The use of simulation for evaluating branch-less banking via cellphones
The use of simulation for evaluating branchlessbanking servicing opportunities via cell phones (Case Study – Palestine Islamic Bank) Researcher Ashraf Al-Astal Supervisor Prof. Dr. Yousif Ashour
ContentsResearch Background Research Methodology Research Problem Results & AnalysisResearch Objectives Conclusions Theoretical Study Recommendations Future Studies
Research Background Research Background Facts• One of the most remarkable technology stories of the past decade has been the spread of mobile phones across the developing world. In fact, mobile devices have become an integral part of everyday life.• Mobile telecommunication services worldwide have experienced a rapid growth. Total number of subscribers will exceed 2.8 billion by the end of 2008 (GSA, 2008).• The rapid spread of mobile phones means that the number of mobile users already exceeds the number of Personal Computers (PCs) world wide.
Research Background Research Background FactsFigure (1.2)Projected installed baseof PCs and mobilephones world wide[Source: Merwe (2003)]
Research Background Research Background FactsFigure (1.3)Number of mobile devicesgrowth vs. PCs per 100inhabitants in Palestine[Source: Reproduced from, ESCWARegion (2006)]
Research Background Mobile Financial Services • These facts leads us to conclude that mobile phones will be the cornerstone of Mobile Mobile Commerce (M-Commerce) by offering a Financial Services communications channel for initiating and executing on-line financial transactions. • Mobile Financial Services (MFS) are new phenomena in the world of M-CommerceM-Banking M-Payment which helps customers to interact with a bank via a mobile device and makes banking virtually anywhere on a real-time basis a reality.
Research Background World Wide Success Stories are several successful stories for There implementing M-Banking and M-Payments services around the world in banking and telecommunication industries: - In South Africa for example, WIZZIT Bank, a division of the South African Bank of Athens[Source: CNN]
ResearchBackground World Wide Success Stories There are several successful stories for implementing M-Banking and M-Payments services around the world in banking and telecommunication industries: -In the Philippines, Globe Telecom Company has been offering branchless banking since 2000. Its G-cash service enables customers to use cell phones to pay bills, repay loans, or purchase goods at shops (it’s effectively a debit card). In the Philippines, 1.3 million people now have G-cash accounts with Global Telecom. [Source: (Anklesaria Aiyar, 2007)]
Research Background Palestine Challenges Palestine needs to learn from these models especially that bankbranches in Gaza Strip area are:- suffering from limitations on the supply of currencies used in Palestine(mainly Israeli Shekels, US Dollars and Jordanian Dinars) used for day-to-daytransactions.- besides the irregularity of salaries dates which caused banked customers toincrease the demand on banking facilities during salary withdrawal dates.
Research Background Banking Sector in Palestine 180 160 140 Numberof Banks/Branches inFigure (1.4) 120 100 Bank Palestine 80 BranchThe development of banks 60and its branches in 40Palestine 20 0[Source: Reproduced and modified 1995 1998 1999 2002 2006 1996 1997 2000 2001 2003 2004 2005 2007from El-Kourd (2007),Palestine Monetary Authority)] Year
Research Problem Research ProblemThe main question of this study is: What will be the impact of implementing Mobile FinancialServices on Tellers and ATM service channels for Palestine IslamicBank (Khanyounis Branch) in terms of total service costs andcustomers waiting time through these service channels?
Research Objectives Research Objectives The main objective of this research aims to evaluate banking servicing opportunities via cell phones as an opportunity for branchless operations that may reduce the cost of the delivered services, improve customer satisfaction, and develop new sources for revenue. This main objective can be sub-divided into the following specific tasks in order to be achieved:- To discuss mobile emerging technologies and its implications forbusiness. In addition, this study will set the differences and similaritiesbetween E-Business and M-Business applications.
Research Objectives Research Objectives (Continued)- To highlight banking servicing opportunities via cell phones and the potentialbenefits of adopting MFS applications (M-Banking and M-Payments) as apromising M-Commerce application for banks and customers in Palestine.- To highlight possible factors that may affect the usage of MFS in Palestine.- To build a simulation model for a bank branch as to study the impact ofadopting MFS as an opportunity to: Reduce cost of distributing services; Improve customers waiting time; and Provide new source of revenue.- To construct a Meta-Models ( Regression Models) for the simulationexperiment that approximates the relationships between different combinationsof possible opportunities and its responses with statistical models (typicallyregression models).
