Marcos Machado is an Assistant Professor in Business and Information Systems at the Industrial Engineering and Business Information Systems (IEBIS) department section of the University of Twente. His current research interests are focused on the applications of machine learning algorithms, data science, and analytics to solve business problems.

 

He received his Ph.D. in Modelling and Computational Science from the Ontario Tech University (Canada), and he holds an MSc in Industrial Engineering from the University of Sao Paulo (Brazil) and a BSc in Mathematics from the Federal Institute of Education, Science, and Technology of Ceara (Brazil). He also has over seven years of experience working in the Brazilian and Canadian banking industries. 

Expertise

  • Economics, Econometrics and Finance

    • Specific Industry
    • Finance
    • Machine Learning
    • Credit
    • Logit Model
  • Computer Science

    • Machine Learning Algorithm
    • Models
    • Warning System

Organisations

Publications

2025

Financing circularity strategies in critical raw materials supply chains: Toward a novel blended framework (2025)Resources Policy, 112. Article 105811 (E-pub ahead of print/First online). Xie, K., Machado, M. R., Spierdijk, L. & Yazan, D. M.https://doi.org/10.1016/j.resourpol.2025.105811Advancing credit risk assessment in the retail banking industry: A hybrid approach using time series and supervised learning models (2025)Data & knowledge engineering, 160. Article 102490. Goldmann, S. H., Machado, M. R. & Osterrieder, J. R.https://doi.org/10.1016/j.datak.2025.102490An analytical approach to credit risk assessment using machine learning models (2025)Decision Analytics Journal, 16. Article 100605. Machado, M. R., Chen, D. T. & Osterrieder, J. R.https://doi.org/10.1016/j.dajour.2025.100605Forecasting customers' risk-adjusted revenue: An explainable machine learning approach for the telecommunication industry (2025)Data-Driven Modelling, 1, 13-65 (E-pub ahead of print/First online). Firmansyah, E. B., Rebelo Moreira, J. L. & Machado, M. R.https://doi.org/10.1142/S3029101125500036Advanced analytics to improve energy efficiency of steel industry - A systematic review on ladle logistics (2025)Cleaner Engineering and Technology, 25. Article 100907. Keshetti, A. R., Ruela, V. S. P., Chen, H. & Machado, M. R.https://doi.org/10.1016/j.clet.2025.100907How can consumers without credit history benefit from the use of information processing and machine learning tools by financial institutions? (2025)Information processing & management, 62(2). Article 103972. van Braak, B., Osterrieder, J. R. & Machado, M. R.https://doi.org/10.1016/j.ipm.2024.103972Modeling commodity price co-movement: building on traditional time series models and exploring applications of machine learning algorithms (2025)Decisions in economics and finance. Article 109283 (E-pub ahead of print/First online). Kozian, L. L., Machado, M. R. & Osterrieder, J. R.https://doi.org/10.1007/s10203-025-00512-1Predicting retail customers' distress in the finance industry: An early warning system approach (2025)Journal of Retailing and Consumer Services, 82. Article 104101. Beltman, J., Machado, M. R. & Osterrieder, J. R.https://doi.org/10.1016/j.jretconser.2024.104101

Research profiles

Teaching (Teacher/Tutor):

  • [Q3] B-IEM/B-BIT (Module 3): Business Process Management (BPM)
  • [Q2/Q4] B-BIT/B-TCS (Module 12): Track Coordination (Information Management)
  • [Q1] Minor (Module 9): Enterprise Soft. for the Integration of Adm. Processes (ESIAP)
  • [Q4] M-BIT/M-IEM/M-BA: Applications of AI in Business (AAIB)

Supervision of BSc thesis projects (1st or 2nd Supervision):

Supervision of MSc thesis projects (1st or 2nd Supervision):

Internship supervision:

  • (Finished) Alessandra Amato
  • (Finished) Nabila Pindya
  • (Finished) Oleg Silcenco
  • (Finished) Sophie Gaastra
  • (Finished) Akhil Raja Keshetti
  • (Finished) Miguel de la Cruz
  • (Finished) Haritha Mutharasu
  • (Finished) Bas Vreeman
  • (Finished) Emma Cañavate
  • (Finished) Tri Imam
  • (Finished) Syifa Silfiyana Selly
  • (Ongoing) Dani Mahaini
  • (Ongoing) Virginia Putri

Committee Service:

Affiliated study programs

Courses academic year 2025/2026

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2024/2025

My research endeavors revolve around the application of analytics, econometrics, applied statistics, and mathematical principles, leveraging data-driven methodologies and machine learning algorithms to address various business challenges. Currently, I am engaged in five significant research initiatives, supported by funding from esteemed entities such as the European Union (IS2H4C, MSCA - DIGITAL), the Dutch Government (Kick-Start AI), and the University of Twente (CEP Twente). Further information regarding these projects is outlined below.

