contracts performance determines the profitability and stability of the financial institutions, and screening the loan applications is a key process in minimizing credit risk. Before making any credit decisions, credit analysis (the assessment of the financial history and financial backgrounds

been done to model and empirically test the decision process of individual lending officers in this market. Existing studies (i.e., Barry, Baker, and Sanint; Sonka, Dixon, and Jones).have concentrated primarily on.credit analysis of farm firms. The objec tive of this paper is to expand on existing

This study analyzes the courts ’ denial of women farmers ’ motion for class-action certifi-cation of their lawsuits alleging gender discrimination in Farm Service Agency (FSA) lending decisions. The plaintiffs ’ claim of “commonality ” of circumstances in women farmers ’ dealings with FSA is tested

are broadly consistent with the lending patterns observed during the recent ®nancial crises. I.

While the benefits of bank financing are relatively well understood, the costs are not. This paper argues that while informed banks make flexible financial decisions which prevent a firm's projects from going awry, the cost of this credit is that banks have bargaining power over the firm

We investigate the determinants of capital structure choice by analyzing the financing decisions of public firms in the major industrialized countries. At an aggregate level, firm leverage is fairly similar across the G-7 countries. We find that factors identified by previous studies as correlated

software we will gain access to more data, but not improve access to the type and quality of information needed for decision making. To develop the concepts needed for future information systems we model information processing as an interaction of data and knowledge. This model provides criteria for a high

type of rational agent, a BeliefDesire -Intention (BDI) agent. The primary aim of this paper is to integrate (a) the theoretical foundations of BDI agents from both a quantitative decision-theoretic perspective and a symbolic reasoning perspective; (b) the implementations of BDI agents from

by markets rather than by internal decisions within firms. Finally, several examples of companies where these changes are already occurring are used to illustrate the likely paths by which new market structures will evolve and the ways in which individual companies can take advantage of these changes.

introduced in this paper differ from those common to much of the computer vision literature in that the underlying random fields are non-Markovian and have a large number of parameters that must be estimated. Relations to other learning approaches, including decision trees, are given. As a demonstration