Theoretical Study Conceptual Background The adjective “Electronic”, used within the specific contexts of “E-Business”or “E-Commerce”, signifies an “anytime access” to business processes. Theaccess takes place using computer networks (it is in this case stationary). Theservices are therefore not completely independent of the current geographiclocation of the user (Hohenberg and Rufera, 2004). The adjective “Mobile”, used within the specific contexts of “M-Business” or“M-Commerce”, signifies an “anytime and anywhere access” to businessprocesses. The access takes place using mobile communication networks, makingthese services independent of the geographic location of the user (Hohenberg andRufera, 2004).
Theoretical Study Conceptual Background For Example: SMS ServicesFigure (2.1) M-Business M-Commerce MFSA holistic perspective of M-Businessand M-Commerce[Source: Tiwari and others (2007)] E-Business E-Commerce For Example: Internet Services
Research Methodology Research MethodologyFigure (4.1)Phases andsteps of thissimulationstudy[Source: Reproduced and modified from,Banks (2000)]
Research Methodology Data Collection Change Point AnalysisChange-Point Analysis was used to detect arrival patterns per day ofmonth. (Chandra and Conner, 2006) used this technique to develop asimulation model with segmented arrival rates as to analyze a realqueuing system for a bank in Indonesia. Hawkins formulated the singlemean change-point model as follows (Chandra and Conner, 2006):Where τ is the change-point between the two segments of data.
Research Methodology Data Collection Change Point AnalysisFigure (4.3)CPA revealed twodistinct segmentsfor the number ofcustomers visitingtellers’ servicedistribution channelper month
Research Methodology Data Collection Change Point AnalysisFigure (4.4)CPA revealed twodistinct segmentsfor the number ofcustomers visitingATM servicedistribution channelper month
Research Methodology Data Collection Arrival Rates Non-Stationary Poisson Process The arrival process was modeled using customers’ arrival statisticscollected for customers visiting tellers’ area and ATM service distributionchannels. Customers’ arrival statistics shows that the inter-arrival timesfluctuate throughout the day hours, therefore it follows a Non-StationaryPoisson Process (NSPP), (i.e., the arrival rate of customers is a functionof time).
Research Methodology Data Collection Arrival Rates Non-Stationary Poisson ProcessTable 4.3AIA outputexpressions forTellers servicechannel arrivals
Research Methodology Data Collection Arrival Rates Non-Stationary Poisson ProcessTable 4.4AIA outputexpressionsfor ATM servicechannel arrivals
Research Methodology Data Collection Arrival Rates Arena Input AnalyzerFigure 4.5AIA sample output for thetime period (9:00-10:00)AMwhich was sampled fromTellers service channelarrivals during a normal day p value greater than 0.05
Research Methodology Data Collection Service RatesFigure 4.6Service times forservice channels
Research Methodology Verification and ValidationFigure (4.30)Model verification andvalidation relations
Research Methodology Verification and Validation Two verification techniques were used:1- After the model has been developed, the researcher has subjected the model tospecial input testing. Verification has been conducted by close observation of theanimated interface during extended runs of the model.2- At a number of times during the model building phases the model was shown tothree Arena simulation experts. Two validation techniques were used:1- The first of these, and the most extensively used, was the animation. Themodel’s operational behavior is displayed graphically as the model moves throughtime.2- The second validation technique was a graphical comparison of the actual andsimulated input arrivals.
Research Methodology Design of Experiment Central Composite DesignFigure 4.39Construction ofCentral CompositeDesign (CCD)[Source: Modifiedfrom Sanchez (2007)]
Research Methodology Design of Experiment Central Composite DesignTable 4.6Design matrix fornormal dayconfiguration
Research Methodology Design of Experiment Central Composite DesignTable 4.7Design matrix forrush dayconfiguration
Research Methodology Meta-Models (Regression) The meta-model could be regarded as a proxy for the full simulation model’sresponse surface; all we would need is a pocket calculator or spreadsheet toevaluate any combination of interest (Law, 2006).
Research Methodology OptimizationExpected Earlier Adopters of MFS in Palestine A recent study by (Al-Hendi, 2007) founds that 36.5% of Palestinianpopulation are willing to use 3G mobile based applications. The interest in 3Gtechnologies by Palestinian society may reflect the interest in the new ITCtrends and innovations.
