPP1 I can operate my tasks on loan origination process with minimum
resources.
BPP2
I can shorten time to operate my tasks on loan origination process. BPP3 I can operate my task to achieve loan origination objectives. BPP4 I can operate my tasks on loan origination process on time. BPP5 I can operate my tasks on loan origination process that meets
customer requirement and expectation.
3.2 Hypotheses
The Perceived task technology fit refers to the congruence among the perceived capabilities of technology, taskrequirements, and the competence of users with the task and the system(as cited in Lin & Huang, 2008).The combined models are Task-Technology Fit model and Task-Technology Acceptance model (Dishaw& Strong,2002; Klopping& Mckinney,2004) indicated that user willing to useIT tool to operate their work when the technology compatible with their task. The combined TTF/TAM model that applied with E-Commerce to predicts the intention to use and utilization (Klopping&Mckinney,2004). In the context of E-Tourism, TTF is positively related to the intention to use tourism web sites. This can propose the hypotheses as follows:
H1: The perceived process technology fit is positively related to intention to use IT.
The study of utilaztion was started from attitude and behavior (Irick, 2008). The utilaztion was measured by determining actual daily use or time spent using computer systems and number of business tasks for which the computer system were used (Goodhue & Thomson, 1995; Zain et al., 2005). It is a frequency of tool use under working environment
(
Dishaw& Strong, 1999)
. However,user will use computer systems to operate their work when the technology fit with their task.The combined TTF/TAM model is a merging of fit between task and technology and behavior that influence using IT(
Sandy &Seddon, 2004; Strong, Dishaw, &Bandy, 2006;Iric 2008; Larsen et al.,2009).This can propose the hypotheses as follows:H2: The perceived process technology fit is positively related to IT Utilization.
The TTF Model was started from individual level, group level, and process level.TTF in individual level represent the correspondence between task requirement, Individual abilities, and the functionality of technology (Goodhue and Thompsan, 1995). The studies TTF in group level that effect group performance is a fit between a group’s task and IT to support it. Finally, TTF in process level (Process-Technology Fit) is the study of the fit between process and IT and its impacts on business process performance. These TTF level studies indicated that task and technology fit is positively related to performance. This can propose the hypotheses as follows:
H3: The perceived process technology fit is positively related to business process performance.
The Task-Technology Fit model and Technology Acceptance model(TAM) were combined into the comprehensive model that capture two different aspect of user’ choices to utilize IT. The ease of use, perceived usefulness and intention to use are influence IT Utilization. This result is apply with e-commerce (Klopping&McKinney, 2004) that descript that if user intention to use e-commerce technology, their will frequent use online shopping website. This can propose the hypotheses as follows:
The performance is a capability to operatethe activities that ensure to achieve goals with an effective and efficient manner.The TTF Model, which are matching with the capabilities of the technology to support a task (Goodhue and Thompsan, 1995). This model started from individual level and group level. In Individual level, the
utilization is influence to individual performance. In Group level, IT utilization is influence to group performance (Zigure&Buckland, 1998).This can propose the hypotheses as follows:
H5: The IT Utilization is positively related to business process performance.
4. Research Design
4.1 Population and Sample
The population for this study is the employeesworking in commercial loan origination process in Thai commercial banks using business process management technology to operate their task.With 95% confidence level (Z = 1.96), variance (σ) of 1.58(Hair, Anderson, Tatham and Black, 2006),margin error of 5% (0.05), lowest mean of 2.98(Klopping&McKinney, 2004) , and E = [margin error] * [lowest mean]; the sample size for infinite population is 275.89 (given by the formula: [Z2σ2] / Ε2) (Klopping&McKinney, 2004). With the sample size for infinite population of 275.89 and the sample size which is given by the finite population correction is 280 samples.
4.2 Data Collection
This study applies survey data collection method withand paper based and online questionnaires that were administered to a convenience sample of 283 current employeesworking in commercial loan origination process in Thai commercial banks. Their responsibility is related to end-to-end lending process starting fromapplication pre-qualification, credit approval, account initiation andactivation and using a business process management technology to operate their task.
