Silvia Figini

Ruolo: Professore Ordinario
Email: silvia.figini@unipv.it
Telefono: +39 0382 984661

 

 

Insegnamenti


Metodi quantitativi per l'analisi economica
Statistica
Statistica economica

Ricevimento studenti


Appuntamento via mail

Prossimi appelli


Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Martedi 15/01/2019 10:00 Aula: E
Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Giovedi 31/01/2019 15:00 Aula: E
Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Martedi 19/02/2019 10:00 Aula: E
Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Martedi 23/04/2019 10:00 Aula: E

Biografia


Dal 2018 Professore Ordinario di Statistica Economica - Università degli Studi di Pavia – Dipartimento di Scienze Politiche Sociali (Abilitazione Scientifica Nazionale 2013).

Vice Coordinatore PhD Internazionale in “Computational Mathematics and Decision Sciences”, Università di Pavia e Università della Svizzera Italiana.

Direttore Scientifico del “Bio-Data Science Research Center”, Istituto Neurologico Nazionale IRCCS Mondino.

Direttore Scientifico del “Centro di Ricerca RIDS” (Res Institute for Data Science), Università di Pavia.

2014-2018 Professore Associato di Statistica - Università degli Studi di Pavia – Dipartimento di Scienze Politiche Sociali (Abilitazione Scientifica Nazionale 2012).

2010-2014 Ricercatore di Statistica - Università degli Studi di Pavia – Dipartimento di Scienze Politiche Sociali

Formazione
Phd in Statistica presso l’Università L. Bocconi di Milano.
Laurea in Economia (indirizzo quantitativo) presso l'Università di Pavia

Periodi di studio e ricerca presso:
University of Cambridge, Department of Pure Mathematics and Mathematical Statistics; University of Umea, Department of Statistics and Business School of Economics; University of Aalto, Department of Statistics and Computer Science; Dublin City University, Department of Statistics; University of Edimburgh, Credit Research Centre; Universitité Paris 1 Panthéon-Sorbonne, Maison des Sciences Economiques.


Curriculum accademico


Interventi presso sedi istituzionali

(2017) “Data science models to predict terrorist events”, presso la Presidenza del Consiglio dei Ministri

(2015) “Reti sociali e antiriciclaggio: Metodologia ed evidenze empiriche su dati bancari”, presso Unità di Informazione Finanziaria – Banca d’Italia (Workshop “Metodi quantitativi e contrasto alla criminalità economica”).

(2015) “Data science and social network analysis for anti money laundering”, presso il Ministero dell’Economia e delle Finanze.


Partecipazione a Progetti di Ricerca Europei

SYRTO 2013-2016: “SYstemic Risk TOmography” – Partner coinvolti: Università di Brescia, Centre National De La Recherche Scientifique (CNRS) – Centre d'Economie de la Sorbonne – Axe Finance (CES-Finance) ; MIT Massachusetts Institute of Technology Department of Operation Research Boston College; Athens University of Economics and Business – Research Center (AUEB-RC); VU University Amsterdam; Banca Centrale Europea; Universita? Ca? Foscari di Venezia.

MUSING 2006-2010: “Multy Industry semantic based next generation business intelligence”.

Partecipazione a Progetti di Ricerca Nazionali

PRIN (2013-2015) Multivariate statistical models for risk assessment
PRIN (2007-2008) Modelli statistici multivariati per la valutazione dei servizi di pubblica utilità
PRIN (2007) Progetto CHICOS
PRIN (2005-2006) Metodologie di Data mining per le applicazioni di e-business
FIRB (2006-2009) Metodologie di data mining per le piccole e medie imprese

Didattica
Docente titolare degli insegnamenti di Statistica, Statistica Economica, Metodi Quantitativi per l'Analisi Economica.

Attività di referaggio per le seguenti riviste:
Annals of Applied Statistics, Computational Statistics and data analysis, European Journal of Operational Research, Applied Stochastic Models in Business and Industry, Methodology and Computing in Applied Probability, Journal of Quality Technology and Quantitative Management, Statistical Methods and its applications, Management Science, Journal of the American Statistical Society, Journal Royal Statistical Society (series A e C),Statistical methods and applications, Journal of the Operational Research Society, Advances in Data Analysis and Classification.

Incarichi Istituzionali
Dal 2017 membro Commissione Ricerca Dipartimento Scienze Politiche e Sociali.
Dal 2017 membro Commissione Ricerca Dipartimento Scienze Politiche e Sociali.
Dal 2016 membro Commissione Paritetica Dipartimento Scienze Politiche e Sociali Università di Pavia.
Dal 2016 membro del Nucleo di Valutazione dell’Istituto di Studi Superiori Universitari IUSS Pavia.
(2015 – 2017) membro del Nucleo di Valutazione dell’Università degli Studi di Pavia.
(2012 – 2015) membro della Giunta del Dipartimento di Scienze Politiche e Sociali, Università di Pavia.


