Promoting entrepreneurship in Morocco among young people has been a challenge for some years of economic and social problems, especially after the events of the Arab Spring. Several programs have been set up by the government for young entrepreneurs. Thus, faced with the large number of credit applications solicited by these young entrepreneurs, banks are obliged to resort to artificial intelligence techniques. For this purpose, the aim of this article is to propose a decision-making system enabling the bank to automate its credit granting process. It is a tool that allows the bank, in the first instance, to select promising projects through a scoring approach adapted to this segment of young entrepreneurs. In a second step, the tool allows the setting of the maximum credit amount to be allocated to the selected project. Finally, based on the knowledge of the bank's experts, the tool proposes a breakdown of the amount granted by the bank into several products adapted to the needs of the entrepreneur.

<span lang="EN-US">This paper proposes an ontological scorecard model for credit risk management. The purpose of credit scoring model is to reduce the possibility of potential losses with regard to issued loans. Loans are provided according to strict criteria which contain information about the client, loan structure, the purpose, repayment source and collateral. Several techniques have been used for credit risk assessment before granting a loan. Ontology design patterns is used here to enable the implementation of domain knowledge using the OWL rules and to improve the decision making process in credit monitoring. The modeling of our ontology will make the data publication simpler and graph structures intuitive, thus making its reusability and expandability easier.</span>

The different policies adopted at the national and international level aimed at investing in the youth to accelerate their development on all socio-economic, political and cultural sectors. This orientation is based on the considerable growth of this population of youth from 15 to 29 years old representing about one third of the total population of the MENA region (Middle East and North Africa) (Approximately more than 100 million). However, lack of direction and support needed to fully contribute to the development of their communities, this potential can turn into frustration, as demonstrated by the "Arab Spring". In this sense and to promote the opportunities with these young people, Morocco has launched several employment programs like “Moukawalati” directing them to the world of entrepreneurship. From the perspective of successful operational deployment of these programs, this paper presents a practical approach of selection of the promising projects through the implementation of a highly predictive scoring approach adapted to the specificities of this segment of young micro-entrepreneurs.

Special ISSUE VSST 2016 This paper proposes an ontological integration model for credit risk management. It is based on three ontologies; one is global describing credit risk management process and two other locals, the first, describes the credit granting process, and the second presents the concepts necessary for the monitoring of credit system. This paper also presents the technique used for matching between global ontology and local ontologies.

The latest biggest financial crisis reveals different weakness points over the global financial system. The concentration risk is one of many different risks that figured out by the regulators after the 2008 financial crisis. To deal with such a risk the regulators set up a dispositive of measures to control it. Therefore, we suggest in this paper a version of a mathematical model that optimize the allocation of capitals for a credit portfolio of a bank with taking into consideration the Moroccan regulatory environment.