4.3 Research Instrument
This study is quantitative research with paper based and online survey. Nominal scale is used for collecting opinion of current employeesworking in commercial loan origination process in Thai commercial banks. The questionnaire composes of 3 parts; Part I isa selective respondents question about using of business process management technology on lending activities. Part II is a survey of perceived process technology fit on loan origination process performance withthe Interval scale (5-point Likert scale).Part III is a demographicsurvey. These measures are shown in Table I.
5. Data Analysis and Results
5.1 ReliabilityAssessment
The cronbach’s alpha statistics of measures for each factor—perceived process-technology fit, intention to use, IT Utilization and business process performance are .883, .820, .954, and .887. All reliability statistics are over 0.7, which express that all measurements for each factor have good reliability (Kloping&Mckinney, 2004).
5.2 Descriptive Analysis
Frequency evaluation: The samples are male and female equally. They are young worker 21 – 30years old.Average year experience in loan origination in this study is 1-10 years. The responsibilities in loan origination are Credit Data Analyst 38.9 %, Credit Analyst 25.4%, Credit Approver 14.8% and others 20.8%.
Nominal distributionevaluation: Skewness/ Std. Error of Skewness value between 3 and -3, is used as the criteria of bell-shaped normal curve. This show normal distribution and scatter based on statistical assumption which will not generate inaccurate conclusions. For independent variables in this study, all of them are based on statistical assumption.
5.3 Data Reduction and Factor Analysis
Regression analysis and factor analysis using principle axis factoring extraction and varimax rotation were used to test the research model and hypotheses with Eigen value not less than 1 and factor loadings of each factors are more than 0.5(Hair, Anderson, Tatham and Black, 2006). There are 4 group of data reduction as follows: The factor of perceived process-technology fit, the factor of intention to use,the factor of IT utilization, and the factor of business process performance.These factors are shown in Table 2.
Table 2: Factor Loading
Measured Variables Factor Loading Business Process Performance
BPP4 0.858 BPP5 0.843 BPP6 0.808 BPP3 0.790 BPP1 0.781 BPP2 0.773
Measured Variables Factor Loading
IT Utilization
UT2 0.964
UT1 0.955
UT3 0.955
Measured Variables Factor Loading
Perceived Process-Technology Fit
PPTF4 0.774 PPTF3 0.768 PPTF8 0.761 PPTF2 0.754 PPTF5 0.749 PPTF7 0.740 PPTF1 0.709 PPTF6 0.682
Measured Variables Factor Loading
Intention to Use
IU2 0.872
IU3 0.863
5.4 Results
Table 3 Results of Hypothesis Testing
Hypotheses Results
H1: The perceived process technology fit is positively related to intention to use.
Supported
H2: The perceived process technology fit is positively related to IT Utilization. Supported H3: The perceived process technology fit is positively related to business
process performance.
Supported
H4: The intention to use IT is positively related to IT Utilization. Supported H5: The IT Utilization is positively related to business process performance. Supported
Figure 2: Results of Model
6. Conclusion and Recommendations
This work focused on studying the factor that could affect loan origination performance.
This research evaluated the impact of perceived process technology fit on loan origination process performance that is a process-level fit model. First, perceived process technology fit had a positive significant to intention to use. Second, perceived process technology fit and intention to use had a positive significant to utilization. Finally, perceived process technology fit and IT utilization had a positive significant to business process performance. Based on the results of this study, It is create new model to identify loan origination process performance that specify fit between loan origination process and business process management technology, intention to use and IT utilization that effect loan process performance. Executive is able to apply the business process management technology which provides business process automation based on pre-defined rules, real time information analytics and storing electronic documents to enhance loan origination process performance with efficiency, effectiveness, productivity, timeliness, loan quality, shorter time to market and meet customer expectation.
For future research, the study of impact of process technology fit on loan origination process performance is essential to increase our contextual understanding of
loan origination performance by set an experimental design with control variables for business process management technology and establish a factor that effect to loan origination performance and try to apply this model in other industry.
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