Current projects

Kickstart AI: Artificial Intelligence (AI) in Finance

ING Group - University of Twente (UT)

Joint cooperation of ING Group (ING) and University of Twente (UT), advancing Artificial Intelligence (AI) in Finance

Sustainable Circular Economy Transition: from Industrial Symbiosis to Hubs for Circularity (IS2H4C)

I am a contributor to IS2H4C – a four‑year, €23.5 million flagship Horizon Europe collaboration that will turn industrial zones into “Hubs 4 Circularity” (H4C) and help Europe reach near‑zero‑emission targets under the Green Deal and Fit‑for‑55. Led by Dr Devrim Yazan (IEBIS, University of Twente) and delivered by 35 partners in nine countries, IS2H4C is the largest EU‑funded project ever run at UT.

My specific contributions

  • Grant design & proposal writing – co‑authored the successful application with a focus on Work Package 5 (Financial and Business Models).
  • AI‑driven finance & business solutions – work closely with the WP5 lead and all four demonstration hubs to explore and pilot AI applications for investment, risk, and operations in circular‑economy ecosystems.
  • Doctoral supervision – supervise a PhD researcher investigating the “risk and value of circularity” to quantify economic upside and de‑risking mechanisms for H4C stakeholders.

Circular Economy Platform Twente (CEP Twente)

Member of the CEP Twente, a project coordinated by Dr. Devrim Yazan (IEBIS/Utwente). This project aims to establish the Circular Economy Platform Twente (CEP Twente) as a collaborative initiative between the academicians and students of the five faculties of the University of Twente (UT) including Green Hub Twente within 2023. The primary goal of the CEP Twente is to accelerate the transition towards a sustainable circular economy by fostering interdisciplinary research, education, and knowledge exchange. Starting in 2024, we aim to act as a regional platform that provides room for collaboration among regional stakeholders, including municipalities, companies, and NGOs. The platform will serve as an umbrella association, bringing together diverse stakeholders from academia, industry, and (local) government to build a community that shares a common vision and creates societal, environmental, and economic impact in the Twente region.

Marie Sklodowska-Curie Action Industrial Doctoral Network on Digital Finance (MSCA Digital Finance)

Marie Sklodowska-Curie Action Industrial Doctoral Network on Digital Finance (MSCA Digital Finance)

I am a contributor to DIGITAL, the Marie SkƂodowska‑Curie Industrial Doctoral Network on Digital Finance (MSCA Digital Finance), a €3.7 million EU‑funded initiative coordinated by Dr Joerg Osterrieder (IEBIS, University of Twente). The network delivers cutting‑edge research and training that bridges academia and industry, nurturing the next generation of digital‑finance experts across Europe’s innovation ecosystem.

My specific contributions

  • Grant conception & consortium building – co‑authored the successful Horizon Europe proposal and supported the Principal Investigator in assembling the multi‑country research network.
  • Work Package 8 lead (Project Management, 09/2023‑01/2025) – steered day‑to‑day governance, reporting, risk and quality management from project launch through the end of Year 1.
  • Work Package 5 co‑lead (Sustainable Finance) – coordinate research strands on green and responsible‑finance applications within the consortium.
  • Doctoral supervision – co‑supervise an MSCA PhD fellow investigating real‑world green‑finance use‑cases in partnership with Swedbank, the Fraunhofer Institute and other leading private‑sector stakeholders.

BuddyGPT

BuddyGPT for UT students: Integrating ChatGPT technology with Canvas Learning Management System for enriched, engaging and enjoyable learning experiences (Project Leader and PI: Dr. Gayane Sedrakyan).

Finished projects

COST Action - Fintech and AI in Finance

COST Action - Fintech and AI in Finance

Member of the COST Action: Fintech and AI in Finance. Project is coordinated by Dr. Joerg Osterrieder (IEBIS/Utwente). The Action will investigate AI and Fintech from three different angles: Transparency in FinTech, Transparent versus Black Box Decision-Support Models in the Financial Industry and Transparency into Investment Product Performance for Clients. The Action will bridge the gap between academia, industry, the public and governmental organisations by working in an interdisciplinary way across Europe and focusing on innovation.

Erasmus: Blended Intensive Program (BIP) - Methods for Fintech and Artificial Intelligence in Finance

The aim of the BIP is to create an interdisciplinary course on advanced topics in the field of statistics and probability, with applications in the Fintech sector and Artificial Intelligence on key topics included in the UN SDGs.

The programme will enable participants to understand and develop analyses on financial instruments using appropriate techniques. Starting from the theoretical analysis of the technical-conceptual determinants and the regulatory environment of AI, models will be presented and the results of field tests of the experience gained in the adoption of models of the kind will be presented.

The programme aims to provide analytical skills to create, manage and interrogate large datasets applicable to the financial sector and to build critical awareness of current issues in the Fintech landscape. A set of programming tools will facilitate the implementation of models and enable participants to analyse decision-making processes.

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University of Twente

Ravelijn (building no. 10), room 3105
Hallenweg 17
7522 NH Enschede
Netherlands

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