Mining Data to Catch Tax Cheats

This teaching case covers technical and non-technical concerns about data mining enabled by the creation of a data warehouse by the California Franchise Tax Board (CFTB). CFTB used data mining to analyze data collected from federal, state and municipal agencies and other organizations to identify residents who under-report income or fail to file tax returns. The case presents different stakeholders’ privacy, financial, technical and political concerns regarding the use of data obtained from an array of sources. The case is aimed at an undergraduate or MBA/MS course on IS Management, Data Management/Warehousing or Information Privacy. It could also be used to study IT and public policy, or E-government. It provides an opportunity for students to consider how social and political factors interact with technical challenges in inter-enterprise relationships. It also offers an opportunity to consider the value of data in relation to both the financial and non-financial costs of obtaining it

#Audited: Social Media and Tax Enforcement

With limited resources and a diminished budget, it is not surprising that the Internal Revenue Service would seek new tools to maximize its enforcement efficiency. Automation and technology provide new opportunities for the IRS, and in turn, present new concerns for taxpayers. In December 2018, the IRS signaled its interest in a tool to access publicly available social media profiles of individuals in order to “expedite IRS case resolution for existing compliance cases.” This has important implications for taxpayer privacy. Moreover, the use of social media in tax enforcement may pose a particular harm to an especially vulnerable population: low-income taxpayers. Social science research shows us that the poor are already over-surveilled, and researchers have identified various ways in which algorithmic screening and data mining can result in discrimination. What, then, are the implications of social media mining in the context of tax enforcement, especially given that the IRS already audits the poor at a rate similar to which it audits the highest earning individuals? How can these concerns be reconciled with the need for tax enforcement? This article questions the appropriateness of the IRS further automating its enforcement tactics in ways that may harm already vulnerable individuals, makes proposals to balance the use of any such tactics with respect for taxpayer rights, and considers how tax lawyers should advise their clients in an era of diminishing privacy

Digitalization and International Tax Dispute Resolution: A Window of Opportunity for BRITACOM

Digitisation technologies are facilitating and transforming tax administration and dispute resolution in various ways. This paper presents some existing and emerging best practices in digitalized tax administration and smart dispute resolution. Inspired by the objectives of the Belt & Road Initiative and BRITACOM and these best practices, this paper suggests that BRITACOM take advantage of digitisation and seize upon the unprecedented opportunity to create a digitalized mechanism for resolving cross-border tax disputes among Belt & Road jurisdictions

Why Internal Moral Enhancement Might Be politically Better than External Moral Enhancement

Technology could be used to improve morality but it could do so in different ways. Some technologies could augment and enhance moral behaviour externally by using external cues and signals to push and pull us towards morally appropriate behaviours. Other technologies could enhance moral behaviour internally by directly altering the way in which the brain captures and processes morally salient information or initiates moral action. The question is whether there is any reason to prefer one method over the other? In this article, I argue that there is. Specifically, I argue that internal moral enhancement is likely to be preferable to external moral enhancement, when it comes to the legitimacy of political decision-making processes. In fact, I go further than this and argue that the increasingly dominant forms of external moral enhancement may already be posing a significant threat to political legitimacy, one that we should try to address. Consequently, research and development of internal moral enhancements should be prioritised as a political project