Temi di interesse


Machine Learning; Deep Learning; Intelligenza Artificiale; Modellistica matematica; Misure di concentrazione e di polarizzazione; Teoria delle decisioni; Statistica Bayesiana.


Pubblicazioni


Pubblicazioni su Riviste Internazionali
Figini S., Maggi M. and Uberti P.(2018) The market rank indicator to detect financial distress, Econometrics and Statistics, https://doi.org/10.1016/j.ecosta.2017.12.001

Figini S., Bonelli F., Giovannini E. (2017) Solvency prediction for Small and Medium Enterprises in banking, Decision Support Systems, vol. 102, pp. 91-97.

Figini S. and Giudici P. (2017) Credit risk assessment with Bayesian model averaging, in Communications in Statistics - Theory and Methods, vol. 46, pp. 9507-9517.

Figini S., Savona R., Vezzoli M. (2016) Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach, in Intelligent Systems in Accounting Finance and Management, Vol. 23, Issue 1, pp. 6–20.

Figini S. Gao L. and Giudici P. (2015) Bayesian Operational Risk Models, Journal of Operational Risk, vol. 10, pp. 45-60.

Gigliarano C., Figini S., Muliere P. (2014) Making Classifier Performance Comparisons when ROC Curves intersect, Computational Statistics and data analysis, vol. 77, pp. 300-312.

Figini S., Giudici P. (2013) Measuring risk with ordinal variables, Journal of the Operational Risk, vol.8(2), pp. 35-43.

Figini S., Uberti P. (2013) Concentration measures in risk management, Journal of the Operational Research Society, vol. 64, pp. 718-723.

Cutillo L., Carissimo A.M. and Figini S., (2012) Network Selection: A Method for Ranked Lists Selection, PLOSOne, vol. 7(8).

Dridi A., Figini S., Giudici P. and Limam M. (2011) A financial Stress Index for the analysis of XBRL data, Journal of Financial Transformation, pp. 219-223.

Figini S. and Giudici P., (2011) Statistical Merging of Rating Models, Journal of the Operational Research Society, vol. 62, 1067-1074.

Figini, S., Kenett, R. and Salini S. (2010) Optimal scaling for risk assessment: merging of operational and financial data, Quality and Reliability Engineering International, vol. 26(8), pp. 887-897.

Figini, S. and Giudici P.(2010) Statistical Local Models for Customer Lifetime Value, Advances and Applications in Statistics, vol. 18(1), pp. 41 – 55.

Figini, S. e Uberti P., (2010): Model assessment for predictive classification models, Communications in Statistics Theory and methods, vol. 39(18), pp. 3238-3244.

Figini, S. (2010): Penalised models to estimate customer survival, Statistical methods and applications, vol. 19, issue 1, 141-150.

Figini, S. (2010): Statistical local models for customer satisfaction data, in Journal of quality technology and quantitative management, Vol. 7, N.1, pp. 69-82.

Uberti, P. and Figini S. (2010): How to measure single-name credit risk concentrations, to appear in European Journal of Operational Research, vol. 202(1), 232-238.

Figini, S., Giudici, P., e Uberti P. (2010): A threshold based approach to merge data in financial risk management, Journal of Applied Statistics, vol. 37(11), pp. 1815-1824.

Figini, S., De Quarti, E. and Giudici (2009): Churn risk mitigation models for student’s behaviour, in Electronic Journal of Applied Statistical Analysis, Vol. 2, N.1, pp. 37 – 57.

Figini S. and Giudici P. (2009) String analysis for interaction detection, Journal of Applied Statistics, vol. 21, pp.281-288.

Figini, S. e Giudici, P. (2009): Bayesian Churn Models, in Advances and Applications in Statistical Sciences, Vol. 1, N. 2, pp. 285-310.

Figini, S., De Giuli, E., Giudici, P. and Fantazzini, D. (2009): Enhanced Credit Default Models for Heterogeneous SME Segments, in Journal of Financial Transformation Vol. 25 N.1, pp. 31-39.

Figini, S. e Giudici, P. (2009): Statistical models for e-learning data, in Statistical methods and applications, vol. 18, pp. 293-304.

Fantazzini D. and Figini S. (2009): Random Survival Forest models for SME Credit Risk Measurement, in Methodology and computing in applied probability, vol. 11, pp. 29-45.

