Search
Generic filters
Menu

FinTech

Background

The combination of finance and technology is the cornerstone of economic activity. As a sector FinTech has a huge disruptive power for any business, not only the conventional Finance sector and the verticals within it, such as PayTech.

Enterprises are constantly seeking ways to innovate faster, deliver at scale and with high impact.

This research cluster aims to bring together key stakeholders that have an interest in Fintech or seeing an opportunity in Fintech innovation providing a unique opportunity to innovate and disrupt current business practices and ecosystems, and to improve customer experiences

Research Focus

Innovative Payment Paths:
We investigate how digital technologies can assist to change and improve all aspects of payments towards a seamless customer experience. This includes the evaluation of technologies and possibilities of mobile payment solutions to optimize the checkout process.

Technologies to evaluate may include existing contactless payment functions (NFC), new technologies (instant payments, blockchain, chatbot, wearables, etc.) and also various Fintech solutions in the context of European directives. Satisfaction of customers and merchants with existing technologies will also be evaluated and possible improvements for these technologies should be presented.

Data Governance and Consent Management:
With this research we investigate aspects and practices on Data Governance, including privacy and consent management as well as automation of data governance practices and information quality aspects.

View All FinTech Projects

Trust and Quality
Information Quality and the trust in financial information and decisions is an ongoing challenge and subject to debate. A diversity of explanation methods for AI predictions has been developed in the literature being able to understand the predictions made by those models.

Researchers have been developing a wide range of XAI that allow explanations or human-AI interfaces with natural language processing capabilities for different stakeholders.

However, trust into those AI techniques is still an issue, especially from experience domain experts, who are knowledgeable about their domain.

With this research we aim to investigate the elements of trustworthiness in Financial information, and how a deep understanding is enabled through explanations provided by explainable artificial intelligence (XAI) techniques.

Researchers:

Digital Construction Cluster Lead

Dr Zohreh Pourzolfaghar
Director

Professor Markus Helfert

Digital Construction Cluster Lead

Dr Zohreh Pourzolfaghar

Zohreh Pourzolfaghar is Assistant Professor for the School of Business in Maynooth University. She is a members of Lero, the Science Foundation Ireland Research Centre for Software. Zohreh formerly has been Research Fellow at Innovation Value Institute (IVI), Maynooth University’s digital transformation research centre. She is a senior research member of the Business Informatics Group. She is the theme lead in a project investigating the application of Enterprise Architecture in Smart Cities, funded by Science Foundation Ireland (SFI). She has been Principle Investigator for an Industry Fellowship Programme, funded by SFI. Zohreh presented her work at international conferences and has published research in Journals and Conference Proceedings. Zohreh is also leading research within the Cost Action CA16222 (WISE-ACT), a European-wide network.  She has been thematic lead in a successful European Marie Curie PERFORM project. She is a member of the supervisory board of the EU project PERFORM, that focuses on Digital Retail. She has been awarded the SFI industry fellowship (2018) working with industry on topics related to Smart Cities and Building Information Management. She is the Co-PI for submitted H202 Techland proposal. Zohreh received her Ph.D. in Project Management in design process of building projects. Zohreh has years of experience working with project-oriented construction companies to improve organisatioanal productivity and their work processes.

Director

Professor Markus Helfert

Markus Helfert is the Director of IVI and Professor of Digital Service Innovation at Maynooth University. He is also Director of the Business Informatics Group at Maynooth University. He is a Principle Investigator at Lero – The Irish Software Research Centre and at the Adapt Research Centre. His research is centred on Digital Service Innovation, Smart Cities and IoT based Smart Environments and includes research areas such as Service Innovation, Intelligent Transportation Systems, Smart Services, Building Information Management, FinTech, Data Value, Enterprise Architecture, Technology Adoption, Analytics, Business Process Managem ent. Prof. Helfert is an expert in Data Governance Standards and is involved in European Standardisation initiatives. Markus Helfert has authored more than 200+ academic articles, journal and book contributions and has presented his work at international conferences. Helfert has received national and international grants from agencies such as European Union (FP7; H2020), Science Foundation Ireland and Enterprise Ireland, was project coordinator on EU projects, and is the Project coordinator of the H2020 Projects: PERFORM on Digital Retail.

Email:Markus.Helfert@mu.ie

List of Publications:

Scientific Publications
  • Gabriel Hogan, Markus Helfert: Transparent Cloud Privacy: Data Provenance Expression in Blockchain. CLOSER 2019: 430-436
  • Douglas Cirqueira, Dietmar Nedbal, Markus Helfert, Marija Bezbradica: Scenario-Based Requirements Elicitation for User-Centric Explainable AI – A Case in Fraud Detection. CD-MAKE 2020: 321-341

FinTech Projects

Enterprise Architecture and Formal Modelling (EAFM)

Enterprise Architecture and Formal Modelling (EAFM)

Identifying Key Stakeholders as Part of Requirements Elicitation in Software Ecosystems (SECOs)

Identifying Key Stakeholders as Part of Requirements Elicitation in Software Ecosystems (SECOs)

A Method and Process Model for Consent Withdrawal Management

A Method and Process Model for Consent Withdrawal Management