Silvia Figini

Role: Associate Professor
Email: silvia.figini@unipv.it
Telephone: +39 0382 984661

 

 

Courses


Metodi quantitativi per l'analisi economica
Statistica

Office hours


Appuntamento via mail

Prossimi appelli


Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Lunedi 26/06/2017 14:30 Aula: E
Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Martedi 18/07/2017 09:30 Aula: E
Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Venerdi 15/09/2017 14:30 Aula: E
Statistica - Statistica economica - Metodi quantitativi per l'analisi economica  Venerdi 29/09/2017 14:30 Aula: E

Biography



Full Professor – Abilitazione Scientifica Nazionale 2013.

From 2014: Associate Professor of Statistics University of Pavia, Department of Political and Social Sciences.

2010-2014 Lecturer of Statistics University of Pavia, Department of Political and Social Sciences.

2006: Phd in Statistics Bocconi University Milan

Degree in Quantitative Economics, Universityof Pavia.

Visiting for research periods: (2006-2007) University of Cambridge (UK), (2013) University of Umea (Sweden), (2013) University of Aalto (Finland), (2013) University of Dublin, (2014) University of Edimburgh, (2014) University Paris 1 La Sorbonne.


Academic curriculum


European Research Project

SYRTO 2013-2016: “SYstemic Risk TOmography” – Partners: University of 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; European Central Bank; University Ca' Foscari Venice.

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

National Research Project
PRIN (2013-2015) Multivariate statistical models for risk assessment
PRIN (2007-2008) Multivariate statistical models for the evaluation of public services.
PRIN (2007) CHICOS
PRIN (2005-2006) Data mining for e-business applications.
FIRB (2006-2009) Data mining for SMEs.

Teaching
Statistics; Quantitative methods for economics; Applied Statistics.
Basics of Probability and Statistics Masters e PhD Programme in Risk and Emergency Management (REM)

Member of:
Italian Statistical Society
CLAssification and Data Analysis Group
International Society of Business and Industrial Statistics
European Network for Business and Industrial Statistics
International Association for Statistical Computing
International Society for Bayesian Analysis

Referee
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.


Research interests


Predictive and classification models for risk analysis; Bayesian models; Big data analytics; Social Network Analysis; Anti-money laundering models.


Recent publications


Papers in international journals

1. Gigliarano, Figini, Muliere (2014) Making Classifier Performance Comparisons when ROC Curves intersect, Computational Statistics and data analysis, vol. 77, pp. 300-312.
2. Figini, Giudici (2013) Measuring risk with ordinal variables, Journal of the Operational Risk, vol.8(2), pp. 35-43.
3. Figini, Uberti (2013) Concentration measures in risk management, Journal of the Operational Research society, vol. 64, pp. 718-723.
4. Figini, Carissimo and Cutillo (2012) Network Selection: A Method for Ranked Lists Selection, PLOSOne, vol. 7(8).
5. Figini, Giudici, Dridi, Limam (2011) A financial Stress Index for the analysis of XBRL data, accepted in Journal of Financial Transformation.
6. Figini, Giudici (2011) Statistical Merging of Rating Models, Journal of the Operational Research Society, vol. 62, 1067-1074.
7. Figini, S., Salini, S. and Kenett, R. (2010) Optimal scaling for risk assessment: merging of operational and financial data, Quality and Reliability Engineering International, vol. 26(8), pp. 887-897.
8. Figini, S. and Giudici P. (2010) Statistical Local Models for Customer Lifetime Value, Advances and Applications in Statistics, vol. 18(1), pp. 41 – 55.
9. Figini, S. e Uberti P., (2010): Model assessment for predictive classification models, Communications in Statistics Theory and methods, vol. 39(18), pp. 3238-3244.
10. Figini, S. (2010): Penalised models to estimate customer survival, Statistical methods and applications, vol. 19, issue 1, 141-150.
11. 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.
12. Figini, S. e Uberti, P. (2010): How to measure single-name credit risk concentrations, to appear in European Journal of Operational Research, vol. 202(1), 232-238.
13. Figini, S., Giudici, P., e De Quarti, E. (2009): Churn risk mitigation models for student’s behaviour, in Electronic Journal of Applied Statistical Analysis, Vol. 2, N.1, pp. 37 – 57.
14. 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.
15. Figini and Giudici (2009) String analysis for interaction detection, accepted in Italian Journal of Applied Statistics, vol. 21, pp.281-288 .
16. Figini, S. e Giudici, P. (2009): Bayesian Churn Models, in Advances and Applications in Statistical Sciences, Vol. 1, N. 2, pp. 285-310.
17. Figini, S., Fantazzini, D., De Giuli, E. e Giudici, P. (2009): Enhanced Credit Default Models for Heterogeneous SME Segments, in Journal of Financial Transformation Vol. 25 N.1, pp. 31-39.
18. Figini, S. e Giudici, P. (2009): Statistical models for e-learning data, in Statistical methods and applications, vol. 18, pp. 293-304.
19. Figini, S. e Fantazzini D. (2009): Random Survival Forest models for SME Credit Risk Measurement, in Methodology and computing in applied probability, vol. 11, pp. 29-45.
20. Figini, S. e Fantazzini, D. (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.
21. Figini, S., Giudici, P., Uberti, P. e 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.
22. Figini, S., Baldini, P. e Giudici, P. (2006): Nonparametric Approaches for e- Learning Data , in Lecture Notes in Computer Science , 4065, pp. 548 – 560.
23. Figini, S. e Giudici, P. (2005): Link Analysis for fraud detection, Italian Journal of Applied Statistics, Vol. 17 – Fascicolo 3 – pp. 389 – 397.