The Distributed Liability of Distributed Ledgers: The Legal Risks of Blockchain

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=301821

Doubtful debt: the rising cost of student loans

The Commonwealth Government could save more than $800 million a year by 2017, according to this report, if it recovers outstanding student loans from deceased estates and people living overseas. Overview: Student loans have helped millions of Australians finance their higher education since the Government introduced the Higher Education Contribution Scheme, HECS, in 1989. The successor to HECS — the Higher Education Loan Program, HELP — lends more than$6 billion a year. It has been a very effective policy. But it has become expensive. By 2017 the Commonwealth will have $13 billion of loans on its books that it does not expect to collect. Students and former students repay their education debt only if they earn more than a threshold amount — currently$51,309 a year. Income contingent loans cleverly help cash-poor students pay for their education when they can afford to do so. Some of them never earn enough in Australia to repay what they borrowed. About 17 per cent of new lending is now classified as doubtful, meaning it is not expected to ever be fully repaid. This expense, which appears each year in the Commonwealth Budget, is projected to be $1.1 billion this financial year. With student numbers rapidly increasing, and new uses being found for income contingent loans, doubtful debt costs will continue to rise. This report investigates several ways of reducing doubtful debt while still protecting against financial hardship. One reason for doubtful debt is that HELP debtors leave Australia. Because HELP is repaid through the Australian income tax system it is not collected from people living elsewhere. England and New Zealand have similar student loan schemes and both require debtors in other countries to pay. This report recommends the New Zealand policy of requiring a flat annual repayment from student loan debtors living overseas. For debtors staying in Australia, some never earn more than the income threshold or do so for too few years to repay all their debt. Because the threshold is linked to average weekly earnings, it is increasing in real terms. Over time, this means that fewer debtors are obliged to repay. Linking the threshold to inflation would maintain its real value while increasing future repayment levels. Although these reforms would reduce HELP’s costs, on their own their effect on doubtful debt is modest. Its main cause is that HELP debt in deceased estates is written off. This is not a good use of scarce higher education funding. Most beneficiaries of the HELP write-off will not be financially dependent on the HELP debtor. Partnered HELP debtors earning less than the threshold are not usually the household’s main income earner. Their children will be adults by the time the estate is distributed. Introducing asset contingent HELP repayment for estates over$100,000 would radically improve HELP’s finances. If all these reforms were implemented now, they would save $860 million a year by 2016–17, and remove the need for planned cuts to teaching and research expenditure. HELP’s repayment system was never designed for lending on the scale we see today. With the reforms in this report, we can achieve the goals of HELP at a much lower cost

How Countries Should Share Tax Information

Offshore tax evasion, international money laundering, and aggressive international tax planning significantly reduce government revenues. In particular, for some low-income countries the amount of capital flight (where elites move and hide monies offshore in tax havens) exceeds foreign aid. Governments struggle to enforce their tax laws to constrain these actions, and they are inhibited by a lack of information concerning international capital flows. The main international policy response to these developments has been to promote global financial transparency through heightened cross-border exchanges of tax information. The Article examines elements of optimal cross-border tax information exchange laws and policies by focusing on three key challenges: information quality, taxpayer privacy, and enforcement. Relatedly, the Article discusses how the exchange of automatic big tax data combined with data analytics can help address these challenges. The recommended laws and policies will improve how countries share tax information, which in turn will help inhibit global financial crimes

The Promises and Perils of Using Big Data to Regulate Nonprofits

For the optimist, government use of “Big Data” involves the careful collection of information from numerous sources. The government then engages in expert analysis of those data to reveal previously undiscovered patterns. Discovering patterns revolutionizes the regulation of criminal behavior, education, health care, and many other areas. For the pessimist, government use of Big Data involves the haphazard seizure of information to generate massive databases. Those databases render privacy an illusion and result in arbitrary and discriminatory computer-generated decisions. The reality is, of course, more complicated. On one hand, government use of Big Data may lead to greater efficiency, effectiveness, and transparency; on the other hand, such use risks inaccurate conclusions, invasions of privacy, unintended discrimination, and increased government power. Until recently, these were theoretical issues for nonprofits because federal and state regulators did not use Big Data to oversee them. But nonprofits can no longer ignore these issues, as the primary federal regulator is now emphasizing “data-driven” methods to guide its audit selection process, and state regulators are moving forward with plans to create a single, online portal to collect required filings. In addition, regulators are making much of the data they collect available in machine-readable form to researchers, journalists, and other members of the public. The question now is whether regulators, researchers, and nonprofits can learn from the Big Data experiences of other agencies and private actors to optimize the use of Big Data with respect to nonprofits. This Article explores the steps that nonprofit regulators have taken toward using Big Data techniques to enhance their ability to oversee the nonprofit sector. It then draws on the Big Data experiences of government regulators and private actors in other areas to identify the potential promises and perils of this approach to regulatory oversight of nonprofits. Finally, it recommends specific steps regulators and others should take to ensure that the promises are achieved and the perils avoided

Spartan Daily, October 2, 1989

Volume 93, Issue 21https://scholarworks.sjsu.edu/spartandaily/7881/thumbnail.jp