MSc in Information Systems

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/2481

Students enrolled in the MSc in Information Systems programme are required to submit a thesis as a compulsory component of their degree requirements. This collection contains merit-based theses submitted by postgraduate students specialising in Information Systems. Abstracts are available for public viewing, while the full texts can be accessed on-site within the library.

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Theses and Dissertations of the Sri Lanka Institute of Information Technology (SLIIT) are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License .

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Implementing a RPA Helpdesk to Facilitate a Typical University in Sri Lanka
(2021) Tharindunie, D.S.Hasintha
Robotic Process Automation is focusing on replacing humans by automated systems. Actually, this is not like the traditional workflow. Most universities and institutions are seeking for new methods to minimize the costs and effectively link with the academic based applications as well. Modern educational methods have been developed for the universities and educational institutions. Most of the leading Business Intelligence software vendors provide a number of resources. They are composed of free software access to teach, teaching materials, student evaluation programs, training guidance, research articles, curriculum details, certificate level programs, and training programs.
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Business Continuity through Crisis Situations: Evaluation of Impact of ERP Systems on Business Performance through Crisis Situations in SME of Apparel Industry in Sri Lanka.
(2021) Ranasinghe, N.M.
The economic development is highly impacted by Micro, Small and medium enterprises. In the past few years Micro, Small and medium enterprises have become highly competitive, and the number of organizations have increased with the economic growth. This also has caused Micro, Small medium enterprises to face many challenges and with these challenges to expand their businesses and open organizations to new technologies. But in past few decades academia researchers and business world has debated on the impact that enterprise resource planning systems has on business performance. Further to the effects of enterprise resource planning systems in normal times these systems can positively or negatively impact business performance at the times of crisis. At such times, employees must work remotely due to crisis situations, and this may lead organizations to adapt into enterprise resource planning systems. Hence the main purpose of this research is to evaluate the effects of enterprise resource planning systems have on business performance specially through crisis situations. The crisis in this study mainly focuses on the covid-19 outbreak as this is the most recent crisis that global economy had to face. The globalization has resulted in a complicated, prolonged, and large-scale supply chain. Also, businesses depend on its supply chain to achieve competitive advantage. With the complexity and large-scale nature, the supply chains have become challenging to manage and have been subjected to high risk. To prevail over such supply chain interruptions, sufficient response approaches and risk managing implements should be executed to build an impervious business. This study presents understandings on whether ERP systems facilitates the above-mentioned response plans with interest to minimizing the operational destruction triggered by Covid-19. The study is conducted via exploratory research first to identify the factors which cause successful and productive utilization of ERP systems. The results suggest six likely elements. Based on the findings of the literature review, there hypothesis have been developed to conduct the quantitative analysis. The quantitative analysis is conducted by building a questionnaire and collecting data from stakeholders of Sri Lankan Micro, Small Medium Enterprises (MSME). The questionnaire consisted of thirty six questions – four questions to gather demographic data of the sample and thirty two questions covering six independent variables and two dependent variables with four questions on each variable Four hundred and twenty-three valid responses were gathered from Sri Lankan apparel micro, small and medium enterprises. Data was validated using Cronbach’s Alpha test and the correlation between the variables were assessed using the Pearson’s correlation test. The findings of the study suggests that ERP usage has a highly positive effect on business performance and ERP usage is affected by user satisfaction in a low positive manner while ERP system complexity has a negative low effect on the ERP usage. The paper here onwards builds the framework and hypotheses for the research while showing how the factors suggested the framework. Data collected survey and analysis also is depicted throughout the paper while the last section opens the discussion on how the study gradually concluded the outcomes.
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Factors Determining the User Adoption of Biometric Authentication in Sri Lankan Payment Channels
(2021) Balasuriya, D.M.
Payment channels have become an essential element in people’s lives. There are many emerging payment channels in Sri Lanka such as EDC (Electronic Data Capture)/ POS (Point of Sale)/ kiosks/ Internet Payment Gateway/ Mobile based payment solutions. With the emergence of new payment channels individuals have shown keenness on moving to digital payment channels instead of traditional methods because of its convenience. Despite its popularity it has become a source for financial frauds. The main reason being the lack of security and privacy of payment channels. Most payment channels use traditional authentication methods such as passwords, PIN (Personal Identification Number), OTP (one-time password), or digital cards. These authentication methods are vulnerable, and they are quite often compromised by fraudsters. There financial organisations are now looking at a more user/customer centric authentication method. Biometric is a user/customer centric authentication method where the authentication happens using a biometric trait of the user/customer. Since most Sri Lankans are not tech-savvy it is somewhat of a challenge to make customers use payment channels that has biometric authentication. Therefore, this study looks at the factors that will determine the user adoption of biometric authentication. In order to identify potential factors that could affect biometric adoption a comprehensive literature review was conducted. What previous researchers around the world have discovered were useful in deciding the potential factors; security and privacy, reliability, usefulness, and ease of useTo quantify the impact of each factor on biometric adoption a quantitative research study which had 390 respondents was conducted by the author. After a thorough analysis of the responses, it was identified that security and privacy, reliability, usefulness, and ease of use influences the user adoption of biometric authentication in Sri Lankan payment channels. The author believes this report will be beneficial to various stakeholders in the financial industry and the information technology industry in Sri Lanka as well as similar demographic segments.
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Work From Home (WFH): Challenges For IT Industry In Sri Lanka During COVID19: A Study On Employees Perspective
(2021) Sarathchandra, D.H.D.N.
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Impact of Artificial Intelligence towards democracy in modern society
(2021-04) Amarasekara, E.A.V.A.L.
Open Access
Impact of Artificial Intelligence towards democracy in modern society
(2021-04) Amarasekara, E.A.V.A.L
Artificial intelligence consciousness has gotten a ton of consideration lately, and it's relied upon to have a major effect on our networks later on, with both positive and negative ramifications for vote based system. In this paper, I take a gander at what Artificial intelligence brainpower can mean for common freedoms and majority rules system, assessing the outlining of difficulties, arrangements, and management work in three unique situations. I built up a hypothetical structure dependent on past investigations in this field to play out a near contextual analysis between the European Commission and two nations that are at the front line of understanding AI's difficulties, in particular Sweden and France. The discoveries show that while a few issues are perceived as basic, a few issues, like security, are focused on. As far as difficulties, arrangements, and guidelines, there are a few varieties between the three cases, however, their techniques are fairly comparable. Sweden's technique is to put resources into cultural change by empowering more AI exploration and collaboration, while additionally being steady of guidelines in specific zones. France takes a more management weighty position, suggesting some AI limitations in protection, fighting, and the work market. To make AI more accommodating, the European Commission is underlining responsibility in AI methodology. The shared factor is that the two of them overlook the issue of political race impedance and online right to speak freely, which is distinguished in the writing as one of AI's significant difficulties
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The Effect of Using Online Platform and Campus-Based Classrooms on Student Performance
(2021-09) Fernando, Anton Jude Kumar
As per the existing environment, the COVID-19 has caused the education system, including schools worldwide, to shut down. Nevertheless, nearly 1.2 billion students are out of school worldwide. As a result, education has undergone substantial changes with the initiation of e-learning, through which teaching is conducted essentially and through interactive platforms with the help of technology today. Although several accept that unplanned and accelerated online learning changes – with little teaching, insufficient bandwidth, and limited scheduling – will create an impediment to long-term success by creating a poor user experience, some feel substantial gains in a new composite educational paradigm. However, considering the objectives of the research, it is to examine the effect of using online platform and campus-based classrooms on student performance, examine the required level of Online Platform and Campus-Based Classrooms in the case study area and also to examine the impact and both positive and negative externalities on online platform and campus-based classrooms on student performance, international schools in western province of Sri Lanka which are significant. However based on research questions, it is to understand the factors affecting the appropriate implementation of online platform and campus-based classrooms on student performance, the economic environment have any significance on online platform and campus-based classrooms on student performance, and finally to identify the variation in the level of the implementation of online platform and campus-based classrooms on student performance, international schools in western province in the country. Nevertheless, considering the results and discussion area, it rejects the null hypothesis of the case study of using online platforms and campus- based classrooms on student performance in international schools in the western province of Sri Lanka. Furthermore, it accepted the alternative hypothesis of the case study, and there is a strong relationship between available technology, teaching interactivity, peer collaboration, student engagement and the effect of using online platforms and campus-based classrooms of online platforms and campus-based classrooms in international schools in the western province of Sri Lanka while showing certain variations according to summary item statistics and inter item iv covariance. Therefore, it is required to understand the ways and means of enhancing available technology, teaching interactivity, peer collaboration, student engagement and the effect of using online platforms in order to get better results from online platform and campus-based classrooms in international schools in western province in the country.
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Sentiment Based Approach to Analyse Fake News Related to COVID 19 in Sri Lanka
(2021-09) Somasinghe, K.I.
Generation and spread of fake news have drastically increased with the growth of technology and advancement of online media platforms. Today, rather than using traditional resources to get information, most people rely on the internet and it has become a part of every individual’s life since this is a one of the simplest methods to acquire information on almost everything. This internet based media has become a source of sharing news and these sources are used by companies, political parties as well as social influencers etc. Fake news changes the perception of the viewers and diverts them from the reality. By analyzing fake news in Sinhala Language related to COVID-19 which is a disastrous situation to not only Sri Lanka but the whole world it would be a great advantage to notify people regarding fake news and the resources they use to spread fake news and reduce unethical sharing of news, to protect the authenticity of news that reaches people and the authenticity of the journalism field. This research presents an approach to analyze the effect of polarity in the sentiment of the news data and analyze how it affects towards fake news in Sinhala language using textual data. The proposed model uses natural language processing techniques such as sentiment analysis and machine learning algorithms such as Logistic Regression, Support Vector Machine, Naive Bayes.
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Explore the Scope to Implement Intelligent Enterprise Resource Planning (I-ERP) System in Business Processes
(2021-09) Senarathna, D.M.I.P.
Businesses are known to invest a significant capacity of their funds towards the implementation of Enterprise Resource Planning (ERP) as well as Business Intelligence (BI) systems in order to gain a sustainable competitive edge, to be in par with the advantages that the latest technological advancements are able to provide and to ensure the smooth running of their work processes. In today’s challenging economic environment contained by the context of complicated BI and ERP, these techniques have become key strategical tools, which promptly influences the success of any software project implementation. Not much attention has been given to the integration of “Business Intelligence and Enterprise Resource Planning” which was convert form the traditional ERP system to an Intelligent-ERP system. A few experiments had been conducted in some organizations but most of the projects did not see a conclusion towards a successful integration or completion of the project due to various challenges faced during the implementation process. This research attempts to evaluate and assess the implementation of an Intelligent Enterprise Resource Planning (I-ERP) System in business processes in the company Norlanka Manufacturing Colombo Limited in Sri Lanka; in order to increase efficiency of business processes and use human knowledge effectively for decision making activities and to overcome business related issues such as repetitive and tedious work processes, increased costs and unproductivity. The main methodology that was utilized in this thesis was a primary method that utilized surveys to obtain information from 145 employees working in Norlanka. Using the SPSS tool, the data was analyzed using a number of statistical methods such as correlation, frequencies, descriptive and inferential analysis and the findings revealed that there was a significant link between the independent variables, business values, user engagement, user adoption, operational costs, operational efficiency with the dependent variable implementation of I-ERP in Norlanka. Furthermore, recommendations included, ensuring a change management team is in place, making sure top-level management and other key stakeholders were actively involved and the aspect of customization was considered according to the organization’s aim, objectives and scope.