Book

Giudici,P. and Figini S. (2009): Applied data mining for business and industry, Wiley, London.

Papers on international books

1. 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.
2. 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 (University of Lapland, Finland and University of Tampere, Finland).
3. Figini, S. (2008): Data Mining for Lifetime Value estimation, to appear in Encyclopedia of Data Warehousing and Mining - 2nd Edition Editor: John Wang.
4. 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).
5. Figini, S., Giudici, P. e Cerchiello, 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.
6. 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.

International Proceedings

1. Figini S., Vezzoli M. (2013) Ensemble models: theory and applications, International Conference of the Royal Statistical Society (selected paper), New Castle
2. Figini S., Vehtari A. (2013) Gaussian Process Classification And Duration Models For Credit Risk, International Federation of Classification Societies, Tilburg
3. Figini S., Vezzoli M. (2013) Model Averaging For Credit Risk Modelling, International Federation of Classification Societies, Tilburg
4. Figini S., Madormo F. (2013) Risk estimation and assessment using survival models for credit risk data, International Conference on Computational and Financial Econometrics, London.
5. Figini S., Giudici P. (2012) Improving model averaging in credit risk analysis, International Conference on Computational Statistics, Cyprus.
6. Figini S. (2012). Bayesian model averaging for financial evaluation. Meeting of the Italian statistical society.
7. 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.
8. 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.
9. 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.
10. Figini S. (2011): Bayesian Extreme Value Analysis of operational risk data, Proceedings of the Italian Statistical Society.
11. Figini, S. (2010): Risk tendency measures for ordinal variables, Proceedings of the Italian Statistical Society.
12. 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.
13. 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.
14. Figini, S., Kenett, R. e Giudici, P. (2009): Integrating Operational and Financial Risk Assessments, ENBIS9 meeting, Gothenburg.
15. Figini, S. and Sayago, J. T. (2009): Longitudinal models for market reputation and risk, in Proceedings of the Italian Statistical Society, pp.263-266.
16. 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.
17. Figini, S. (2009): Statistical models for XBRL data, EURISBIS 2009.
18. Figini, S. (2009): Non linear rating models for SMEs, EURISBIS 2009.
19. Figini, S. (2009): Predictive rules induction via string analysis, Multivariate methods and models for evaluating public services, Rimini.
20. 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.
21. Figini, S. e Giudici, P. (2008): Methodological aspects to measure credit risk for SME, in Proceedings of the Italian Statistical Society.
22. Brooks, S.P., Figini, S. e Giudici, P. (2007): Bayesian models to estimate customer survival, in Proceedings of ISBA Valencia.
23. 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.
24. Figini, S. e Fantazzini, D. (2007): Default forecasting for small medium enterprises, in Proceeding of S.Co.2007, Venezia, pp. 219-224.
25. 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.
26. 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.
27. Figini, S. (2006): Customer relationship: a survival analysis approach, in: Proceedings of COMPSTAT 2006, Roma , pp. 959-966.
28. Figini, S. e Giudici, P. (2006): Statistical models to analyse customer life cicle in Proceeding of XLIII Italian statistical society meeting, pp. 541 - 544 .
29. 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.

Invited talks

1. Figini S., e Giudici, P. (2012): Improving Model averaging in credit risk analysis, COMPSTAT, Cipro.
2. Figini, S., e Kenett, R. (2009): Integrating Operational and Financial Risk Assessments, ENBIS9 meeting, Gothenburg.
3. Figini, S. (2009): Statistical models for XBRL data, EURISBIS 2009,
International Society of Business and Industrial Statistics meeting, Cagliari.
4. Figini, S., e Giudici P. (2009): Non linear rating models for SMEs, EURISBIS 2009, International Society of Business and Industrial Statistics, Cagliari.
5. Figini, S. (2008): Model clustering and Model averaging, Classification and Data Analysis Group of the Italian Statistical Society meeting, Caserta.
6. Brooks, S.P., Figini, S. e Giudici, P. (2007): Bayesian models to estimate customer survival, ISBA meeting Valencia.
7. Figini, S. and Giudici, P. (2005): Bayesian Feature selection for the estimation of customer lifetime value, M2005, Data Mining Conference, Las Vegas.

PHD Thesis

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