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Normal Day Lower UpperTable 5.36 Name Goal Limit Limit PT (Number) is in range 1 3Constraints TT (Number) is in range 0 2and goals to be MFS (%) is equal to 36.50 20 60achieved for a Teller Area Total Cost ($/Day) minimize 112.47 1131.51normal day Customer Wait Time – Tellers Area (Minutes) is in range 5 10type Net Profit ($/Day) maximize 9.11 26.80
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Normal DayFigure 5.17Desirability plot ofnormal day solutions
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Normal DayFigure 5.18Total cost response oftellers channel duringnormal day type
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Normal DayFigure 5.19Customers waitingtime response of tellerschannel during normalday type
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Rush Day Lower Upper Name Goal Limit LimitTable 5.40 PT (Number) is in range 3 5 TT (Number) is in range 0 2 MFS (%) is equal to 36.50 20 60Constraints and Teller Area Total Cost ($/Day) minimize 214.26 2562.28goals to be Customer Wait Time – Tellers Area (Minutes) is target = 10 10 15achieved for arush day type ATM Area Total Cost ($/Day) minimize 17.78 249.24 Customer Wait Time – ATM Area (Minutes) is in range 0.29 13.23 Net Profit ($/Day) maximize 20.59 62.42
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Rush DayFigure 5.21Desirability plot ofrush day solutions
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Rush DayFigure 5.22Total cost response oftellers channel duringrush day type
Results & Analysis Optimization Using RSM at 36.5% of customers use MFS Rush DayFigure 5.23Customers waitingtime response of tellerschannel during rushday type
Conclusions Conclusion s systems in the bank for both By simulating the behavior of the queuing types of days at the level of 36.5% of customers are willing to use MFS, the study founds that: y Normal Da Rush Day 2 PT, 0 TT, 1 ATM 4 PT, 0 TT, 1 ATMExpected ATM ATM Tellers Tellers Expected ATM ATM Tellers Tellers Net Channel Channel Channel Channel Net Channel Channel Channel Channel Profit Wait Time Cost Wait Time Cost Profit Wait Time Cost Wait Time Cost+ 15.92 0 12.61 17.98 350.92 + 37.10 26.33 486.52 43.03 1735.47 ($/Day) (Minutes) ($/Day) (Minutes) ($/Day) ($/Day) (Minutes) ($/Day) (Minutes) ($/Day) X 0 12.61 6.01 119.23 X 3.17 65.04 9.93 447.70 ($/Day) (Minutes) ($/Day) (Minutes) ($/Day) ($/Day) (Minutes) ($/Day) (Minutes) ($/Day)
Conclusions Conclusion s- Banking will no longer be constrained to conventional service channels.- Mobile Financial Services (MFS) are new phenomena in the world of M-Commercewhich helps customers to interact with a bank via a mobile device and makesbanking virtually anywhere on a real-time basis a reality.- If implemented proficiently, MFS can help financial institutions and banks inPalestine to improve customer acquisition and customer retention, reduce totalservice costs for costly branch offices by migrating simple transactions away fromthese branches.
Conclusions Conclusion sThe challenge for banking sector in Palestine is not to getunbanked to the bank, but to get the bank to the unbanked.
Recommend- ations Recommendations- Palestinian banks need to have a vision for successful implementation of MFSwith smaller pilot projects so they can gain experience with MFS and build supportfor change across the bank. Also, they need to measure and monitor results on aregular basis in order to ensure that they maintain world class performance levels.- Palestinian banks must establish MFS that works across all Palestinian cellphonenetworks and with any cellphone model in order to provide mobile accounts forcustomers. This will result in expanding their customer base into unbankedcustomers that may not live in urban areas, or may not have access to branches;therefore it is important to pay considerable attention to MFS application interfaceand content to suit the targeted segments.
Recommend- ations Recommendations- The Palestinian Monetary Authority is challenged to create an enablingenvironment for the sustainable growth of MFS. This includes the development ofa new set of effective regulations and laws that will supports innovations,mitigates risks that threaten its development and encourage Palestinian banks toimplement competitive MFS, taking into considerations the difficulties appearedin Gaza Strip area for supplying Israeli Shekels, US Dollars and Jordanian Dinarsto the Palestinian banks for day-to-day transactions which caused manydifficulties for both customers and banks.
Future Research Studies Future Research Studies Further research could focus on and go deeper into investigatingthe customers behavior to reveal some of the complexities of technologyadoption that can be applicable to MFS. The aim is to gain some insight into the possible determinants ofsuccess or failure in MFS adoption among consumers in Palestine.