Open Access
Possibilities Offering a Smart Learning System (SLMS) For Advance Level Students
(2022-02) Rumana, A.S.F
The research intends to examine the possibilities for advanced level students utilizing Smart Learning Management to enhance the students' online learning experience (SLMS). These higher education institutions have made significant financial and other resource investments, but until the use of such systems is made mandatory, the benefits they and the students obtain fall far short of expectations. Researchers have worked very hard and come up with many innovative methods to support this sort of learning settings when it comes to innovations in the educational environment. The goal of smart learning tools is to identify methods of instruction and learning that in some way gain from the application of cutting-edge technology. This research addresses this idea and demonstrates how to improve the current learning management systems (LMS). A self-administered survey questionnaire was used in quantitative research.From Sammanthuri Division School, four schools were chosen. Results from 96 valid replies show that students' attitudes on SLMS features, smart environments, and collaboration between teachers and students have a major impact on their use of the system, whereas internet capabilities Experience& acceptance of the LMS had little bearing. The study examines the variables that might affect these students' acceptance of the SLMS for advanced-level pupils. Variables Teachers' and students' collaboration, students' attitudes about SLMS features, and smart environments are thought of as predictor variables, and it is researched how these factors affect the availability of smart learning management systems (the predicted variable)
Open Access
Analyzing the Performance of Different Text Classification Algorithms for “Dhivehi” Documents
(SLIIT, 2024-12) Mohamed, F.R
This research investigates the effectiveness of various machine learning classification algorithms applied to Dhivehi text-based documents. Dhivehi, the official language of the Maldives, presents unique linguistic challenges for text classification due to its limited digital resources and distinct grammatical structure. The study aims to identify the most suitable algorithm for classifying Dhivehi documents and to provide insights into optimizing text classification approaches for less- resourced languages. The research systematically evaluates the performance of several machine learning algorithms, including Support Vector Machines (SVM), Naive Bayes, Decision Trees, XGboost , Random Forest and Neural Networks. These algorithms are applied to a diverse dataset of Dhivehi text, encompassing various genres and topics. The study employs a rigorous methodology involving data preprocessing, feature extraction, and model training and testing. Performance metrics such as accuracy, precision, recall, and F1-score are used to compare the efficacy of each algorithm. Additionally, the research explores the impact of different text representation techniques, including bag-of-words, TF-IDF, and word embeddings, on classification performance. The findings offer valuable insights into optimizing text classification methods for low-resource languages and aim to advance natural language processing tools specifically tailored for “Dhivehi.” The evaluation highlights that K-Neighbors achieved the highest performance, with an accuracy of 64.7% and F1 scores (macro: 0.640, weighted: 0.642), demonstrating a strong balance between precision and recall. Support Vector Machines (accuracy: 63.9%) and XGBoost (accuracy: 62.8%) also showed competitive results, with SVM slightly outperforming XGBoost in F1 metrics. Decision Tree exhibited the lowest performance across all metrics. By identifying the most effective classification algorithms and representation techniques, this research aims to enhance the accuracy and efficiency of Dhivehi text classification tasks. The results will have practical applications in areas such as sentiment analysis, document categorization, and information retrieval systems tailored for the Dhivehi language. Furthermore, the dataset is publicly available on Mendeley data under the name “Dhivehi Categories data set” to foster future research and innovation in this domain.
Open Access
Development of a Neural Network-Based Framework for Skin Disease Recognition
(SLIIT, 2024-12) Senadhipathi, L.A.N.M
Skin diseases impact humans, animals, and plants and are typically brought on by germs or infections. These ailments include ringworm, yeast infections, brown sports, allergies, and other conditions. Early detection can help lessen the impact of diseases. But there are other risks that the skin can encounter, one of which is illness. Fungi, bacteria, allergens, enzymes, and viruses are the main causes of skin problems. Skin conditions impair not just one's physical health but also their psychological well-being, especially in those who have damaged or even scarred skin. Identifying the condition via manual feature extractions or symptom-based approaches requires time and requires comprehensive data for accurate identification. Serious health concerns are associated with skin diseases, which require an accurate and timely diagnosis for appropriate treatment. In particular, convolutional neural networks (CNNs) have shown promising results in automated skin disease identification recently. In this study, A novel CNN-based approach is presented, achieving a 95% accuracy rate in classifying seven different types of skin diseases from the HAM10000 image dataset. Dermatoscopic images from the HAM10000 dataset are preprocessed and categorized into seven classes: basal cell carcinoma, melanoma, vascular lesions, dermatofibroma, melanocytic nevi, and benign keratosis. After extensive testing and fine-tuning, it achieved an overall accuracy of 95% on the testing set. The outcomes show that the suggested CNN-based method can accurately identify a variety of skin conditions by using the HAM10000 picture dataset. Deep learning techniques can significantly help dermatologists and other healthcare professionals diagnose skin conditions accurately and automatically, enabling them to provide prompt and efficient treatments. This work adds a great deal to the growing field of dermatological computer-aided diagnosis and offers valuable data for upcoming advancements in the identification of skin diseases.
