DESIGNING OBJECT-ORIENTED REPRESENTATIONS FOR REASONING FROM FIRST-PRINCIPLES

Modeling expert knowledge using "situation-action" rules is not always feasible in knowledge intensive domains involving volatile knowledge (e.g., trading). The explosive search space involved in such domains and its dynamic nature make it extremely difficult to setup a rule base and keep it accurate. An alternative approach suggests that in some domains many of the rules expert use can be derived by reasoning from "first-principles". That approach entails modeling experts' deep knowledge, and emulating reasoning processes with deep knowledge that allow experts to derive many of the rules they use and justify them. This paper discusses the design and implementation of an object-oriented representation for the deep knowledge traders utilize in a business domain called hedging, which is knowledge intensive and involves volatile knowledge. It illustrates how deep knowledge modeled using that representation is used to support reasoning from first-principles. The paper also analyzes features of that representation that we have found to be extremely beneficial in the development of a knowledge-based system called INTELLIGENT-HEDGER. Based on our experience we feel that, with minor modifications, this representation can be used in other managerial domains involving financial reasoning.Information Systems Working Papers Serie

Primary Drivers of Software Maintenance Cost Studied Using Longitudinal Data

We examine the main drivers of software maintenance effort and cost. We use the ‘Distributed Cognition’ framework to hypothesize about how ‘discovery work’ in maintenance is effected by two types of cost drivers: system attributes (size, complexity, age, etc.) and personnel attributes (number of maintainers, location dispersion, etc.). We test our hypotheses using archival data about over 5,000 maintenance projects carried out between 2009 and 2011 on 412 different operational systems in a large financial institution. We find that personnel attributes are significantly more influential than system attributes. In particular, a marginal change in personnel factors is associated with effort growing much faster than cost, indicating an escalating marginal cost of spreading maintenance work across more maintainers and site locations. We also find, counter to expectation, that two system attributes are negatively linked to maintenance effort and cost. Implications of these findings for research and practices are discussed

QUALITATIVE SYNTHESIS OF CONFIGURATIONS FOR TWO-TERMINAL SYSTEMS BASED ON DESIRED BEHAVIOR

In design, inferring structure from function is a combinatorial generate-and-test problem. Existing methods use prestored domain-specific partial configurations to constrain the generator. We have found that for certain types of economic and physical systems consisting of two-terminal components connected in parallel, it is fruitful to specify function in terms of desired behavior, and to identify sets of components whose resultant behavior matches that desired behavior. In this paper, we present two synthesis operators called stretch and steepen that operate on qualitatively specified piecewise linear functions that characterize the behavior of components. We are currently applying this model to the domain of financial hedging, where behaviors of the components (stocks, bonds, options, etc.) are specified in terms of two-dimensional piecewise linear relationships, and the goal is to synthesize these to produce a constrained behavior in response to uncontrollable events.Information Systems Working Papers Serie

AN INTELLIGENT ASSISTANT FOR FINANCIAL HEDGING

Problems in Finance, particularly those involving risk assessment and management, have been slow to yield to expert systems technology for two reasons. First, expert reasoning in such problems is often based on âfirst principles" instead of âsituation-action" rules that characterize most expert systems. Secondly, the knowledge involved, such as that about financial instruments, is constantly changing. This would make it extremely difficult to keep a rule-base accurate. We have developed a representation in the domain of financial hedging that has the following characteristics. First, it allows for reasoning qualitatively based on first principles using the fundamental quantitative valuation models that characterize each instrument. Secondly, it uses object oriented concepts and inheritance to minimize the effort needed to set up the knowledge base and keep it current. Thirdly, it includes a calculus for derivation of qualitative knowledge of "one-dimensional-order", which allows it to solve problems where optimality constraints are qualitative.Information Systems Working Papers Serie

Linking Operational IT Failures to IT Control Weaknesses

Operational IT failures have significant negative effects on firms but little is known about their origins. Building on accounting research linking adverse operational events to SOX-disclosed control weaknesses (CWs) over financial reporting, we study the origins of IT failures in relation to IT-CWs. We use a sample of 212 operational IT failures where the confidentiality, integrity or availability of data assets and functional IT assets (hardware, networks, etc.) has been compromised. We find that IT failures are linked to a relatively small set of IT-CWs, where each IT failure type is linked to distinctly different IT-CWs. Moreover, IT failures more harmful to the firm are found to be associated with IT-CWs that are more sever and difficult to remediate

DESIGNING OBJECT-ORIENTED REPRESENTATIONS FOR REASONING FROM FIRST-PRINCIPLES

Modeling expert knowledge using "situation-action" rules is not always feasible in knowledge intensive domains involving volatile knowledge (e.g., trading). The explosive search space involved in such domains and its dynamic nature make it extremely difficult to setup a rule base and keep it accurate. An alternative approach suggests that in some domains many of the rules expert use can be derived by reasoning from "first-principles". That approach entails modeling experts' deep knowledge, and emulating reasoning processes with deep knowledge that allow experts to derive many of the rules they use and justify them. This paper discusses the design and implementation of an object-oriented representation for the deep knowledge traders utilize in a business domain called hedging, which is knowledge intensive and involves volatile knowledge. It illustrates how deep knowledge modeled using that representation is used to support reasoning from first-principles. The paper also analyzes features of that representation that we have found to be extremely beneficial in the development of a knowledge-based system called INTELLIGENT-HEDGER. Based on our experience we feel that, with minor modifications, this representation can be used in other managerial domains involving financial reasoning.Information Systems Working Papers Serie

An Event Study Analysis of the Economic Impact of IT Operational Risk and its Subcategories

Organizations’ growing exposure to IT operational risk, or the risk of failures of operational IT systems, could translate into significant losses. Despite this, there are notable theoretical and empirical gaps in the literature on IT operational risk. We propose the “resource weaknesses” framework, which extends the resource-based theory of the firm, as a theoretical lens for investigating IT operational risk and its impacts. We also theorize about and empirically examine the impact differences of two categories of IT operational failures: ones resulting in the disclosure, misuse, or destruction of data assets, and ones resulting in the loss of availability or the mis-operation of functional IT assets responsible for the handling of data assets. Whereas the former, data-related failures have had some coverage in the literature, little is known about the latter, function-related failures. We apply an event study analysis with a well-balanced data set of IT operational failure events that occurred in U.S. financial service firms over a 25-year period. We find that function-related events have a substantially larger negative wealth effect than data-related events, and that firm characteristics such as firm size and growth potential greatly influence the degree of wealth effect. We conclude with important implications for practice and research

Pricing e-service quality risk in financial services

a b s t r a c t E-service quality is crucial for differentiating e-commerce offers and gaining competitive advantage. Eservice quality risk is the risk that a firm's e-service quality will drop, or improve, relative to competitors. There is evidence that benchmark ratings of e-service quality that are published regularly by third-parties can impact the market value of rated firms. Firms therefore continue investing in IT-related determinants of e-service quality. However, they do so without knowing: (1) the cost or return associated with a unit relative deterioration, or improvement in e-service quality ratings, and (2) how this cost or return may vary across firms. To answer these questions, we adapt a well-established financial risk pricing approach for the case of pricing a single idiosyncratic IT investment risk, where an event study is used to generate the market data needed to price ris