The paper presents the collaborative systems classification by field of application. There are described the collaborative tagging systems and an implementation of this kind of systems is analyzed in a commercial bank. The Collaborative Multicash Servicedesk application is presented in order to implement an auto-complete facility.collaborative systems, tagging, auto-complete, banking, application

Cristian Ciurea

English

Research Papers in Economics

 
 
A BANKING COLLABORATIVE TAGGING SYSTEM 
 
Cristian Ciurea
1 
 
Abstract 
 
The paper presents the collaborative systems classification by field of application. There 
are described the collaborative tagging systems and an implementation of this kind of 
systems is analyzed in a commercial bank. The Collaborative Multicash Servicedesk 
application is presented in order to implement an auto-complete facility. 
 
Keywords: collaborative systems, tagging, auto-complete, banking, application. 
 
1. Collaborative systems classification 
 
Collaborative systems are encountered in several areas, such as business, banking, health 
and education. These environments offer elements that allow the development of 
collaborative tools, so as to enrich agents’ collaboration. [1] 
 
The collaborative systems are developed based on a set of specifications that were defined 
in the analysis stage in order to establish the objectives for the development process. A 
collaborative system must behave and must give the results the agents want and that they 
have stated at the start. [2] 
 
The agents of a collaborative system represent any entity interacting or exchanging data in 
the system, be they people or software applications. Every agent’s roles can be seen as a 
group of processes that an agent can execute. A process is one of the ways to use the 
collaborative system. The whole set of available processes define what the collaborative 
system is used for and demand a specific configuration. [3] 
 
The collaborative systems are classified in many categories and there are a lot of criteria 
for collaborative systems classification. Many types of collaborative systems were 
developed in the practice, some of them being encountered in all activity fields. 
 
Field of application classifies collaborative systems in: collaborative systems in 
education, collaborative systems of defense, collaborative systems in production, 
collaborative banking systems, electronic business systems, public administration 
systems, media software development systems, collaborative functional systems, 
collaborative micropayment systems, collaborative planning systems, collaborative 
tagging systems, collaborative writing systems and collaborative medical systems. 
                                                             
1 Cristian Ciurea, Economic Informatics Department, Academy of Economics Studies, Bucharest, 
Romania, email: cristian.ciurea@ie.ase.ro 
  
In the knowledge-based society, a very important research subject is provided by the 
collaborative tagging systems. This kind of systems provides a new means of organizing 
and sharing resources [4] [5]. 
 
2. Collaborative tagging systems 
 
There are many collaborative tagging systems on the web, significant examples being 
search engines like Google, Yahoo, Bing and others. They offer auto-complete options 
and suggestions to help the users to quickly find something. If you want to find a video on 
YouTube, but you do not remember exactly the video name, the collaborative tagging 
system will help you by displaying video names appropriate with your query string. 
 
If a collaborative tagging system is considered, represented by a service desk application 
used in a bank that offers technical support for the electronic payments service, then the 
followings specifications are taken into consideration: 
-  use tags for ensure the correct search in the database with customers; 
-  build the application as a collaborative tagging system that offer auto-complete 
options and suggestions to help the users to quickly find something; 
-  determine the categories of incidents with the great number of requests; 
-  involve the simultaneously work of many analysts. 
The goal of this application is to store and process the customers’ requests, solved 
by the helpdesk analysts within a commercial bank. 
 
The implementation of this application was made under the requirements of bank 
management, using the information technology approved by the bank, so that the final 
software product meets all quality characteristics. 
 
3. Example of a collaborative tagging system in a bank 
 
A bank is a collaborative system with high complexity, with a large number of 
components and a large variety of links between them. The complexity of the banking 
system is given by the operations they carry out, but also by the collaboration between 
different banks from different countries and by the alignment to standards imposed by the 
regulations in this worldwide field. 
 
All the information systems from a bank are collaborative systems, because they require 
the cooperation, communication and coordination of many software applications in order 
to achieve a common goal. This common objective can be represented by the successful 
processing of a payment order or by the interest calculation of a term deposit. 
 
In a bank that offers helpdesk services for the Multicash application, a collaborative 
tagging system was implemented, in order to determine the categories of incidents with 
the great number of requests. This system is represented by an application, Collaborative 
Multicash Servicedesk – CMS, which is available at http://collaborative.ase.ro/teza.  
  