Open Access
Assessing the Feasibility and Effectiveness of Blockchain Technology for Safeguarding Governmental Data Integrity: Focus on Sensitive Diplomatic Communications
(SLIIT, 2024-12) Dilshanie, A.G.C.
This thesis investigates the feasibility and effectiveness of implementing blockchain technology to safeguard governmental data integrity, with a specific focus on sensitive diplomatic communications. Given the increasing importance of data security in an era of digital transformation, this research adopts a comprehensive mixed-method approach. It combines quantitative surveys and qualitative interviews with government IT professionals, blockchain experts, and policy makers to assess the technological, operational, and regulatory dimensions of blockchain implementation. The study reveals that blockchain technology offers substantial benefits in enhancing data security, primarily due to its inherent characteristics such as immutability, transparency, and decentralized architecture. These features are particularly crucial for maintaining the integrity and confidentiality of sensitive diplomatic communications, which are often vulnerable to unauthorized access and tampering. The research highlights that blockchain’s ability to create tamper-proof records and ensure transparent transactions aligns well with the needs of secure diplomatic exchanges. However, the study also identifies several significant challenges that need to be addressed. Issues such as scalability, high energy consumption, regulatory compliance, and the complexity of integrating blockchain with existing governmental IT systems are notable barriers to effective implementation. To address these challenges, the study proposes a detailed framework that includes technical solutions, policy adjustments, and strategic recommendations. This framework
Open Access
Enhancing Block chain Technology in Governmental Operations: A Comprehensive Framework for User Adoption
(SLIIT, 2024-12) Gnanasekara, H. A.
The purpose of this study is to investigate the factors that affect Blockchain adoption in governmental operations in Sri Lanka, and thereby to propose a comprehensive adoption framework for Blockchain technology in Sri Lankan governmental operations. The TechnologyOrganization-Environment (TOE) framework is utilized for this purpose due to its capacity to encapsulate the complexities of technological adoption in the public sector, effectively addressing both internal (organizational) and external (environmental) factors that influence the adoption process. Given the unique structural, regulatory, and data sensitivity challenges of governmental settings, unlike many other models, TOE framework comprehensive integrates employee insights from technological, organizational, and environmental perspectives, making it both adaptable to the public sector’s needs and scalable for implementation across various government entities. More importantly, the TOE framework is uniquely designed to account for the regulatory and operational needs specific to Sri Lankan public sector institutions. It addresses critical compliance requirements, such as data privacy and security regulations, while aligning with the structural intricacies of government workflows, enabling a practical pathway for Blockchain adoption that respect the local regulatory landscape and operational demands. This study has employed various statistical methods to ensure the validity and reliability of the data collected through a structured questionnaire distributed to Grade I – IT Directors to obtain their perceptions and experiences with Blockchain technology. Using the structural equation modelling (SEM), this study reveals that all three perspective of the TOE framework (i.e. technological, organizational and environmental) are significantly influence the Blockchain technology adoption in Sri Lankan governmental operations. More specifically, SEM results show that compatibility, trust, security, support from higher authority, monetary resources, firm size, regulatory support, and rivalry pressure are critical technological, organizational and environmental determinants in developing an adoption framework for Blockchain technology in Sri Lankan governmental operations. The expected impact of the proposed framework based on the findings of this study on public sector operations includes significant improvements in processing times for administrative tasks, a reduction in risks of corruption, and enhanced citizen trust through greater transparency. By addressing the specific challenges faced by the Sri Lankan government in adopting Blockchain technology, this study contributes valuable insights to the discourse on digital transformation in public sector operations
Open Access
AI-DRIVEN SELF-HEALING TEST AUTOMATION FOR ENTERPRISE SOFTWARE SYSTEMS
(Sri Lanka Institute of Information Technology, 2025) Jinarathna, H. D. R. J.
Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) platforms are backbone tools for today’s businesses, helping teams around the company work together efficiently. But because these systems are huge and always changing, testing them gets tricky. Methods we’ve traditionally used—whether having testers run scripts by hand or running automated scripts—can’t keep up. To solve these problems, I’ve built a test automation framework that uses AI to repair itself as it runs. By incorporating Natural Language Processing (NLP) for spotting system changes and Reinforcement Learning (RL) for teaching tests to heal and get sharper, the framework learns to find when a test has broken, to fix the code on the fly, and to keep fine-tuning itself, so people hardly need to step in. I shaped the system by talking to QA engineers about the roadblocks and running pilot cases in a pretend ERP setup. Those conversations, plus the numbers, helped us tweak the design so it feels less like a lab gadget and more like a teammate. Early results are encouraging—flake tests bounce back 35% more often and testers spend 25% less time rewriting logic by hand. My research helps Software Quality Assurance Engineers, learners, and software businesses by offering an easy-to-understand, adaptable way to test big-company software. The results show how using smart technology can make software testing faster, cheaper, and better.
Open Access
Predicting Cryptocurrency Trade Count with Machine Learning Models
(Sri Lanka Institute of Information Technology, 2025) Doluweera,C.Y.P
This study examines the prediction of cryptocurrency trade counts using machine learning. Minute-level market data were cleaned, merged, and enriched with time features to form a reliable dataset. Two ensemble regressors, Random Forest and Gradient Boosting, were implemented alongside baselines, with performance judged mainly by Mean Absolute Error and supported by RMSE. Model tuning and cross validation were used to improve robustness, and results were visualized to compare errors, track actual versus predicted counts, and explain feature influence. Across the tested assets, Random Forest delivered the most consistent accuracy and generalizable results. Feature importance analysis showed trading volume in USD as the dominant driver of predictions, with additional value from simple temporal cues such as hour and day. Deep learning approaches were explored for their ability to capture non-linear and temporal patterns, but they required further stabilization to match the ensembles on this dataset. The work highlights both the promise and the limits of machine learning in a market that trades constantly and moves quickly. Models captured broad trends yet struggled with sharp spikes typical of high volatility periods. The thesis proposes practical next steps, including periodic retraining, integration of sentiment and external signals, and the use of explainable methods to improve transparency. These contributions offer a clear framework for real time trade count forecasting and for building adaptive tools to support decision making in digital asset markets.
Open Access
IT Service Management Challenges During Healthcare Digital Transformation: Evidence from Electronic Medical Record Systems in Sri Lankan Government Hospitals
(Sri Lanka Institute of Information Technology, 2025-01) Weerarathna,K.A.N
This research investigates IT Service Management (ITSM) challenges during healthcare digital transformation through the implementation of Hospital Health Information Management Systems (HHIMS) in NorthWestern Province government hospitals, Sri Lanka. Using the ITIL v4 Service Value System framework, this mixed-methods study examines challenges across three key dimensions: Organizations and People, Information and Technology, and Partners and Suppliers. The study employed sequential explanatory mixed-methods design, collecting quantitative data from 26 IT professionals through structured questionnaires and qualitative insights from 12 healthcare professionals via semi-structured interviews. Statistical analysis revealed significant correlations between ITIL v4 dimensional challenges and digital transformation success, while thematic analysis identified critical implementation barriers including inadequate change management, infrastructure limitations, and multi-stakeholder coordination difficulties. Key findings indicate that Organizations and People dimension challenges (r = -0.68, p < 0.01) had the strongest negative impact on transformation success, followed by Information and Technology challenges (r = -0.61, p < 0.01) and Partners and Suppliers coordination issues (r = -0.59, p < 0.01). Qualitative analysis revealed that staff resistance stemmed from inadequate training (83% of respondents), poor digital literacy support, and system design misalignment with clinical workflows. The research contributes a contextual framework for understanding ITSM challenges in developing country healthcare systems and provides actionable recommendations for improving EMR implementation success. Policy implications include the need for comprehensive management strategies, enhanced technical infrastructure, and improved multi-agency governance structures.
