Network based scoring models to improve credit risk management in peer to peer lending platforms

Financial intermediation has changed extensively over the course of the last two decades. One of the most significant change has been the emergence of FinTech. In the context of credit services, fintech peer to peer lenders have introduced many opportunities, among which improved speed, better customer experience, and reduced costs. However, peer-to-peer lending platforms lead to higher risks, among which higher credit risk: not owned by the lenders, and systemic risks: due to the high interconnectedness among borrowers generated by the platform. This calls for new and more accurate credit risk models to protect consumers and preserve financial stability. In this paper we propose to enhance credit risk accuracy of peer-to-peer platforms by leveraging topological information embedded into similarity networks, derived from borrowers' financial information. Topological coefficients describing borrowers' importance and community structures are employed as additional explanatory variables, leading to an improved predictive performance of credit scoring models

Monitoring Covid-19 contagion growth in Europe. CEPS Working Document No 2020/03, March 2020

We present an econometric model which can be employed to monitor the evolution of the COVID-19 contagion curve. The model is a Poisson autoregression of the daily new observed cases, and can dynamically show the evolution of contagion in different time periods and locations, allowing for the comparative evaluation of policy approaches. We present timely results for nine European countries currently hit by the virus. From the findings, we draw four main conclusions. First, countries experiencing an explosive process (currently France, Italy and Spain), combined with high persistence of contagion shocks (observed in most countries under investigation), require swift policy measures such as quarantine, diffuse testing and even complete lockdown. Second, in countries with high persistence but lower contagion growth (currently Germany) careful monitoring should be coupled with at least “mild” restrictions such as physical distancing or isolation of specific areas. Third, in some countries, such as Norway and Denmark, where trends seem to be relatively under control and depend on daily contingencies, with low persistence, the approach to restrictive measures should be more cautious since there is a risk that social costs outweigh the benefits. Fourth, countries with a limited set of preventive actions in place (such as the Netherlands, Switzerl

La nuova scheda per l’analisi sensoriale dell’aceto balsamico tradizionale

L’analisi sensoriale è uno strumento molto potente e utile nell’attribuzione qualitativa degli alimenti, essa è complementare alle analisi chimiche e strumentali perché porta informazioni di altra natura, complesse e non rilevabili in altro modo. Per questo motivo, i tentativi di “tarare” l’analisi sensoriale sulla composizione del balsamico sono infruttuosi e concettualmente scorretti. Un presupposto essenziale per assicurare l’efficacia dell’analisi sensoriale è che essa sia svolta con procedure che massimizzino l’indipendenza di giudizio degli assaggiatori sia all’interno del panel che nella sequenza dell’analisi del campione. In questo contesto gioca un ruolo chiave sia il metodo di assaggio che la scheda per la raccolta delle espressioni di gradimento

Explainable AI methods in cyber risk management

AbstractArtificial intelligence (AI) methods are becoming widespread, especially when data are not sufficient to build classical statistical models, as is the case for cyber risk management. However, when applied to regulated industries, such as energy, finance, and health, AI methods lack explainability. Authorities aimed at validating machine learning models in regulated fields will not consider black‐box models, unless they are supplemented with further methods that explain why certain predictions have been obtained, and which are the variables that mostly concur to such predictions. Recently, Shapley values have been introduced for this purpose: They are model agnostic, and powerful, but are not normalized and, therefore, cannot become a standardized procedure. In this paper, we provide an explainable AI model that embeds Shapley values with a statistical normalization, based on Lorenz Zonoids, particularly suited for ordinal measurement variables that can be obtained to assess cyber risk

Big data analysis for financial risk management

A very important area of financial risk management is systemic risk modelling, which concerns the estimation of the interrelationships between financial institutions, with the aim of establishing which of them are more central and, therefore, more contagious/subject to contagion. The aim of this paper is to develop a novel systemic risk model. A model that, differently from existing ones, employs not only the information contained in financial market prices, but also big data coming from financial tweets. From a methodological viewpoint, the novelty of our paper is the estimation of systemic risk models using two different data sources: financial markets and financial tweets, and a proposal to combine them, using a Bayesian approach. From an applied viewpoint, we present the first systemic risk model based on big data, and show that such a model can shed further light on the interrelationships between financial institutions

