The Non-Financial Reporting Directive (“NFRD”),[1]is an important contributor to the European Union’s (EU) goal of creating a more sustainable future for all. By requiring large public-interest entities to report non-financial information relating to sustainability matters, the NFRD increases business transparency and gives stakeholders the opportunity to make more informed investment decisions, monitor corporate activities and initiate discussions based on current practices. The purpose of this thesis is to analyze the NFRD as it stands today and to analyze in what way the NFRD has the potential to improve by chiefly using the legal dogmatic method. The thesis reached its completion with an appropriate timing (January 2021) as the EU has announced its ambition to revise the NFRD by the first quarter of 2021. The conclusion drawn is that the NFRD should be revised on a series of points. Most importantly, reliability of the provided information should be secured through a stronger verification mechanism. Other areas for improvement concern the enlargement of the scope of the NFRD and the implementation of further measures securing comparable data.  [1]Directive 2014/95/EU.

La presente investigación busca identificar el impacto financiero en empresas del sector downstream de Hidrocarburos domiciliadas en Lima en el año 2020 en relación a las variaciones de tasa de cambio de la moneda extranjera. En el año 2020 hubo dos sucesos que afectaron la economía de las empresas del sector downstream de hidrocarburos, el primero es la caída de precios del petróleo, debido a la paralización de China y a un desacuerdo entre Arabia Saudita y Rusia respecto a los niveles de producción de petróleos, lo cual conlleva a una guerra de precios; el segundo sería la desaceleración de la economía global, causada por la Pandemia COVID-19. De esta manera, tenemos como objetivo de nuestra investigación identificar como es el tratamiento contable cuando se generan diferencias de cambio. Estas variaciones de tipo de cambio pueden generar un impacto importante en la rentabilidad o liquidez en las empresas del sector downstream de hidrocarburo. Por ello, este trabajo de investigación se encuentra organizado en 5 secciones. En el Capítulo I, Marco Teórico, se encontrarán las definiciones importantes y relevantes para que con ello el lector tenga un mejor entendimiento sobre el tema del impacto financiero que se genera con las variaciones del tipo de cambio. En el Capítulo II, Plan de investigación, se plantearon el problema principal, los objetivos e hipótesis generales y específicos. En el Capítulo III, Metodología de Investigación se identificó el tipo de investigación para el trabajo y se determinó el tamaño de la muestra para llevar a cabo el análisis de carácter cualitativo y cuantitativo. En el Capítulo IV, Desarrollo de la investigación, se podrá ver la ejecución de las entrevistas en profundidad y encuestas realizadas a los profesionales y funcionarios del sector a investigar. Para finalizar, en el Capítulo V, Análisis de resultados, se analizaron los resultados obtenidos de las encuestas y entrevistas, con ello se presentaron conclusiones y propusieron recomendaciones en base al trabajo de investigación y respuestas de los expertos en el sector. / This research seeks to identify the financial impact on companies in the downstream Hydrocarbons sector domiciled in Lima in 2020 in relation to changes in the foreign currency exchange rate. In 2020 there were two events that affected the economy of companies in the downstream hydrocarbon sector, the first being the fall in oil prices, due to the paralysis of China and a disagreement between Saudi Arabia and Russia regarding production levels oil, which leads to a price war; the second would be the slowdown in the global economy, caused by the COVID-19 Pandemic. In this way, our research objective is to identify how the accounting treatment is when exchange differences are generated. These exchange rate variations can have a significant impact on profitability or liquidity in companies in the downstream hydrocarbon sector. Therefore, this research work is organized in 5 sections. In Chapter I, Theoretical Framework, the important and relevant definitions will be found so that with this the reader has a better understanding of the issue of the financial impact that is generated with exchange rate variations. In Chapter II, Research Plan, the main problem, objectives and general and specific hypotheses were raised. In Chapter III, Research Methodology, the type of research for the work was identified and the sample size was determined to carry out a qualitative and quantitative analysis. In Chapter IV, Development of the investigation, it will be possible to see the execution of the in-depth interviews and surveys carried out with the professionals and officials of the sector to be investigated. Finally, in Chapter V, Analysis of results, the results obtained from the surveys and interviews were analyzed, thereby finding conclusions and proposing recommendations based on research work and responses from experts in the sector. / Tesis

Ekonomisk brottslighet är mer lukrativt jämfört med annan brottslighet som narkotika, häleri och människohandel. Tidiga åtgärder som försvårar att kriminella kan använda företag för brottsliga syften gör att stora kostnader för samhället kan undvikas. En genomgång av litteraturen visade också att det finns stora brister i samarbetet mellan svenska myndigheter för att upptäcka grov ekonomisk brottslighet. Idag uppdagas brotten först ofta efter att en konkurs inletts. I studier har maskininlärningsmodeller prövats för att kunna upptäcka ekonomisk brottslighet och några svenska myndigheter använder maskininlärningsmodeller för att upptäcka brott men mer avancerade metoder används idag av danska myndigheter. Bolagsverket har idag ett omfattande register för bolag i Sverige och denna studie syftar till att undersöka om maskininlärning kan användas för att identifiera misstänkta bolag, genom att använda digitalt inlämnade årsredovisningar och information ur bolagsverkets register för att kunna träna klassificeringsmodeller att identifiera misstänkta bolag. För att träna modellen så har stämningsansökningar inhämtats från Ekobrottsmyndigheten som kunnat kopplas till specifika bolag av de inlämnade årsredovisningar. Principalkomponentanalys används för att visuellt visa på skillnader mellan grupperna misstänkta och icke misstänkta bolag och analyserna visade på ett överlapp mellan grupperna och ingen tydlig klustring av grupperna. Data var obalanserat med 38 misstänkta bolag av totalt 1009 bolag och därför användes översamplingstekniken SMOTE för att skapa mer syntetiskt data och för att öka antalet i gruppen misstänkta. Två maskininlärningsmodeller Random Forest och Stödvektormaskin (SVM) jämfördes i en 10 fold korsvalidering. Där båda uppvisade en recall på runt 0.91 men där Random Forest hade en mycket högre precision och med högre accuracy. Random Forest valdes och tränades på nytt och uppvisades en recall på 0.75 när den testades på osett data bestående av 8 misstänkta av 202 bolag. Ett sänkt tröskelvärde resulterade i en högre recall men med en större antal felklassificerade bolag. Studien visar tydligt problemet med obalans i data och de utmaningar man ställs inför med mindre data. Ett större data hade möjligjort ett strängare urval på brottstyper som hade kunnat ge en mer robust modell som skulle kunna användas av bolagsverket för att lättare kunna identifiera misstänkta bolag i deras register. / Economic crimes are more lucrative compared to other crimes as drugs, selling of stolen gods, trafficing. Early preventions that make it more difficult for criminals to use companies for criminal purposes can reduce large costs for sociaty. A litterature study showed that there are large weaknesses in the collaboration between Swedish authorities to detect serious economic crimes.Today most crimes among companies that commit fraud are found after a company has declared bancruptcy. In studies, machine learning models have been tested to detect economic crimes and some swedish authorites are now using machine learning methods to detect different crimes and more advanced methods are used by the danish authorites. Bolagsverket has a large register of companies in Sweden and the aim of this study is to investigate if machinelearning can be used to detect on annual reports that have been digitaly submited and information in Bolagsverket’s register to be able to train classificationsmodels and identify companies that are suspicious. To be able to train the model lawsuits have been collected from the Swedish Economic Crime Authority that can be connected to specific companies through their digitally submited annual report. Principal component analysis is used to visually show differences between the groups suspect companies and not suspected companies and the analysis show that there is an overlap between the groups and no clear clustering between the groups. Because the dataset was unbalanced with 38 suspicious companies out of 1009 companies the oversampling tecnique SMOTE was used to create more synthethic data and more suspects in the dataset. The two machinelearnings models Random Forest and support vector machine (SVM) was compared in a 10 fold crossvalidation. Both models showed a recall on around 0.91 but Random Forest had a much higher precision with a higher accuracy. Random Forest was chosen and was trained again and showed a recall on 0.75 when it was tested on unseen data with 8 suspects out of 202 companies. Lowering the treshold resulted in a higher recall but with a larger portion of wrongly classfied companies. The study shows clearly the problem with an unbalanced dataset and the challanges with a small dataset. A larger dataset could have made it possible to make a more selective selection of certain crimes that could have resulted in a more robust model that could be used by Bolagsverket to easier identify suspicous companies in their register.

Cette thèse sur la nouvelle gouvernance financière publique dans le système des Nations Unies se présente en deux parties : première partie - La mise en œuvre de la nouvelle gouvernance financière publique dans les organisations du système des Nations Unies ; et deuxième partie - Le renforcement de la nouvelle gouvernance financière publique dans les organisations du système des Nations Unies. Pour notre étude, nous avons appliqué aux organisations du système des Nations Unies les éléments pertinents du cadre de référence établi par certains organes subsidiaires pour la nouvelle gouvernance financière publique, en particulier ceux qui se rapportent au cycle allant de la planification à l'établissement des rapports, dont il est question plus en détail dans les deux parties de la thèse. Ce cadre de référence vaut pour la nouvelle gouvernance financière publique dans son ensemble. Or. pour certaines activités spéciales, seule la budgétisation axée sur les résultats est pratiquée. Certains éléments du cadre de référence ne s'appliquent donc pas dans le contexte de la présente thèse, cependant d'autres aspects jugés importants pour toute démarche de la nouvelle gouvernance financière publique sont pris en compte. / This thesis on the new public financial governance in the United Nations system has two parts : first part - the implementation of the new public financial governance in organizations of the United Nations system ; and second part - the strengthening of the new public financial governance in organizations of the United Nations system. For our study, we applied the relevant elements of the terms of reference established by certain subsidiary bodies for new public financial governance in organizations of the United Nations system, in particular those that relate to the cycle from planning to establish reports being discussed more in detail in the two parts of the thesis. This framework applies to the new public financial governance as a whole. However, for some special activities, only the results-based budgeting is practiced. Some elements of the terms of reference do not therefore apply in the context of the present thesis, however, other aspects considered important for any new public financial governance process are taken into account.