Senior Scientific Advisory Board

Wolfgang Karl Haerdle attained his Dr. rer. nat. in Mathematics at Universitaet Heidelberg in 1982 and in 1988 his habilitation at Universitaet Bonn. He is Ladislaus von Bortkiewicz Professor of Statistics at Humboldt-Universitaet zu Berlin and the director of the Sino German Graduate School IRTG1792 on "High dimensional non stationary time series analysis". He also serves as head of the joint BRC Blockchain Research Center (with U Zuerich & U Bukarest). He is guest professor at WISE, Xiamen U, SMU Singapore, NYCU Hsinchu TW, and Charles U Prague. His research focuses on data sciences, dimension reduction and quantitative finance. He has published over 30 books and more than 300 papers in top statistical, econometrics and finance journals. He has professional experience in financial engineering, smart data analytics, machine learning and cryptocurrency markets. He has created a financial risk meter (FRM), a cryptocurrency index (CRIX), and invented the Q2 eco system (quantlet.com & quantinar.com).

"Rigorous statistics turns AI from an impressive demo into an auditable tool. A compliance Copilot has to show its work, and this project is built to do exactly that."

Codruta Mare is Professor of Statistics and Econometrics at the Department of Statistics, Forecasts, Mathematics and PhD coordinator in the field of Cybernetics and Statistics, Faculty of Economics and Business Administration, and the Scientific Director of the Interdisciplinary Centre for Data Science, Babes-Bolyai University, Cluj-Napoca, Romania. She teaches courses in Statistics, Econometrics, Economic Forecasting and Spatial Econometrics among others. Besides her solid theoretical and methodological background, she has important expertise gained in research projects and consultancy activities for public institutions (The World Bank, European Commission, Romanian Ministry of Structural Funds, Cluj-Napoca City Hall, etc.) and private companies, both SMEs and multinational corporations. She has also delivered trainings in data analysis and visualization internationally, including for clients in the United Arab Emirates (Dubai Municipality and Government of Abu Dhabi) and Saudi Arabia (King Faisal Specialist Hospital & Research Centre). She is currently the Grant Award Coordinator of the COST Action CA19130 "FinAI – Fintech and Artificial Intelligence in Finance" and country lead and Work Package 1 coordinator in the Marie Sklodowska-Curie Industrial Doctoral Network on Digital Finance (DIGITAL).

"Compliance teams do not need more data, they need models that survive the move from research into regulated practice. That is what this project sets out to deliver."

Prof. Dr. Daniel Traian Pele graduated in Mathematics (2000) and earned his Master in Stochastic Processes and Theoretical Statistics at the University of Bucharest (2002). He received his Ph.D. in Statistics (2007) and habilitation in Statistics (2019) at the Bucharest University of Economic Studies. He currently serves as a Professor at the Department of Statistics and Econometrics, the Bucharest University of Economic Studies, Romania, teaching Statistics of Financial Markets and Time Series. His research profile is that of a data scientist, focused on statistical modelling of financial markets and digital assets.

"Onboarding and compliance in Swiss finance is a statistical-modelling problem wearing a paperwork costume. I am glad to support a project that treats it that way."

Associate Professor in Statistics at UNINA. The main results of her work consist of the study and development of a class of statistical models used for the analysis of ordinal data. Specifically, she proved the identifiability of this class of models and extended the models for adapting them to non-standard situations as in multilevel/hierarchical contexts and when overdispersion or shelter effects are present. She has been visiting Fellow at Lancaster, Geneve, and Iowa Universities, London School of Economics, Athens University of Economics and Business, and Technische Universitaet Dortmund. She has been awarded grants with an international profile including a DAAD scholarship, Fulbright scholar, and the Virtual Mobility Grant of COST Action FinAI (CA19130). She is Principal Investigator of the Erasmus+ KA131 Blended Intensive Programme Advanced Analytics for Data Science (2022) and Methods for Fintech and Artificial Intelligence in Finance (2023). In 2023 she received an International Advanced Fellowship from Babes-Bolyai University (SMART: Statistical Modelling & Data Analytics for FinTech). She is Associate Editor of the Journal of the Royal Statistical Society Series C, Metrika, and Statistical Modelling. She has authored over 100 papers in statistical modeling, with recent research interests extending to analytics in health, fintech, financial inclusion, and inequality.

"Turning compliance from a box-ticking exercise into an evidence-based workflow is a worthwhile research goal — and a necessary one for the next generation of digital finance."

Hanna Kristín Skaftadóttir is an Associate Professor at Bifröst University and Program Leader of Business Intelligence. She holds a PhD in AI and Automation in Business from the University of Iceland. Her research focuses on artificial intelligence, automation, business intelligence, digital finance, and the organizational adoption of emerging technologies, with particular emphasis on explainable AI, governance, and interpretable analytics in regulated settings.

Alongside her academic work, she is CEO of Sanitica AI and has professional experience in finance, auditing, innovation, and technology implementation. Her background includes Deloitte, KPMG, and Íslandsbanki, as well as applied work on AI adoption, process automation, and responsible data handling in organizational environments. She has published on AI in accounting and finance, business intelligence, and the organizational conditions that shape successful and trustworthy use of advanced systems.

