8 sections from the Description of Action (Part B)
5
Project: 101119635 — DIGITAL — HORIZON-MSCA-DN-2022
LIST OF PARTICIPATING ORGANISATIONS
Legal Non
Consortium Entity Acad -aca
Awards Dept./
Scientist-in-
Role of associated
Member Short emic dem Doctoral Country Division / Charge Partner or link to
Name ic
Degrees Laboratory beneficiary
Beneficiaries
University of
UTW x x NL
High-Tech
Prof. Dr. J.
Twente
Business and
Osterrieder
Entrepreneurship
WU Vienna
WWU x x AT Department of Prof. Dr. R.
University of
Economics Hochreiter
Economics and
Business
University of
UNA x x IT Department of Prof. Dr. M.
Political Sciences Iannario
Naples
Federico II
Kaunas
KUT x x LT
Faculty of
Prof. Dr. A.
Kabasinskas
University of Mathematics and
Technology Natural sciences
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Informatics
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University
Business
Administration
Cardo S.R.L CAR x IT
Artificial Altin
Intelligence Kadareja
Laboratory (CEO)
Poznań POZ x x PL Department of Prof. Barbara
University of Econometrics Będowska-
Economics and Sójka
Business
Associated
Partners
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Research) Training, Research
Swedbank AB SWE x LT
Aidas Covering Northern
Malakauskas Europe, Hosting DCs,
(Head Transferable Skills
Finance) Training, Research
Royalton
ROY x LU
Portfolio
Dr. Michael
Hosting DCs,
Partners Management
Althoff
Transferable Skills
Holdings SA Research
(Board
Training, Research
Member)
6
Project: 101119635 — DIGITAL — HORIZON-MSCA-DN-2022
Bern Business BFH x CH
Applied Data Prof. Dr. Hosting DCs,
School
Science and Joerg Transferable Skills
Finance Osterrieder Training, Research
Athena ARC x GR Information Prof. Ioannis Hosting DCs,
Research Management Emiris Transferable Skills
Center Systems Institute (President and Training, Research
General
Director)
European
EIT x BE
EIT Digital Dr. Tuan Training on Digital
Institute of
Doctoral Training Trinh (Board Finance, Hosting DCs,
Technology
Department Member) Research
Digital
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ECB x DE
Directorate Daniela Covering Europe,
General SSM Schackis Hosting DCs,
Governance & (Deputy DG) Transferable Skills
Operations Training, Research
Bank for BIS x CH
Rafael
Monetary and Hosting DCs,
International
Schmidt
Economic Transferable skills,
Settlements
(Head of
Department Training,
MED IT)
Research
Deutsche Bank DBA x DE LGD and CCF Roman Hosting DCs,
Methodologies Timofeev Transferable skills,
(Head of Training,
LGDCCF Research
Methods)
University of UKL x x DE
Kaiserslautern- Department of Prof. Dr, Ralf Hosting DCs,
Landau Financial Korn Transferable skills,
Mathematics Training,
Research
Data for non-academic beneficiaries
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country)
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Cardo Milan, Italy Research on 111 91 www.cardo 2.191.881€ No Yes
S.R.L AI ai.com
Declarations
Name (institution / individual) Nature of inter-relationship
Jörg Osterrieder Prof. Dr. Osterrieder is Associate Professor at the University of Twente and Professor at Bern
Business School.
1 Defined as the total value of sales of goods and services during the last accounting period.
2 As defined in Commission Recommendation 2003/361/EC.
7
Project: 101119635 — DIGITAL — HORIZON-MSCA-DN-2022
with industry and other relevant non-academic partners are a defining characteristic of the DIGITAL research model
(ECB, BIS, ARC and FRA). Each IRP is established jointly by academic and industry representatives, and each DC
will spend 18 months in industry, in world-class research centres and government agencies. With this design,
we ensure that the progress with respect to the established research objectives is continuously monitored, validated
by industry, and in accordance with the existing and upcoming technological regulations. The continuous feedback
loop with industry ensures that developed solutions are applicable in the real world.
sexual orientation, and all other relevant diversity aspects; supervisors, candidates, and trainers in training schools
will be chosen to comply with sex and gender integration; and Ph.D. research projects will be evaluated, among other
things, based on the degree to which they integrate sex and gender into research, following EU principles.34 35
libraries and tools. Proper documentation, licenses, user guides, examples, and evaluation results will be provided so
that a third party can reproduce findings and become familiar with the various frameworks.
have a significant impact on people’s lives. This will be accomplished by enabling systems that are explicable,
trustworthy, and ethical (WP 1, 3, 4). Legal accountability, transparency, and fairness are considered from the start of
a project. IRPs will begin with ethical considerations, and regular meetings and audits will ensure compliance
throughout. Each AI pipeline implementation will be exhaustively described upon completion. WP 3 is central to the
development of trustworthy AI systems.