Significance and management of acetic acid bacteria culture collections

Acetic acid bacteria (AAB) are obligate aerobic microorganisms which have large significance in human life. Traditionally, AAB species have been used to produce fermented food and beverages thanks to their ability to oxidize ethanol to acetic acid. Moreover, in the last decades, they have been extensively investigated for other industrial biotechnology applications as the development of processes for highvalue products or biosensors. The potential exploitation of AAB diversity requires the existence of microbial culture collections, which are able to supply not only strains but essential data for fundamental microbial research. Therefore, microbial collections can be helpful to provide critical insights into AAB physiology and metabolism as well as integrate sequence data with transcriptional and functional studies to better define complex traits and develop new potential microbial processes. This article reviews the significance of microbial collections, with an overview of the well-known European Biological Resources Centers (BRCs) collecting AAB, and provides an insight into their cultivability and metabolic activity. It also discusses appropriate techniques in preserving authentic strains, quality control implications, databases and BRC networking as well as connections among collections and stakeholders

Dessert freddi: criteri per la loro classificazione [Cold dessert: criteria for their classification]

The expression “cold desserts” names a heterogeneous group of sweet products, which includes gelati, ice cream, pudding, mousse and more. The present work develop an inventory of all the sweet products falling under the definition of “cold desserts”. To reach this aim, several databases (Mintel GNPD), pastry’s books, industrial, as well as artisanal, products are going to be consulted. Moreover, the research has the objective to advance a rational organization of the sweet products comprised by the “cold dessert”’s definition. Thanks to such a logical organization, it will be possible to develop homogenous groupings of products, according to their characteristics. The variables with the greatest discriminating and grouping power employed in this research are: the product’s temperature of consumption, its structure, and the modalities through which it incorporates the air. The main difference between industrial and artisanal gelato is indeed in the modalities through which the air is incorporated in the products and in their consequently different rheological properties

A sociological assessment of conjugal conflict

A explicaçao sociológica do conflito conjugal tem sido muito referida, mas raramente testada empiricamente. Com base num conjunto de dados longitudinais recolhidosemduas fases junto de 1534 mulheresemrelações heterossexuais, usámos o modelo de equações estruturais (SEM) para medir o impacto da divisão do trabalho doméstico, do individualismo e do fechamento do casal sobre a probabilidade de conflitos conjugais. Os resultados indicam que o individualismo conjugal tem um grande impacto, a divisão do trabalho doméstico um impacto menor e o fechamento do casal não tem impacto no conflito conjugal. Os resultados são discutidos à luz dos actuais debates sociológicos sobre conjugalidade.A sociological explanation of conjugal conflict was often stressed but seldom empirically tested. Based on a two-wave longitudinal dataset of 1534 women in heterosexual relationships, we use structural equation modeling (SEM) to measure the impact of the division of household labor, individualism and conjugal closure on the likelihood of conjugal conflicts. Results indicate that conjugal individualism has a major impact, division of household labor a minor impact, and conjugal closure no impact, on conjugal conflict. Results are discussed in the light of current sociological debates on partnerships.L’explication sociologique du conflit conjugal a souvent été avancée mais rarement testée du point de vue empirique. À partir d’un ensemble de données longitudinales recueillies en deux phases auprès de 1534 femmes vivant en couple hétérosexuel, nous avons utilisé le modèle d’équations structurelles pour mesurer l’impact de la répartition des tâches ménagères, de l’individualisme et de l’isolement du couple sur la probabilité des conflits conjugaux. Les résultats indiquent que l’individualisme conjugal a un grand impact, la répartition des tâches ménagères un impact moindre et l’isolement du couple n’a pas d’impact sur le conflit conjugal. Les résultats sont discutés à la lumière des débats sociologiques actuels sur la conjugalité.La explicación sociológica del conflicto conyugal ha sido muy referida, pero raramente probada empíricamente. Con base en un conjunto de datos longitudinales recabados en dos etapas, con 1534 mujeres en relaciones heterosexuales, usamos el modelo de ecuaciones estructurales (SEM) para medir el impacto de la división del trabajo doméstico, del individualismo y del cierre de la pareja sobre la probabilidad de conflictos conyugales. Los resultados indican que el individualismo conyugal tiene un gran impacto, la división del trabajo doméstico un impacto menor y el cierre de la pareja no tiene impacto en el conflicto conyugal. Los resultados son discutidos a la luz de los actuales debates sociológicos sobre la vida en pareja