Fantazzini, D. and Figini S. (2009): Default Forecasting for Small-Medium Enterprises: Does Heterogeneity Matter? in International Journal of Risk Assessment and Management Vol. 11, No.1(2) pp. 138-163.

Figini, S., Giudici, P., Uberti, P. and Sanyal, A. (2007) A statistical method to optimize the combination of internal and external data in operational risk measurement, in Journal of Operational Risk, Vol 2(4), pp. 69-78.

Baldini, P., Figini S. and Giudici, P. (2006): Nonparametric Approaches for e-Learning Data in Lecture Notes in Computer Science , 4065, pp. 548 – 560.

Figini, S. e Giudici, P. (2005): Link Analysis for fraud detection, Italian Journal of Applied Statistics, Vol. 17 – Fascicolo 3 – pp. 389 – 397.

Contributi su monografie di ricerca internazionali
Figini, S., Salini, S. (2009): Bayesian merging and calibration for OpR, to appear in “Operational risk management a practical approach to intelligent data analysis”, Wiley London.

Figini, S. (2009): Credit risk estimation for SME, to appear in Handbook of Research on Data Mining in Public and Private Sectors: Organizational and Government Applications (book edited by Prof. Antti Syväjärvi and Prof.. Jari Stenvall, University of Lapland, Finland and University of Tampere, Finland).

Figini, S. (2008): Data Mining for Lifetime Value estimation, to appear in Encyclopedia of Data Warehousing and Mining - 2nd Edition Editor: John Wang.

Figini, S. (2008): Predictive dynamics models for SMEs, in “Data Analysis and Classification: from the exploratory to the confirmatory approach”, Springer (series on Studies in Classification, Data Analysis and Knowledge organisation).

Cerchiello, P., Figini, S. and Giudici, P.(2007): Data mining, for business and industry (editors: Dave Stewardson Douglas C. Montgomery Tony Greenfield and Shirley Coleman), in Statistical Practice in Business and Industry, Wiley London, pp. 163-184.

Figini, S., Giudici, P., Polla, D., e Galliano, C. (2005): Survival Analysis Models to Estimate Customer Lifetime Value, Fifth IEEE International Conference on Data Mining (ICDM-2005), IEEE Computer Society Press, pp.114-124.

Relazioni invitate a convegni internazionali
Figini S. (2017) Credit data science risk models for SMEs, International workshop “Data science in Finance and Insurance”, Université Chatolique de Louven.

Figini S., Gigliarano C. e Muliere P. (2014) Assessment and comparison of survival models using concentration indices, Computational and Financial Econometrics Pisa.

Figini S., Gigliarano C. e Muliere P. (2013) On discrimination indices for survival models, Computational and Financial Econometrics London.

Figini S. e Madormo F. (2013) Risk estimation and assessment using survival models for credit risk data, Computational and Financial Econometrics London.

Figini S., e Giudici, P. (2012) Model uncertainty in credit rating models, Computational and Financial Econometrics Oviedo.

Figini S., e Giudici, P. (2012): Improving Model averaging in credit risk analysis, COMPSTAT, Cipro.

Figini, S., e Kenett, R. (2009): Integrating Operational and Financial Risk Assessments, ENBIS9 meeting, Gothenburg.

Figini, S. (2009): Statistical models for XBRL data, EURISBIS 2009, International Society of Business and Industrial Statistics meeting, Cagliari.

Figini, S., e Giudici P. (2009): Non linear rating models for SMEs, EURISBIS 2009, International Society of Business and Industrial Statistics, Cagliari.

Figini, S. (2008): Model clustering and Model averaging, Classification and Data Analysis Group of the Italian Statistical Society meeting, Caserta.

Brooks, S.P., Figini, S. e Giudici, P. (2007): Bayesian models to estimate customer survival, ISBA meeting Valencia.

Figini, S. and Giudici, P. (2005): Bayesian Feature selection for the estimation of customer lifetime value, M2005, Data Mining Conference, Las Vegas.

Comunicazioni su atti di convegno internazionali
Figini S., Gigliarano C. and Muliere P. (2014) Assessment and comparison of survival models using concentration indices, Computational Financial Econometrics 2014.

Figini S., Vezzoli M. (2013) Ensemble models: theory and applications, International Conference of the Royal Statistical Society (selected paper), New Castle.

Figini S., Vehtari A. (2013) Gaussian Process Classification And Duration Models For Credit Risk, International Federation of Classification Societies, Tilburg.

Figini S., Vezzoli M. (2013) Model Averaging For Credit Risk Modelling, International Federation of Classification Societies, Tilburg.