 
The Collaborative Multicash Servicedesk application goal is to store and process the 
customers’ requests, solved by the Multicash helpdesk analysts within a commercial bank 
in Romania. 
 
In the Collaborative Multicash Servicedesk application only authorized users have access 
based on a user name and password. The application administrator is dealing with the 
access rights of each user, adding and deleting some users according with the bank 
security rules. 
 
The CMS application involves three categories of users: customer, bank analyst and 
administrator. Each user has a different interface depending on its category. The 
customers have the possibility to post a problem, to view an existing solution from the 
knowledge database and to view the status of their posted problems. The bank analyst can 
take a problem posted by a customer and solve it. The administrator has the possibility to 
generate reports regarding the status of problems solved by each bank analyst. [6] 
The fields to be completed or selected by the bank analyst are: 
-  customer name, based on suggestions from a predefined list of Multicash 
customers; 
-  the contact person of the customer who made the call; 
-  the request category, which was a drop-down list with predefined categories and 
related codes; 
-  request description, which is a field for adding the details of the problem; 
-  the way to solve by selecting the appropriate option. 
The application provides a search option of a request in the database and the 
export of requests table in Microsoft Excel. 
 
The customers have also an interface in which they can fill in a request. This option is 
used for the non-phone requests solved by the bank analysts. 
 
In figure 1 is presented the manner in which an analyst fills the customer name, using the 
tagging facility offered by the Collaborative Multicash Servicedesk application. By 
entering a word or few characters from the customer name, the system automatically 
search through the clients database the name appropriate to the string entered. The search 
is realized in a table with 6.000 customers with the help of JavaScript and C# functions.   
  
 
Fig. 1. Tagging facility for customer name 
 
The collaborative tagging system represented by the CMS application offers an auto-
complete facility in order to help the analyst to correctly fill and find the name of 
customers and users which called the technical support. 
 
The CMS application is a collaborative system because involve the simultaneously work 
of many analysts, which have the possibility to see and find who spoke with a particular 
customer, which problem had the customer and how it was solved. Being a multi-user 
application, CMS is collaborative by its goal, meaning the recording and processing of 
customer requests in a period of time.   
 
In figure 2 is presented the manner in which an analyst fills the user name, meaning the 
person that called the helpdesk assistance. The database of users contains 12.000 records. 
The system will search the user name in this database, showing all the records which 
accomplish the criteria.  
  
 
 
Fig. 2. Tagging facility for user name 
 
A part of the C# code for implementing these searches and selections from the database is 
presented bellow: 
 
string connString; 
int i, rec_countClienti, rec_countPers; 
connString = "Provider=Microsoft.Jet.OLEDB.4.0; Data Source ="  + 
Request.PhysicalApplicationPath + "\\files\\baza.mdb"; 
OleDbConnection objConnection = new OleDbConnection(connString); 
objConnection.Open(); 
string strSqlClienti = "select * from Clienti"; 
string strSqlPers = "select * from Persoane"; 
OleDbCommand  objCommandClienti = new  OleDbCommand(strSqlClienti, 
objConnection); 
OleDbDataAdapter adapClienti = new OleDbDataAdapter(objCommandClienti); 
DataSet dsClienti = new DataSet(); 
adapClienti.Fill(dsClienti); 
rec_countClienti = dsClienti.Tables[0].Rows.Count; 
string[] nameClienti = new string[rec_countClienti]; 
for (i = 0; i < nameClienti.Length; i++) 
nameClienti[i] = "'" + dsClienti.Tables[0].Rows[i][0].ToString() +"'"; 
string arrNameClienti = "nameClienti"; 
arrValueClienti = String.Join(",", nameClienti);  
OleDbCommand objCommandPers = new OleDbCommand(strSqlPers, objConnection); 
OleDbDataAdapter adapPers = new OleDbDataAdapter(objCommandPers); 
DataSet dsPers = new DataSet(); 
adapPers.Fill(dsPers); 
rec_countPers = dsPers.Tables[0].Rows.Count; 
string[] namePers = new string[rec_countPers]; 
for (i = 0; i < namePers.Length; i++) 
namePers[i] = "'" + dsPers.Tables[0].Rows[i][0].ToString() +"'"; 
string arrNamePers = "namePers"; 
arrValuePers = String.Join(",", namePers); 
objConnection.Close(); 
 