The members will
● Promote awareness of sustainability issues that have arisen as a result of the research project, as well as
awareness of sustainability goals and initiatives in general (such as the European Green Deal and the United
Nations Sustainable Development Goals), including through the activities of the project pertaining to
outreach, communication, and dissemination
● Encourage people to lessen the environmental effect of their research and activities connected to research by
spreading ideas and providing examples of best practices for enhancing the sustainability of research projects.
This may be done via social media and other online platforms.
In case of success, the researchers to be recruited by the Swiss university will be fully financed by the Swiss State
Secretariat for Education, Research and Innovation (SERI). The SERI will apply the same rules as the European
Commission, based on the MSCA Work Programme 2021-2022, incl. recruiting, mobility and funding rules. The
present project proposal deals with the issue of Digital Finance. This means that it combines access to data and data
issues with AI aspects. Consequently, the main ethical dimensions that are found in this proposal are related to personal
data and the use of AI. For a successful implementation of the action in order to address the project's objectives, data
needs to be manipulated and analysed. There is the need for data from financial actors like banks, regulators, or other
financial companies. All this data will be processed using two main types of methods: statistical/ econometrics and AI.
Ethical issues related to personal data that can be attached to our objectives are given by the collection of data,
organization and storage, adaptation/ alteration, retrieval and consultation, use, and transferability/ sharing. We will
use both available data related to individuals and financial actors, and data that will be collected through surveys or
interviews. All members of the projects will consult databases with personal data. For survey reasons, mailing lists will
have to be constructed. Additionally, in order to increase the impact of our results we will ask partners and respondents
if they would like to provide their e-mail addresses or other types of personal contacts to be kept up-todate about the
results of our research activities. The topic addressed by the present project proposal does not lead to any harm in the
health or the physical safety of the participants. It may, however, hinder their safety, from the perspective of their
personal data being employed in the research.
The second major ethical dimension that we emphasize for our project is the use of AI. Digital Finance is characterized
nowadays by a substantial amount of data (Big Data). Econometrics tools have to be combined with the use of AI
methods, in order to obtain the most accurate results. AI techniques will be both used and developed to ensure the
objectives' fulfillment. But, just as expressed by the European Commission, there are different ethical aspects that have
to be taken into account. One very important is related to the trustworthiness and robustness of AI. AI models/systems
can generate confusion or affect human autonomy. Additionally, both human and other artificial actors can interact in
an adversarial manner with the developed AI system. Our goal is to fill in the research gap existing in the field of
Digital Finance and Explainable AI. For this, we will also provide strong interdisciplinary training for future European
financial and data researchers in Europe, in order to boost capabilities and create a qualified workforce. Consequently,
ethical dimensions are also to be found in the training programmes.
Another important aspect is that some of the participants in the project proposal come from non-EU countries -
Switzerland. Consequently, additional ethical issues may arise, depending on the national legislation of the beneficiary.
This will all be treated according to the EU ethical guidelines.
To address the ethical issues mentioned in the Ethics Self-Assessment part, we will first adhere to the highest ethical
standards provided by both national and European regulations in the field. In each particular case (non-EU countries
participants included) the strictest ethical regulation will be applied and all participants will have to implement it.
In respect to the AI ethical issues that we emphasized in the Ethics Self-Assessment, the first step is to use the ALTAI
checklist, as stated before. To counteract the adversarial usage of AI, all applications developed within the project will
be safely kept and used according to international laws. Additionally, we will take care that AI tools that we use or
develop preserve the human decision-making autonomy and that they are only a means to achieve better results such
as to contribute to the fulfillment of the project's objectives, on one hand, and to an increase in the standard of living
of individuals, by increasing financial innovation and financial access. We will involve an advisory board made up of
specialists in the field. For example, in the COST Action CA 19130 that we are involved in, we have Maria Maloney,
from University College Dublin that is a specialist in GDPR, in general and GDPR related to AI, in particular. Another
important issue is related to the robustness of the AI tools and applications developed. To mitigate this risk, all tools
and applications will be tested several times and in comparison to other types of approaches, like, for example,
Econometrics. All activities related to the use of AI will comply with the ALTAI checklist and the 7 major requirements
in this list. Network Organization.
The consortium is confirming that compliance with ethical principles and applicable international, EU and national
law in the implementation of research activities not originally envisaged (or not described in detail) in the DoA will be
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Project: 101119635 — DIGITAL — HORIZON-MSCA-DN-2022
ensured. Any ethical concerns raised by those activities will be handled following rigorously the recommendations
provided in the European Commission Ethics Self-Assessment Guidelines.
The consortium is confirming that an ethics advisor will be appointed and that two ethics reports will be delivered at each
reporting period.
The consortium is confirming that in case of an Ethics Check, relevant documents, authorisations, approvals will be
obtained, kept on file and sent to the REA upon request.
43