International Journal of Electronics and Computer Science Engineering 828 Available Online at www.ijecse.org ISSN- 2277-1956 Estimation of Credit Risk for Business Firms of Nationalized Bank by Neural Network Approach

Abstract—Financial credit risk assessment has gained a great deal of attention. Many different parties have an interest in credit risk assessment. Banking authorities are interested because it helps them to determine the overall strength of the banking system and its ability to handle adverse conditions. Due to the importance of credit risk analysis, many methods were widely applied to credit risk measurement tasks, from that Artificial Neural Network plays an important role for analyzing the credit default problem. Artificial neural networks represent an easily customizable tool for modeling learning behavior of agents and for studying a lot of problems very difficult to analyze with standard economic models ANN has many advantages over conventional methods of analysis. According to Shachmurove (2002), they have the ability to analyze complex patterns quickly and with a high degree of accuracy.The focus of this paper is to determine that a neural network is a suitable modelling technique for predicting the business firm loan is satisfactory or not. This paper shows that an ANN approach will classify the applicant as a default or not and predict a credit default allowance amount more closely aligned with the credit default expense incurred during the fiscal period than traditional management approaches to estimating the allowance. The results show that credit risk evaluation using Back propagation neural network and expert evaluation have the very good consistenc

On the catalytic mechanism and stereospecificity of Escherichia coli L-threonine aldolase

L-Threonine aldolases (L-TAs) represent a family of homologous pyridoxal 5′-phosphate-dependent enzymes found in bacteria and fungi, and catalyse the reversible cleavage of several l-3-hydroxy-α-amino acids. L-TAs have great biotechnological potential, as they catalyse the formation of carbon-carbon bonds, and therefore may be exploited for the bioorganic synthesis of l-3-hydroxyamino acids that are biologically active or constitute building blocks for pharmaceutical molecules. Many L-TAs, showing different stereospecificity towards the Cβ configuration, have been isolated. Because of their potential to carry out diastereoselective syntheses, L-TAs have been subjected to structural, functional and mechanistic studies. Nevertheless, their catalytic mechanism and the structural bases of their stereospecificity have not been elucidated. In this study, we have determined the crystal structure of low-specificity L-TA from Escherichia coli at 2.2Å resolution, in the unliganded form and cocrystallized with l-serine and l-threonine. Furthermore, several active site mutants have been functionally characterized in order to elucidate the reaction mechanism and the molecular bases of stereospecificity. No active site catalytic residue was revealed, and a structural water molecule was assumed to act as the catalytic base in the retro-aldol cleavage reaction. Interestingly, the very large active site opening of E. Coli L-TA suggests that much larger molecules than L-threonine isomers may be easily accommodated, and L-TAs may actually have diverse physiological functions in different organisms. Substrate recognition and reaction specificity seem to be guided by the overall microenvironment that surrounds the substrate at the enzyme active site, rather than by one ore more specific residues