Implicit rating: A potential new method to alert crisis on the interbank lending market

A new measure called “implicit rating” is introduced which might be a component of an early warning system. The proposed methodology relies on the aggregation of experts’ knowledge hidden in the transactional data of the interbank market of unsecured loans. Banks are simultaneously assessing the creditworthiness of each other which is reflected in the partner limits and in the interest rates. In the Hungarian interbank market the overall trading volume and the average interest rate did not show any negative trends before the crisis of 2008, however the average implicit partner limit started to decrease several months earlier, hence it might serve as a stress indicator

The Role of Artificial Intelligence, Financial and Non-Financial Data in Credit Risk Prediction: Literature Review

Small and medium-sized enterprises (SMEs) are of major importance in world economies and job creation. Financing is one of the key issues for SME development since SMEs are often considered riskier than large companies. It is argued in the literature that artificial intelligence (AI) and non-financial data could increase the financial inclusion of disadvantaged groups, such as SMEs. This article presents an overview of selected studies on credit risk prediction from the 1960s to 2022, covering topics of research work applying classical statistical methods, studies using AI methods on traditional financial data and studies applying AI methods on non-financial data. Literature overview results showed that the inclusion of non-financial data in credit risk prediction models could increase credit risk prediction performance, while AI methods can enable the inclusion of non-financial data. Since non-financial data potentially could be used as alternative data in credit prediction models, AI and non-financial data could help to increase access to finance for SME

Razvrščanje strateških in operativnih ciljev trajnostnega razvoja Pohorja, Slovenija

The combination of participatory process and multi-criteria decision methods have proven to be effective in supporting forest management decisions, since it offers inclusion of different opinions, views, and preferences of the problem. Our study is based on the results of the NATREG project, which deals with management of Pohorje, a mountain area in Slovenia. The results define six strategic goals and appertaining operative goals, which are the outcomes of workshops with different stakeholders. The aim of our study is ranking the strategic goals according to their contribution in the implementation of the "Pohorje 2030" vision and of the operative goals according to the appertaining strategic goals. Analytic hierarchy process is applied for comparisons of goals. Geometric mean method is employed for aggregating individual judgments into group judgment. The results show that all strategic goals are important, although most attention should be devoted to the goals "Preserved cultural heritage and local tradition" and "Environmental and consumer friendly usage of natural resources".Kombinacija participatornega vključevanja deležnikov v proces odločanja in večkriterijskih metod se je pri gospodarjenju z gozdom izkazala za uspešno, saj ponuja možnost vključevanja različnih mnenj, pogledov in preferenc problema. Osnova naše raziskave je projekt NATREG, ki je potekal na Pohorju v Sloveniji in v okviru katerega so določili šest strateških ciljev in pripadajoče operativne cilje. Cilj raziskave je razvrstitev strateških ciljev glede na njihov prispevek k uresničitvi vizije ŽPohorje 2030Ž in operativnih ciljev glede na pripadajoči strateški cilj. Za primerjavo ciljev smo uporabili metodo analitičnega hierarhičnega procesa. Individualne ocene smo združili v skupno oceno z geometrijsko sredino. Rezultati kažejo, da so pomembni vsi strateški cilji, najbolj pa "Ohranjena kulturna dediščina in lokalna izročila" in "Okolju in uporabniku prijazna raba naravnih virov"

Ranking strategic and operative goals for sustainable development of Pohorje, Slovenia

The combination of participatory process and multi-criteria decision methods have proven to be effective in supporting forest management decisions, since it offers inclusion of different opinions, views, and preferences of the problem. Our study is based on the results of the NATREG project, which deals with management of Pohorje, a mountain area in Slovenia. The results define six strategic goals and appertaining operative goals, which are the outcomes of workshops with different stakeholders. The aim of our study is ranking the strategic goals according to their contribution in the implementation of the “Pohorje 2030” vision and of the operative goals according to the appertaining strategic goals. Analytic hierarchy process is applied for comparisons of goals. Geometric mean method is employed for aggregating individual judgments into group judgment. The results show that all strategic goals are important, although most attention should be devoted to the goals “Preserved cultural heritage and local tradition” and “Environmental and consumer friendly usage of natural resources”

A model to forecast financial failure, in non financial galician SMES

We are concerned with providing more empirical evidence on forecast failure, developing forecast models, and examining the impact of events such as audit reports. A joint consideration of classic financial ratios and relevant external indicators leads us to build a basic prediction model focused in non-financial Galician SMEs. Explanatory variables are relevant financial indicators from the viewpoint of the financial logic and financial failure theory. The paper explores three mathematical models: discriminant analysis, Logit, and linear multivariate regression. We conclude that, even though they both offer high explanatory and predictive abilities, Logit and MDA models should be used and interpreted jointly

Bankruptcy prediction models in Galician companies. Application of parametric methodologies and artificial intelligence

This paper provides empirical evidence on the prediction of non-financial companies’ failure. We develop several models to evaluate failure risk in companies from Galicia. We check the predictive ability of parametric models (multivariate discriminant, logit) compared with auditor’s report. Models are based on relevant financial variables and ratios, in financial logic and a in financial distress situations. We examine a random sample of companies in cross-sectional perspective, checking the predictive capacity at any given time, also verifying is models give reliable signals to anticipate future events of financial distress. Findings suggest that our models are extremely effective when applied in medium and long term, and that they offer higher predictive capabilities than external audit.peer-reviewe

A Multiagent System For Web-Based Risk Management in Small and Medium Business

Business Intelligence has gained relevance during the last years to improve business decision making. However, there is still a growing need of developing innovative tools that can help small to medium sized enterprises to predict risky situations and manage inefficient activities. This article present a multiagent system especially conceived to detect risky situations and provide recommendations to the internal auditors of SMEs. The core of the multiagent system is a type of agent with advanced capacities for reasoning to make predictions based on previous experiences. This agent type is used to implement an evaluator agent specialized in detect risky situations and an advisor agent aimed at providing decision support facilities. Both agents incorporate innovative techniques in the stages of the CBR system. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented

A multi-agent system for web-based risk management in small and medium business

Business Intelligence has gained relevance during the last years to improve business decision making. However, there is still a growing need of developing innovative tools that can help small to medium sized enterprises to predict risky situations and manage inefficient activities. This article present a multi-agent system especially created to detect risky situations and provide recommendations to the internal auditors of SMEs. The core of the multi-agent system is a type of agent with advanced capacities for reasoning to make predictions based on previous experiences. This agent type is used to implement a evaluator agent specialized in detect risky situations and an advisor agent aimed at providing decision support facilities. Both agents incorporate innovative techniques in the stages of the CBR system. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented