Methods for Fintech and Artificial Intelligence in Finance

Blended Intensive Programme (BIP), September 4-10, 2024 – Naples

Information

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.

Participants

TBA

Disciplinary Area

For participation in the course, it is preferable to have a previous study background in quantitative studies (mathematics, statistics, economics, data science, computer science). However, it is not compulsory.

Learning and Teaching Methods

The learning method is divided into virtual and face-to-face sessions, focused on case studies of real data management. The learning methodology will combine lectures of the methodologies to practical workshops aimed at implementing the techniques presented on the case studies.

  • Number of ECTS credits awarded: 3 CFU
  • Main language of teaching/training: English level B2, as described in the ‘European Language Portfolio’ section of the Council of Europe

Registration

Participants are waived of the fee course.

​Coffee, snacks, and light lunch will be provided by the host institution while for dinner a couple of partner restaurants will be indicated.

Program

The course consists of one week in presence (4 September – 10 September 2024) organised as described below

September 2 – online

  • Evening. Seminar: Statistical learning for Fintech and Financial Inclusion
    General introduction to the course with the participation of all the representatives of the partner Institutes/Universities

September 3 – online

  • Evening. Seminar: Data integration, pre-processing and data fusion in R

September 4 – in presence

  • Evening. Seminar: Digitalization and Financial Awareness
    Directorate General for Consumer Protection and Financial Education
    Financial Education Directorate Young People, Analysis and Surveys Division (Head of Division) Banca d’Italia

September 5 – in presence

  • Morning. Methods for dimension reduction and clustering in Fintech surveys
    Main topics: Clustering mixed type nominal/ordinal/interval data, Joint dimension reduction and clustering
  • Evening. Laboratory lectures – supervised tutorial, individual and teamwork

September 6 – in presence

  • Morning. Generalized Linear Models for rating data
    Main topic: Basic principles of categorical data, Binary data models, Polytomous data models
  • Morning. Panel data for assessing Fintech, financial inclusion and income per capita
    Main topic: Multivariate Regression analysis, Multilevel models
  • Evening. Laboratory lectures – supervised tutorial, individual and teamwork

September 7 – in presence

  • TBA. Laboratory lectures – supervised tutorial, individual and teamwork
  • Social activities

September 8 – in presence

  • TBA. Laboratory lectures – supervised tutorial, individual and teamwork
  • Social activities

September 9 – in presence

  • Morning. Latent variable models for Financial knowledge
    Main topics: Latent variables, Classical Test Theory, Item Response Theory, IRT models for polytomous items, Hierarchically Structured Modelling
  • Evening. Laboratory lectures – supervised tutorial, individual and teamwork

September 10 – in presence

  • Morning. Hybrid approach for the analysis of complex data structures
    Main topic: Hybrid methods; Implementations of dimension reduction for continuous, polytomous e mixed data, complex categorical structures
  • Evening. Wrap-up – summary, feedback, alternative methods

October 21 – online

  • Evening. Presentation of the results of an analysis project by participants (final meeting) and seminar by a keynote speaker on BIP topics

During the final meeting Rita Cappariello, Bank of Italy will hold a seminar titled Sustainable Finance: insights and data for an assessment.

This will be followed by a panel discussion attended by members of the scientific committee and the concluding papers of the participants in the Blended Intensive Programme Advanced Analytics for Data Science.

 

Mentors

  • Rosa Fabbricatore
  • Carla Galluccio
  • Valeria Policastro
  • Roberto Rondinelli

 

Program Committee

  • MARIA IANNARIO, University of Naples Federico II (proponent and coordinator)
  • JORG OSTERRIEDER, University of Twente, Netherlands (Sending institution)
  • RONALD HOCHREITER, WU Vienna University, Austria (Sending institution)
  • CODRUTA MARE, Babes-Bolyai University in Cluj-Napoca, Romania (Sending institution)
  • MARTIN ALEXY, University of Economics, Bratislava (Sending institution)
  • IOANNIS NTZOUFRAS, Athens University of Economics and Busines, Greece (Sending institution)
  • ANDREAS GROLL, Technische Universität Dortmund

Local Scientific Committee

  • MARIA IANNARIO, University of Naples Federico II
  • ALFONSO IODICE D’ENZA, University of Naples Federico II
  • LUCIO PALAZZO, University of Naples Federico II
  • FRANCESCO PALUMBO, University of Naples Federico II
  • GIANCARLO RAGOZINI, University of Naples Federico II
  • DOMENICO VISTOCCO, University of Naples Federico II

Conference Secretariat

  • MARIA GIOVANNA PORZIO, University of Naples Federico II

Mail: maria.iannario@unina.it

Social Events

TBA

TBA

 

Venue

Department of Political Science, University of Naples Federico II

Via Leopoldo Rodinò, 22 – Naples, Italy
http://www.scienzepolitiche.unina.it

  • Statistics Laboratory (Aula G4)

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Accomodation

Participants can enjoy low-cost accommodation at the hostel. Some suggested hostels: