Reformen för frivillig revision genomfördes med syfte att möjliggöra valfrihet för revisionsfrågan utefter småföretagens egna behov och resurser. Trots att reformen genomfördes för över ett decennium sedan är forskarna fortfarande oense om effekterna av den avskaffade revisionsplikten. Det senaste åren har debatten kring återinförandet av revisionsplikten varit aktuell där argumenten bakom återinförandet baseras på den ökade ekonomiska brottsligheten och minskade lönsamheten hos de bolag som valt bort revisionen. Även de olika fördelar som revisorns kompetens och legitimitet som skapar trygghet för företagens intressenter är argument för återinförandet av revisionsplikten. Denna studie bidrar med en ökad förståelse och vägledning för småföretag i valet om frivillig revision. Syftet med denna studie är därför att undersöka om reformen för frivillig revision har påverkat konkursrisken hos svenska aktiebolag, samt om det finns andra finansiella faktorer som kan påverka småföretagens långsiktiga överlevnad. Syftet besvaras med utgångspunkt i tre teorier: legitimitetsteori, informationsasymmetri och signalteori, som dessutom utgör en del av den teoretiska referensramen. Den kvantitativa studien utvecklar hypoteser genom teorierna och den tidigare forskningen. Dessa ligger till grund för dataanalysen som sker genom logistisk regression för att skapa en konkursprognostiseringsmodell. Datamaterialet som undersökts består av sekundärdata genererad från Retriever Business av småföretag i Västra Götaland under period 2019. Studiens resultat visar att det finns ett signifikant negativt samband mellan revisorn och konkursrisk. Studien visar därmed att revisorn har en effekt på konkursrisken, även om det är svårt att fastställa den exakta påverkan som revisorn har på konkursrisken. Resultatet ger trots det indikationer på att återinförande av revisionsplikten skulle gynna såväl småföretagare som myndigheter och bidrar på så sätt med stöd till debatten om återinförandet av revisionsplikten. / The reform for voluntary audit was implemented with the aim of enabling freedom of choice regarding audit matters based on the needs and resources of small businesses. Despite the reform being implemented over a decade ago, researchers are still divided on the effects of abolishing the mandatory audit requirement. In recent years, there has been a debate on reintroducing the mandatory audit requirement, with arguments based on increased economic crime and decreased profitability among companies that have opted out of audits. The various advantages of the auditor's expertise and legitimacy in providing security for stakeholders are also arguments for the reintroduction of the mandatory audit requirement. This study contributes to a better understanding and guidance for small businesses in the decision-making process regarding voluntary audits. Therefore, the purpose of this study is to examine whether the reform for voluntary audit has influenced the bankruptcy risk of Swedish limited liability companies and to identify other financial factors that may affect the long-term survival of small businesses. The purpose is addressed based on three theories: legitimacy theory, information asymmetry, and signaling theory, which also form part of the theoretical framework. The quantitative study formulates hypotheses based on these theories and previous research. These hypotheses form the basis for data analysis using logistic regression to create a bankruptcy prediction model. The data analyzed consist of secondary data generated from Retriever Business on small businesses in Västra Götaland during the period 2019. Therefore, this study is written in Swedish. The study's results show a significant negative correlation between the auditor and bankruptcy risk. Thus, the study demonstrates that the auditor has an effect on bankruptcy risk, although it is difficult to determine the exact impact of the auditor on bankruptcy risk. In spite of that, the results provide indications that reintroducing the mandatory audit requirement would benefit both small business owners and authorities, thus offering support to the debate on reintroducing the mandatory audit requirement.

This study explores the financial performance measurement of South Africa's Top Companies. It aims to find a conclusion on the research problem, that is 'Do South Africa's Top Companies use the available arsenal to measure their financial performance?' Commerce and industry are the cornerstones of the economy of a country. This study purports to contribute to the ways and means of minimising the risk of business failures due to the resultant effects on the economy. The sample comprises of sixty companies. The sampling frame is the first hundred companies of the Financial Mail 200 Top Performers for 2004. The arsenal that is available to measure financial performance is researched in the financial literature. Mainly, this covers ratio analysis and interpretation, and the bankruptcy prediction models. To arrive at a conclusion on the research problem, a research instrument is developed from the host of financial ratios in the literature, including the bankruptcy prediction models. The research instrument comprises of popular ratios that are also found to be 'logical', as well as the ratios that make up the Z-Score bankruptcy prediction model. The instrument is called the Ratio Map and Z-Score and is applied to test the financial strengths/weaknesses of the Top Companies. In addition to the Ratio Map and Z-Score, the measures applied by the Top Companies as 'highlights' are analysed. This is done to determine the extent at which the measures unearth the strengths/weaknesses of the Top Companies. The conclusion drawn is that the Top Companies do not utilise the available arsenal to measure their financial performance. The supporting evidence is that the most frequently applied 'highlights' measures by the Top Companies cover only one area of the many financial fields of a company, that is, share performance. On the other hand, the analyses per Ratio Map and Z-Score have not revealed major material weaknesses in the financial position of the Top Companies. It is proposed that: ïf  More information be given in the notes to the financial statements to facilitate meaningful analysis; and ïf  A follow-up research study be done to assess the trends of the Top Companies. / Business Management / D.Comm. (Business Management)

Från 1900-talets början har banker och låneinstitut använt nyckeltal som hjälpmedel vid bedömning och kvantifiering av kreditrisk. För dagens investerare är den ekonomiska miljön mer komplicerad än för bara 40 år sedan då teknologin och datoriseringen öppnade upp världens marknader mot varandra. Bedömning av kreditrisk idag kräver effektiv analys av kvantitativa data och modeller som med god träffsäkerhet kan förutse risker. Under 1900-talets andra hälft skedde en snabb utveckling av de verktyg som används för konkursprediktion, från enkla univariata modeller till komplexa data mining-modeller med tusentals observationer. Denna studie undersöker om det är möjligt att prediktera att svenska företag kommer att gå i konkurs och vilka variabler som innehåller relevant information för detta. Metoderna som används är diskriminantanalys, logistisk regression och överlevnadsanalys på 50 aktiva och 50 företag försatta i konkurs. Resultaten visar på en träffsäkerhet mellan 67,5 % och 75 % beroende på vald statistisk metod. Oavsett vald statistisk metod är det möjligt att klassificera företag som konkursmässiga två år innan konkursens inträffande med hjälp av finansiella nyckeltal av typerna lönsamhetsmått och solvensmått. Samhällskostnader reduceras av bättre konkursprediktion med hjälp av finansiella nyckeltal vilka bidrar till ökad förmåga för företag att tillämpa ekonomistyrning med relevanta nyckeltal i form av lager, balanserad vinst, nettoresultat och rörelseresultat. / From the early 1900s, banks and lending institutions have used financial ratios as an aid in the assessment and quantification of credit risk. For today's investors the economic environment is far more complicated than 40 years ago when the technology and computerization opened up the world's markets. Credit risk assessment today requires effective analysis of quantitative data and models that can predict risks with good accuracy. During the second half of the 20th century there was a rapid development of the tools used for bankruptcy prediction. We moved from simple univariate models to complex data mining models with thousands of observations. This study investigates if it’s possible to predict bankruptcy in Swedish limited companies and which variables contain information relevant for this cause. The methods used in the study are discriminant analysis, logistic regression and survival analysis on 50 active and 50 failed companies. The results indicate accuracy between 67.5 % and 75 % depending on the choice of statistical method. Regardless of the selected statistical method used, it’s possible to classify companies as bankrupt two years before the bankruptcy occurs using financial ratios which measures profitability and solvency. Societal costs are reduced by better bankruptcy prediction using financial ratios which contribute to increasing the ability of companies to apply financial management with relevant key ratios in the form of stock , retained earnings , net income and operating income.

This study explores the financial performance measurement of South Africa's Top Companies. It aims to find a conclusion on the research problem, that is 'Do South Africa's Top Companies use the available arsenal to measure their financial performance?' Commerce and industry are the cornerstones of the economy of a country. This study purports to contribute to the ways and means of minimising the risk of business failures due to the resultant effects on the economy. The sample comprises of sixty companies. The sampling frame is the first hundred companies of the Financial Mail 200 Top Performers for 2004. The arsenal that is available to measure financial performance is researched in the financial literature. Mainly, this covers ratio analysis and interpretation, and the bankruptcy prediction models. To arrive at a conclusion on the research problem, a research instrument is developed from the host of financial ratios in the literature, including the bankruptcy prediction models. The research instrument comprises of popular ratios that are also found to be 'logical', as well as the ratios that make up the Z-Score bankruptcy prediction model. The instrument is called the Ratio Map and Z-Score and is applied to test the financial strengths/weaknesses of the Top Companies. In addition to the Ratio Map and Z-Score, the measures applied by the Top Companies as 'highlights' are analysed. This is done to determine the extent at which the measures unearth the strengths/weaknesses of the Top Companies. The conclusion drawn is that the Top Companies do not utilise the available arsenal to measure their financial performance. The supporting evidence is that the most frequently applied 'highlights' measures by the Top Companies cover only one area of the many financial fields of a company, that is, share performance. On the other hand, the analyses per Ratio Map and Z-Score have not revealed major material weaknesses in the financial position of the Top Companies. It is proposed that: ïf  More information be given in the notes to the financial statements to facilitate meaningful analysis; and ïf  A follow-up research study be done to assess the trends of the Top Companies. / Business Management / D.Comm. (Business Management)

The diploma thesis is focused on evaluating the performance of the company KOHUT Třinec s.r.o. in period from 1. 4. 2007 to 31. 3. 2011. Evaluation is made by using selected indicators of financial analysis, namely pyramidal decompositions and systems of purposefully selected indicators. The theoretical part contains the definition of basic concepts for understanding the issues examined. Based on financial analysis in the practical section are made possible suggestions to improve the current situation of the company and suggestions to remove the identified problems.

