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COMET: An Application of Model-Based Reasoning to Accounting Systems

AI Magazine

An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that process millions of transactions to produce the numbers summarized in a company's financial statements. Accounting sys-ems contain internal controls, procedures designed to detect and correct errors and irregularities that can occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur and evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. To cope with this complexity and variability, the COMET system applies a model-based reasoning approach to the analysis of accounting systems and their controls.


Mechanism Design for Social Good

arXiv.org Artificial Intelligence

Across various domains--such as health, education, and housing--improving societal welfare involves allocating resources, setting policies, targeting interventions, and regulating activities. These solutions have an immense impact on the day-to-day lives of individuals, whether in the form of access to quality healthcare, labor market outcomes, or how votes are accounted for in a democratic society. Problems that can have an out-sized impact on individuals whose opportunities have historically been limited often pose conceptual and technical challenges, requiring insights from many disciplines. Conversely, the lack of interdisciplinary approach can leave these urgent needs unaddressed and can even exacerbate underlying socioeconomic inequalities. To realize the opportunities in these domains, we need to correctly set objectives and reason about human behavior and actions. Doing so requires a deep grounding in the field of interest and collaboration with domain experts who understand the societal implications and feasibility of proposed solutions. These insights can play an instrumental role in proposing algorithmically-informed policies. In this article, we describe the Mechanism Design for Social Good (MD4SG) research agenda, which involves using insights from algorithms, optimization, and mechanism design to improve access to opportunity. The MD4SG research community takes an interdisciplinary, multi-stakeholder approach to improve societal welfare. We discuss three exciting research avenues within MD4SG related to improving access to opportunity in the developing world, labor markets and discrimination, and housing. For each of these, we showcase ongoing work, underline new directions, and discuss potential for implementing existing work in practice.



COMET: An Application of

AI Magazine

An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that process millions of transactions to produce the numbers summarized in a company's financial statements. Accounting systems contain internal controls, procedures designed to detect and correct errors and irregularities that can occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur and evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that produce the numbers summarized in the financial statements. Accounting systems contain internal controls, procedures designed to detect and correct errors and irregularities that can occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur, determine their downstream effects in the accounting system, and evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. In the United States, the Securities and Exchange Commission requires a yearly independent audit of the financial statements of public companies.


This nasty ransomware overwrites your PC's master boot record

PCWorld

It's hard enough for non-technical users to deal with ransomware infections: understanding public-key cryptography, connecting to the Tor anonymity network and paying with Bitcoin cryptocurrency. A new malicious program now makes it even more difficult by completely locking victims out of their computers. The new Petya ransomware overwrites the master boot record (MBR) of the affected PCs, leaving their operating systems in an unbootable state, researchers from antivirus firm Trend Micro said in a blog post. The MBR is the code stored in the first sectors of a hard disk drive. It contains information about the disk's partitions and launches the operating system's boot loader.


Petya ransomware overwrites MBRs, locking users out of their computers

PCWorld

It's hard enough for non-technical users to deal with ransomware infections: understanding public-key cryptography, connecting to the Tor anonymity network and paying with Bitcoin cryptocurrency. A new malicious program now makes it even more difficult by completely locking victims out of their computers. The new Petya ransomware overwrites the master boot record (MBR) of the affected PCs, leaving their operating systems in an unbootable state, researchers from antivirus firm Trend Micro said in a blog post. The MBR is the code stored in the first sectors of a hard disk drive. It contains information about the disk's partitions and launches the operating system's boot loader.


Online Energy Price Matrix Factorization for Power Grid Topology Tracking

arXiv.org Machine Learning

Grid security and open markets are two major smart grid goals. Transparency of market data facilitates a competitive and efficient energy environment, yet it may also reveal critical physical system information. Recovering the grid topology based solely on publicly available market data is explored here. Real-time energy prices are calculated as the Lagrange multipliers of network-constrained economic dispatch; that is, via a linear program (LP) typically solved every 5 minutes. Granted the grid Laplacian is a parameter of this LP, one could infer such a topology-revealing matrix upon observing successive LP dual outcomes. The matrix of spatio-temporal prices is first shown to factor as the product of the inverse Laplacian times a sparse matrix. Leveraging results from sparse matrix decompositions, topology recovery schemes with complementary strengths are subsequently formulated. Solvers scalable to high-dimensional and streaming market data are devised. Numerical validation using real load data on the IEEE 30-bus grid provide useful input for current and future market designs.


Mechanism Design for Double Auctions with Temporal Constraints

AAAI Conferences

This paper examines an extended double auction model where market clearing is restricted by temporal constraints. It is found that the allocation problem in this model can be effectively transformed into a weighted bipartite matching in graph theory. By using the augmentation technique, we propose a Vickrey-Clarke-Groves (VCG) mechanism in this model and demonstrate the advantages of the payment compared with the classical VCG payment (the Clarke pivot payment). We also show that the algorithms for both allocation and payment calculation run in polynomial time. It is expected that the method and results provided in this paper can be applied to the design and analysis of dynamic double auctions and futures markets.


New Polynomial Classes for Logic-Based Abduction

AAAI Conferences

We address the problem of propositional logic-based abduction, i.e., the problem of searching for a best explanation for a given propositional observation according to a given propositional knowledge base. We give a general algorithm, based on the notion of projection; then we study restrictions over the representations of the knowledge base and of the query, and find new polynomial classes of abduction problems.


Comet:odel-Based Reasoning to Accounting Systems

AAAI Conferences

Price Waterhouse Technology Centre 68 Willow Road Menlo Park, CA 94025-3669 {nado chams delisio hamscher)@tc.pw.com Abstract An important problem faced by auditors is gauging how much reliance can be placed on the accounting systems that process millions of transactions to produce the numbers summarized in a company's financial statements. Accounting systems contain internal controls, procedures designed to detect and correct errors and irregularities that may occur in the processing of transactions. In a complex accounting system, it can be an extremely difficult task for the auditor to anticipate the possible errors that can occur and to evaluate the effectiveness of the controls at detecting them. An accurate analysis must take into account the unique features of each company's business processes. To cope with this complexity and variability, the Comet system applies a model-based reasoning approach to the analysis of accounting systems and their controls. An auditor uses Comet to create a hierarchical flowchart model that describes the intended processing of business transactions by an accounting system and the operation of its controls. Comet uses the constructed model to automatically analyze the effectiveness of th controls in detecting potential errors. Price Waterhouse auditors have used Comet on a variety of real audits in several countries around the world. Auditors have the task of determining whether the financial statements of a company are a fair presentation of the company's financial position.