"A useful compliance Copilot must do more than extract data. It must support human judgment with reliable, verifiable, document-grounded outputs."

Monica Violeta Achim is a professor and doctoral supervisor in the field of Finance at the Faculty of Economic Sciences and Business Administration, Babes-Bolyai University, Cluj-Napoca. With over 26 years of experience in academia, she has published as author and co-author, over 140 scientific articles and 25 books. In 2020 and 2026 she obtained the Award for Excellence in Scientific Research at Babes-Bolyai University, Faculty of Economics and Business Administration, Cluj-Napoca, Romania, as a recognition of the results obtained in the research activity. She led a major project in Financial Crime of about 250,000 Euro that was financed by the Romanian Minister of Education, 2020-2023. Recently, according to international platforms like ScholarGPS, she was ranked in the top 2% world scientists (2024-2025) and top 1% world scientists (2024-2025) in the area of financial crime. She is also a member of the Association of Certified Financial Crime Specialists (ACFCS) and provides trainings in the area of compliance and Anti Money Laundering for financial and bank institutions.

"Anti-money-laundering and financial-crime prevention begin with the quality of the data captured at onboarding. A compliance Copilot that improves that first step is a meaningful contribution."

Claudia Tarantola is a Full Professor of Statistics at the University of Milan's Department of Economics, Management, and Quantitative Methods. She holds a degree in Political Economy from Bocconi University and a Ph.D. in Methodological Statistics from the University of Trento, with research experience at the University of Bristol and a postdoc at the Athens University of Economics and Business. She has led and participated in various research initiatives, including a project on risk management in energy markets funded by ENEL S.P.A. Her research focuses on Bayesian methods, copula modeling, categorical data analysis, data science, and financial risk models, with publications in leading journals like Bayesian Analysis, Quantitative Finance, and Journal of the Royal Statistical Society: Series B.

"Bayesian and statistical-risk methods have matured far beyond the research lab. Applying them to the day-to-day work of Swiss compliance officers is where they earn their keep."

Alessandra Tanda is an Associate Professor of Banking and Finance in the Department of Economics at the University of Insubria. She has extensive teaching experience in the field of financial intermediation and markets, in undergraduate, master's and postgraduate courses. Her main research interests include FinTech and DeFi, the financial structure of financial and non-financial firms, the ESG and sustainability profile of financial markets, with particular reference to climate risk, and the governance of financial intermediaries. She has published widely and has participated in numerous national (PRIN and PRIN PNRR) and international projects, including FINTECH HO2020, PERISCOPE and the Cost Fin-AI network, all funded by the European Union.

"Obtaining the correct information for client onboarding is of the utmost importance when it comes to identifying customers and preventing money laundering activities. While using innovative tools to speed up the process is welcome, this must be done properly to ensure compliance and sustainable efficiency gains."

Stephen Chan is an Associate Professor of Mathematics at the American University of Sharjah. He was awarded the EPSRC Doctoral Prize Fellowship in 2016 at the University of Manchester, UK. His research focuses on extreme value analysis and distribution theory for financial commodities and blockchain data. He co-developed the R package 'VaRES' for computing value at risk and expected shortfall and co-authored two books: Extreme Events in Finance: A Handbook of Extreme Value Theory and its Applications and Artificial Intelligence and Beyond for Finance. Stephen's work extends beyond academic publications, emphasizing technology transfer and commercialization. His projects include a Real-time Risk Rating System for Digital Assets. These innovations have been showcased at events such as the 2024 AUS Innovation Expo and the 2023 Inaugural Hong Kong Laureate Forum at Hong Kong Science Park. He is also a member of the Society of Actuaries (SOA) Research Institute, where he served on the project oversight group for "Decentralized Finance for Actuaries" and co-published three industry research reports on decentralized finance for actuaries.

"Risk and compliance in a digital-assets era cannot be solved with spreadsheets. Bringing modern statistics and AI to the Swiss compliance stack is long overdue."

Roman Matkovskyy is Associate Professor in Finance and Accounting at Rennes School of Business, France. His research focuses on cryptocurrency markets, systemic risk in digital assets, investor behaviour during market stress events, and the pricing of Bitcoin and Ethereum. His work includes empirical studies on the FTX collapse, COVID-19 impacts on financial markets, herding behaviour in cryptocurrency trading, and Bitcoin options pricing, published in outlets such as Finance Research Letters, Economics Letters, Applied Economics, and the Journal of International Financial Markets, Institutions and Money.

Yuanyuan Zhang is Assistant Professor in the Department of Mathematics and Statistics, College of Arts and Sciences, at the American University of Sharjah. She earned her PhD in Mathematical Sciences from the University of Manchester in 2020 with a thesis titled “Statistical Methods and Distribution Theory with Applications to Finance and Cryptocurrencies.” Her research covers cryptocurrency economics and econometrics, decentralised finance, cryptocurrency-market efficiency, volatility modelling, non-fungible tokens, and Bitcoin and stock-index pricing.