Open Access
Challenges and Opportunities in Mobile Banking Adoption among Young Adults in Sri Lanka
(Sri Lanka Institute of Information Technology, 2025-09) Liyanage S L
This study examines the challenges and opportunities associated with mobile banking adoption among young adults in Sri Lanka. Mobile banking currently provides accessibility, convenience and financial inclusion, yet its adoption remains inconsistent due to issues such as security concerns, lack of trust, digital literacy gaps and infrastructure limitations. While mobile banking provides numerous benefits, such as 24/7 access to financial services, reduced dependency on physical bank branches and increased financial inclusion, significant barriers still need to be addressed. The purpose of this research is to identify barriers, examine user perceptions and propose strategies that can enhance adoption. A structured questionnaire will be administered among young adults in different geographic settings (urban, suburban, rural). To guarantee a thorough understanding, both mobile banking users and non-users will be included. Data collected will be analyzed to highlight trends in adoption, perceptions of security and the role of financial literacy. It is anticipated that the results would help banks, policymakers and tech companies create mobile banking systems in Sri Lanka that are safer, easier to use, and more inclusive. By addressing existing challenges and leveraging opportunities, the research aims to foster a more inclusive and technology-driven financial ecosystem that aligns with global banking trends.
Embargo
Enhancing the value proposition of priority Banking in SriLanaka
(Sri Lanka Institute of Information Technology, 2025-10) NAWARATHNE,I.K.S.S.
Priority banking has become a vital strategic focus for banks and financial institutions aiming to retain and grow affluent, high-net-worth client segments. In Sri Lanka, despite significant investments in branded premium offerings, evidence suggests that the actual value perceived by customers often falls short of expectations. Past studies highlight key issues, including a lack of personalization, insufficient digital integration, reactive relationship management, and limited lifestyle benefits. Customer feedback reinforces this gap, with many clients perceiving “priority” services as symbolic rather than substantive. This research investigates how Sri Lankan banks can enhance the value proposition of their priority banking services by aligning more closely with evolving elite customer expectations. Using a mixed-method approach, the study integrates surveys and interviews with relationship managers and priority clients in certain states and private banks in Sri Lanka, supported by secondary data from reports and academic studies. Findings reveal that while customers value exclusivity and trust, true loyalty is undermined by generic service delivery and limited proactive engagement. To address these gaps, this study proposes the P.E.A.K. Model, a strategic framework emphasizing Personalization (tailored financial and lifestyle solutions), Experience Integration (seamless digital- physical journeys), Anticipation (proactive, predictive engagement), and Knowledge Empowerment (financial literacy and advisory tools). The model underscores the importance of leveraging AI- driven personalization, omnichannel CRM, and well-trained relationship managers to create a more differentiated and meaningful client experience.
Open Access
AI-Driven Help Desk Integration: Enhancing Customer Support with Chatbots, Sentiment Analysis, and SLA Automation
(Sri Lanka Institute of Information Technology, 2025-11) Nimnadi Dilsika
This research investigates the integration of Artificial Intelligence (AI) into help desk systems to improve customer service efficiency, accuracy, and overall satisfaction. The proposed AI-driven help desk framework combines three intelligent components: a chatbot for instant and automated responses, a sentiment analysis engine to detect and interpret customer emotions, and a Service Level Agreement (SLA) management module that ensures real-time tracking of response and resolution performance. Using a dataset of 40,000 simulated support tickets, the system was evaluated for key metrics such as response time, SLA compliance, and customer satisfaction levels. The results demonstrated notable improvements, including faster response rates, higher SLA adherence, and enhanced emotional understanding in customer interactions. Overall, the study confirms that AI integration transforms traditional help desks into proactive, data-driven, and emotionally intelligent service environments. Future advancements will focus on predictive SLA modeling, multilingual capabilities, and multimodal sentiment analysis for broader adaptability.