La récente crise financière qui a débuté aux États-Unis en 2007 a révélé les faiblesses du système bancaire international se traduisant par l’effondrement de nombreuses institutions financières aux États-Unis et aussi par l’augmentation de la part des prêts non performants dans les bilans des banques européennes. Dans ce cadre, nous proposons d’abord d’estimer et de tester l’efficacité des modèles de prévisions des défaillances bancaires. L’objectif étant d’établir un système d’alerte précoce (EWS) de difficultés bancaires basées sur des variables financières selon la typologie CAMEL (Capital adequacy, Asset quality, Management quality, Earnings ability, Liquidity). Dans la première étude, nous avons comparé la classification et la prédiction de l’analyse discriminante canonique (CDA) et de la régression logistique (LR) avec et sans coûts de classification en combinant ces deux modèles paramétriques avec le modèle descriptif d’analyse en composantes principales (ACP). Les résultats montrent que les modèles (LR et CDA) peuvent prédire la faillite des banques avec précision. De plus, les résultats de l’ACP montrent l’importance de la qualité des actifs, de l’adéquation des fonds propres et de la liquidité en tant qu’indicateurs des conditions financières de la banque. Nous avons aussi comparé la performance de deux méthodes non paramétriques, les arbres de classification et de régression (CART) et le nouveau modèle régression multivariée par spline adaptative (MARS), dans la prévision de la défaillance. Un modèle hybride associant ’K-means clustering’ et MARS est également testé. Nous cherchons à modéliser la relation entre dix variables financières et le défaut d’une banque américaine. L’approche comparative a mis en évidence la suprématie du modèle hybride en termes de classification. De plus, les résultats ont montré que les variables d’adéquation du capital sont les plus importantes pour la prévision de la faillite d’une banque. Enfin, nous avons étudié les facteurs déterminants des prêts non performants des banques de l’Union Européenne durant la période 2012-2015 en estimant un modèle à effets fixe sur données de panel. Selon la disponibilité des données nous avons choisi un ensemble de variables qui se réfèrent à la situation macroéconomique du pays de la banque et d’autres variables propres à chaque banque. Les résultats ont prouvé que la dette publique, les provisions pour pertes sur prêts, la marge nette d’intérêt et la rentabilité des capitaux propres affectent positivement les prêts non performants, par contre la taille de la banque et l’adéquation du capital (EQTA et CAR) ont un impact négatif sur les créances douteuses. / The recent financial crisis that began in the United States in 2007 revealed the weaknesses of the international banking system resulting in the collapse of many financial institutions in the United States and also the increase in the share of non-performing loans in the balance sheets of European banks. In this framework, we first propose to estimate and test the effectiveness of banking default forecasting models. The objective is to establish an early warning system (EWS) of banking difficulties based on financial variables according to CAMEL’s ratios (Capital adequacy, Asset quality, Management quality, Earnings ability, Liquidity). In the first study, we compared the classification and the prediction of the canonical discriminant analysis (CDA) and the logistic regression (LR) with and without classification costs by combining these two parametric models with the descriptive model of principal components analysis (PCA). The results show that the LR and the CDA can predict bank failure accurately. In addition, the results of the PCA show the importance of asset quality, capital adequacy and liquidity as indicators of the bank’s financial conditions. We also compared the performance of two non-parametric methods, the classification and regression trees (CART) and the newly multivariate adaptive regression splines (MARS) models, in the prediction of failure. A hybrid model combining ’K-means clustering’ and MARS is also tested. We seek to model the relationship between ten financial variables (CAMEL’s ratios) and the default of a US bank. The comparative approach has highlighted the supremacy of the hybrid model in terms of classification. In addition, the results showed that the capital adequacy variables are the most important for predicting the bankruptcy of a bank. Finally, we studied the determinants of non-performing loans from European Union banks during the period 2012-2015 by estimating a fixed effects model on panel data. Depending on the availability of data we have chosen a set of variables that refer to the macroeconomic situation of the country of the bank and other variables specific to each bank. The results showed that public debt, loan loss provisions, net interest margin and return on equity positively affect non performing loans, while the size of the bank and the adequacy of capital (EQTA and CAR) have a negative impact on bad debts.

Master's thesis deals with the consolidation of the financial statements. The thesis is divided into two parts. The first part focuses on the implementation of the consolidated financial statements for the Czech part of the group. The second part analyzes the performance of the consolidated financial statements and the individual companies by financial indicators. The thesis also contains proposals to improve the economic situation of the holding or individual companies.