This thesis explores if fraud or mismanagement in municipal governments can be diagnosed or detected in advance of their bankruptcies by financial statement analysis using Benford’s Law. Benford’s Law essentially states that the distribution of first digits from real world observations would not be uniform, but instead follow a trend where numbers with lower first digits (1, 2…) occur more frequently than those with higher first digits (…8,9). If a data set does not follow Benford’s distribution, it is likely that the data has been manipulated. This widespread phenomenon has been used as a tool to detect anomalies in data sets. The annual financial statements of Jefferson County, Vallejo City, and Orange County were analyzed. All the data sets showed overall nonconformity to Benford’s Law and therefore indicated that there was the possibility of fraud occurring. I find that Benford’s Law, had it been applied in real time to those financial statements, would have been able to detect that something was amiss. That would have been very useful because each of those jurisdictions subsequently went bankrupt. This paper demonstrates that Benford’s Law may in some cases be useful as an early indicator to detect the possibility of fraud in municipal governments’ financial data.

Dans cette thèse, la fiabilité des provisions comptables environnementales est évaluée par une combinaison de méthodes de recherche quantitatives et qualitatives dans une perspective de triangulation des résultats. Tout d'abord, l'étude de la divulgation de ces provisions par les groupes cotés français révèle son insuffisance et sa dégradation sur la période 2005-2010. Ensuite, l'utilisation de tests d'adéquation à la loi de Benford pour les montants comptabilisés au bilan et de régressions multiples pour les impacts au résultat ne permettent pas de remettre en cause la fiabilité des provisions environnementales divulguées par le même échantillon de groupes cotés français. Ces résultats contrastent avec ceux des recherches antérieures validant l'utilisation discrétionnaire des provisions environnementales pour lisser le résultat et limiter l'émergence de coûts politiques. L'étude de cas multiple conduite au niveau des acteurs de ces mêmes groupes explique cette fiabilité des montants par celle de leur processus de détermination et les nombreuses pressions institutionnelles qui l'encadrent. Les résultats de cette thèse indiquent donc que certains choix comptables pouvant affecter le résultat de façon discrétionnaire sont davantage expliqués par les pressions institutionnelles subies que par la volonté des dirigeants d'améliorer leur situation personnelle. / In this dissertation, the reliability of environmental provisions is assessed through a combination of quantitative and qualitative research methods to ensure a triangulation of the results. Firstly, the study of their disclosure by the French listed companies reveals its insufficiency and its degradation over the period of 2005-2010. Secondly, both compliance tests to Benford's law and multiple regression analyses do not undermine the reliability of environmental provisions disclosed by the same sample of French listed companies. These results contrast with previous research validating the use of discretionary environmental provisions to smooth earnings and to limit the emergence of political costs. Thirdly, the multiple case study conducted through semi-structured interviews with actors of these groups explains the reliability of environmental provisions by the one from their assessment process and the important institutional pressure that surrounds it. Therefore, the results of this dissertation suggest that some accounting choices that can discretionary affect earnings are better explained by institutional pressure than by the willingness of managers to improve their personal situations.

Context: Today it is easy to do banking transaction digitally, both on a computer or by using a mobile phone. As the banking-services increases and gets implemented to multi-platforms it makes it easier for a fraudster to commit financial fraud. This thesis will focus on investigating log-files from a Mobile Money system that makes it possible to do banking transactions with a mobile phone.  Objectives: The objectives in this thesis is to evaluate if it is possible to combine two statistical methods, Benford's law together with statistical quantiles, to find a statistical way to find fraudsters within a Mobile Money system. Methods: Rules was extracted from a case study with focus on a Mobile Money system and limits was calculated by using quantiles. A fraud detector was implemented that use these rules together with limits and Benford's law in order to detect fraud.The fraud detector used the methods both independently and combined.The performance was then evaluated. Results: The results show that it is possible to use the Benford's law and statistical quantiles within the studied Mobile Money system. It is also shown that there is only a very small difference when the two methods are combined or not both in detection rate and accuracy precision. Conclusions: We conclude that by combining the chosen methods it is possible to get a medium-high true positive rates and very low false positive rates. The most effective method to find fraudsters is by only using quantiles. However, combining Benford's law with quantiles gives the second best result.