Figini S., Madormo F. (2013) Risk estimation and assessment using survival models for credit risk data, International Conference on Computational and Financial Econometrics, London.

Figini S., Giudici P. (2012) Improving model averaging in credit risk analysis, International Conference on Computational Statistics, Cyprus.

Figini S. (2012). Bayesian model averaging for financial evaluation. Meeting of the Italian statistical society.

Figini S., Cutillo L. and Carissimo A. (2011): Outlier detection in credit risk multivariate data via rank aggregation, Proceedings of the 4th International Conference of the ERCIM WG, London.

Figini S. (2011): A note on additively decomposable inequalities for risk measurement, Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society.

Figini S., Gao L. (2011): Bayesian efficient capital at risk estimation, Proceedings of the International conference ENBIS-DEINDE 2011, European Network for Business and Industrial Statistics & DEsign of INDustrial Experiments.

Figini S. (2011): Bayesian Extreme Value Analysis of operational risk data, Proceedings of the Italian Statistical Society.

Figini, S. (2010): Risk tendency measures for ordinal variables, Proceedings of the Italian Statistical Society.

Figini S., Giudici P. and Uberti P. (2010): Concentration measures for risk analysis, Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society.

Figini S. and Grossi L. (2010): Robust estimation and prediction for credit risk models, Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society.

Figini, S., Kenett, R. e Giudici, P. (2009): Integrating Operational and Financial Risk Assessments, ENBIS9 meeting, Gothenburg.

Figini, S. and Sayago, J. T. (2009): Longitudinal models for market reputation and risk, in Proceedings of the Italian Statistical Society, pp.263-266.

Figini, S. (2009): Local statistical models for variables selection, in Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society, pp. 489-492.

Figini, S. (2009): Statistical models for XBRL data, EURISBIS 2009.

Figini, S. (2009): Non linear rating models for SMEs, EURISBIS 2009.

Figini, S. (2009): Predictive rules induction via string analysis, Multivariate methods and models for evaluating public services, Rimini.

Figini, S. (2008): Model clustering and model averaging, in Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society, pp.125-128.

Figini, S. e Giudici, P. (2008): Methodological aspects to measure credit risk for SME, in Proceedings of the Italian Statistical Society.

Brooks, S.P., Figini, S. e Giudici, P. (2007): Bayesian models to estimate customer survival, in Proceedings of ISBA Valencia

Figini, S., Giudici, P. e Fantazzini, D. (2007): Longitudinal predictive models for SMEs, in Proceeding of the 2007 intermediate conference – Risk and Prediction – of the Italian Statistical Society, pp. 551-552.

Figini, S. e Fantazzini, D. (2007): Default forecasting for small medium enterprises, in Proceeding of S.Co.2007, Venezia, pp. 219-224.

Figini, S., Giudici, P. and Fantazzini, D. (2007): Predictive dynamic models for SMEs, in Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society, Macerata, pp. 193-196.

Figini, S. e Roccato, A. (2007): How to improve predictive models for database marketing applications, in Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society, Macerata, pp. 281-284.

Figini, S. (2006): Customer relationship: a survival analysis approach, in: Proceedings of COMPSTAT 2006, Roma , pp. 959-966.

Figini, S. e Giudici, P. (2006): Statistical models to analyse customer life cicle in Proceeding of XLIII Italian statistical society meeting, pp. 541 - 544 .

Figini, S. e Giudici, P. (2005): Feature selection in genomic predictive mining, in Proceedings of the Classification and Data Analysis Group of the Italian Statistical Society, pp. 249-252.

Figini, S. e Giudici, P. (2004): Modelli previsivi per text mining (in italiano), in Proceedings of the SAS CAMPUS, pp. 59-66, Firenze.

Figini, S. e Giudici, P. (2001): Correspondence analysis for CRM (in italiano), in Proceedings of SMDM01, Pavia .

Tesi
Figini, S. (2007): Bayesian variable and model selection for Customer Lifetime Value, Tesi di dottorato.

Figini, S. (2001): Analisi Statistiche delle corrispondenze per la classificazione e l' e-CRM, Tesi di laurea.

Libro
Giudici P. amd Figini S. (2009) Applied Data Mining for Business and Industry, 2nd edition Wiley ISBN 0470058862; 9780470058862.

Working paper
Figini S. and Galvani M. (2018): Pareto solutions in credit risk analytics, under review.

Figini S. and Uberti P. (2018): Indecision interval for the performance evalutation of binary classification models, under review.

Gigliarano C., Figini S. and Muliere P. (2017): Polarization-based discrimination indexes for survival risk models, under review.

Galvani M. and Figini S. (2017): Learning models to predict terrorist attacks, under review.