The JavaScript code is combined with C# code to realize the tagging and auto-complete 
facilities: 
 
<script> 
var customarrayClienti=new Array(<%=arrValueClienti%>); 
var customarrayPers=new Array(<%=arrValuePers%>); 
</script> 
 
The efficiency of the interaction between Collaborative Multicash Servicedesk application 
and their users is measured with some indicators such as:  
-  the necessary time for data introduction in a form: is measured in seconds and it is 
measured starting the selection or completion of the first field on the form by 
pressing the button for data transmission;  
-  the number of data re-input, because of errors: every press of the button for data 
transmission, a counter is automatically incremented;  
-  the costs of development and use.  
From the CMS application, a situation is generated every month in order to check 
the situation of the requests and the customers that claim problems. 
 
The results obtained for the March 2010 are shown in the table 1, where are presented the 
problems that the customers complained to the bank and the number of times they appear.   
 
Table 1. Number of requests by category 
Category  Number of requests 
Add new accounts in the client application  26 
Add new users in the client application  14 
Other requests  132 
User blocked on the communication  41 
User blocked at logon  20 
Communication initiated  54 
Confirm account balance  71 
Deactivate payments file  1 
Error on starting the application  5  
 
Signature error  46 
Error on see statements  20 
Statements export  1 
Generate electronic signature  20 
Index corrupted in database tables  4 
Training on using the application  14 
Training on see rejected payments  4 
Delivery account statements  7 
Delivery file with bank codes  12 
Delivery files for distributed signature  8 
Change communication channel  1 
Change number of approvals / amount limits  1 
Change name / address of payer  1 
Move the application on another computer  13 
Please repeat job with AC29  9 
Reinstalling the application  7 
Setting print parameters  5 
Setting communication sessions  1 
Training of branches for completing annexes  10 
Transmission interrupted  36 
Check payments status  162 
 
The bank management check this situation monthly in order to see which are the most 
frequently problems of the customers and how these problems can be minimized. Also, 
this report is used by the IT department for establish further improvements of the 
Multicash software. 
 
 
4. Conclusions 
 
Collaborative systems are efficient and achieve results accurately and completely if they 
work the way they are designed to. The development of collaborative systems conduct to 
increase their complexity and the global character of the economy is designed to 
determine, also a global character for many of the collaborative systems. 
 
From informatics point of view, software applications collaborate and are integrated into 
an information system. An electronic payment application works together with the 
application for transactions processing and settlement and with the application for 
rejections monitoring. If any of these three applications is not working, then the customers 
fail to make payments. Collaboration at the level of a banking system is more efficient by 
integrating several applications of the information system. [7] 
  
A collaborative tagging system is very helpful for the agents to quickly find the records 
when working with large databases, such as banking databases. A banking information 
system is thus designed to automate a higher set of current bank operations and provide 
strategic, tactical and operational information necessary in the decision-making process. 
 
 
Acknowledgements 
 
This article is a result of the project POSDRU/6/1.5/S/11 „Doctoral Program and PhD 
Students in the education research and innovation triangle”. This project is co funded by 
European Social Fund through The Sectorial Operational Programme for Human 
Resources Development 2007-2013, coordinated by The Bucharest Academy of 
Economic Studies, project no. 7832, Doctoral Program and PhD Students in the education 
research and innovation triangle, DOC-ECI. 
 
 
References 
 
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[2] C. Ciurea, “A Metrics Approach for Collaborative Systems,” Informatica Economică 
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[3] C. Ciurea, “The Virtual Campus – A Collaborative System,” Economy Informatics 
Journal, Vol. 9, No. 1, Inforec Publishing House, 2009, pp. 39-47. 
[4] C. Au Yeung, N. Gibbins and N. Shadbolt, “Contextualising tags in collaborative 
tagging systems,” Proceedings of the 20th ACM Conference on Hypertext and 
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[5] J. Choi, J. Rosen, S. Maini, M. Pierce and G. Fox, “Collective Collaborative Tagging 
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[6] C. Ciurea, “Collaborative Free Software Development,” Open Source Science 
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[7] C. Ciurea, “Metrics of Collaborative Banking Systems,”  Journal of Applied 
Collaborative Systems, Vol. 2, No. 1, 2010, pp. 16-23. 
 
 

A BANKING COLLABORATIVE TAGGING SYSTEM

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