In order for governments and demographers to, among other things, design policies and pensionplans, as well as for insurance companies to offer policies that serve general public, having reliable mortality data plays a crucial role. The academic world works actively in developing tools (models and methods) that can, based on collected mortality data, forecast future death rates in the observed population. Obviously, to be able to rely on the predicated data one needs a reliable source of existing mortality data. In the light of the ongoing COVID-19 pandemic, reliability of certain death-case reporting has been questioned. In this thesis, the Benford’s Law is used to evaluate how well countries with authoritarian regimes (Azerbaijan, Belarus),and with democratic regimes (Greece, Serbia, Sweden), report their COVID-19 cases to theworldwide public. Statistical tests such as the Chi-squared test, mean absolute deviation, and the distribution distance were used to obtain the results needed to form our conclusions. During our testing, we found that countries with democratic regimes do conform better to the Benford’s law than the authoritarian ones.

Can the law of the natural distribution of random numbers expose malice in financial markets? This thesis aims to analyze the indices S&P 500 and STOXX 600, in an effort to identify days in which behavior in the market was the result of financial manipulation or non normal market movements. What was discovered by extending a previous study [10], was that we could accurately identify many days in which the market crashed or was affected by malpractice similar to the events in the 2007-2008 financial crisis.

Regulation Crowdfunding, enacted in May 2016, is intended to facilitate capital formation in startups and small businesses funded primarily by small investors (Securities and Exchange Commission (SEC), 2016b). This dissertation investigates (1) the risk of fraud in equity crowdfunding offerings and (2) whether investors respond to fraud signals by selecting (rejecting) offers with low (high) fraud risk. Because equity crowdfunding is quite new, no frauds have yet been identified. Therefore, I employ a predictive analytics tool, Benford’s Law, to assess the fraud risk of the offering. I select observable indicators to represent the Fraud Triangle dimensions—incentives, opportunities and rationalization—and test if they predict fraud risk. I also compare offer funding outcomes to my fraud risk assessments to identify if investors’ selections consider fraud risk appropriately. The relaxed auditor assurance and disclosure requirements attracts both honest and dishonest founders, but I find that the risk of fraud is higher in equity crowdfunding offers than in public offerings as reported by other studies. I find that there are several individual fraud indicators and models that explain fraud risk, but these do not predict whether the offer is funded or not (funding outcomes) or the amount that is raised if funded. This dissertation is the first to apply Benford’s Law to equity crowdfunding offers and map fraud attributes to fraud risk and funding outcomes. My dissertation can inform investors, issuers, regulators, intermediaries and practitioners of the high risk of fraud in equity crowdfunding offerings and of several noteworthy fraud indicators. / Business Administration/Accounting

The increasing usage of algorithms and extensive collections of data have changed the discipline of finance and created new possibilities for analyzing the financial markets. To further explore the potential of developing new methods for understanding financial market behaviour, this thesis examines the first digit probability distribution of Benford's Law and its applicability within the financial markets. The research investigates various indices', equities', and technical analysis tools' conformity to Benford's Law by using relative price changes and volume traded. It was found that both indices and equities exhibit resemblance with Benford's Law, whereas technical analysis tools did not. In addition, the relevance of data frequency was explored, but it was deemed not to have any effect on conformity found. In an attempt to apply the findings, a regression analysis was conducted to forecast volatility. However, even though correlation was found, the regression model failed to predict future volatility accurately. / Den ökade användningen av algoritmer och omfattande datainsamling har förändrat det finansiella spelrummet och skapat nya möjligheter för analys av finansmarknaden. För att ytterligare undersöka potentialen i att utveckla nya metoder för att förstå finansmarknadens beteende utforskar denna avhandling Benfords lag och dess tillämpbarhet på den finansiella marknaden. Studien testar olika index, aktiers och tekniska analysverktygs överensstämmelse med Benfords lag genom att använda relativa prisförändringar och handlad volym. Det visade sig att både index och aktier följer Benfords lag medan tekniska analysverktyg inte gjorde det. Dessutom undersöktes datafrekvensens relevans, men detta ansågs inte ha någon effekt på överensstämmelsen med fördelningen. I ett försök att tillämpa resultaten genomfördes en regressionsanalys för att prognosticera volatilitet. Korrelation hittades men regressionsmodellen gav inte ett tillförlitligt resultat.