Inadequate Insurance Claims Reserving and Financial Distress in Non-Life Insurance Companies in Kenya: A Structural Equation Modeling Approach

Financial distress (FD) is a common occurrence in Kenyan commercial sector and is not lacking in non-life insurance companies in Kenya. Several insurance companies have been placed under statutory management for failure to pay genuine claims and other creditors. Insurance companies provide unique financial services, not only to individuals but also to the growth and development of the economy; giving employment to workers and dividends to investors. Financial distress places insurable properties and businesses at risk thus reducing the general public confidence in the insurance sector. For this paper, the goal was to investigate whether inadequate reserving of claims (IRC) causes financial distress in non-life insurance companies in Kenya. In accounting for insurance claims reserves, increases in reserves mean a reduction of profitability of an insurer, whereas a decrease in reserves increases the profitability resulting in higher taxation and payment of dividends, which drains the insurer’s cash flow, thus causing financial distress. Out of 37 non-life insurance companies, registered in 2018 in Kenya, four insurers were subjected to Pilot Testing and another four companies declined to participate in the survey. Secondary data from Insurance Regulatory Authority website was retrieved for calculations of Z-scores as per Altman (1993), amended formula. Primary data was also collected through a questionnaire. A partial least squares Structural Equation Modelling (PLS-SEM) was employed to assess the mediating effect of Insurance Regulatory Association (IRA) supervision on the association between inadequate reserving of claims and financial distress. Goodness-of-fit (GoF) indices were used to assess the model’s goodness of fit. By using the discriminative Z-score formula, 52% of the institutions considered in 2018 were financially distressed, compared to 48% in 2017. However, when considering the average of ten years (2009 to 2018), financially distressed..............Keywords: Non-life  insurance  companies,  Policyholders,  Insurance  Regulatory  Authority,  Claims Reserving, Z-Scores, Structural Equation Modelling DOI: 10.7176/RJFA/12-12-06 Publication date:June 30th 2021

Loan Portfolio Risk and Capital Adequacy: A New Approach to Evaluating the Riskiness of Banks

We develop a Loan Portfolio Risk (LPR) variable that measures time-varying volatility in default risk for a portfolio of bank loans. An Equity-to-LPR ratio (ELPR) is incrementally important in predicting bank failure up to five years in advance, even after controlling for all the CAMELS variables. Publicly-listed banks with higher ELPR have lower market implied costs-of-capital. ELPR also strongly predicts cross-sectional stock returns under stress conditions. During the financial crisis (7/2007-6/2011), a cash-neutral strategy that longs high-ELPR and shorts low-ELPR banks yields a monthly alpha of 3.3% to 4.2%. We conclude LPR captures key aspects of bank risk missed by a risk-weighted-asset approach

The dynamic prediction of company failure - the influence of time, the economy and non-linearity

Dynamic forecasts of financial distress have received far less attention than static forecasts, particularly in Australia. This thesis, therefore, investigates dynamic probability forecasts for Australian firms. Novel features of the modelling are the use of time-varying variables in forecasts from a Cox model and allowing for nonlinearity between financial distress and predictor variables. Cox regression models with time-varying variables are used to estimate the survival probabilities of a large sample of Australian listed companies. Not only is this one of relatively few studies to apply dynamic variables in forecasting financial distress, but to the author’s knowledge it is the first to provide forecasts of survival probabilities using the Cox model with time-varying variables. Forecast accuracy is evaluated using receiver operating characteristics curves and the Brier Score. It was found that the models had predictive power in out-of-sample forecast. Allowing for non-linearity between the predictor variables and financial distress risk substantially improved out-of-sample accuracy in discriminating between distressed and nondistressed firms. However, variables capturing the state of the economy did not substantively improve the predictive power of the model

Essays on Roles of Directors in Corporate Governance

The three chapters in the thesis provide some innovative explanations and perspectives regarding the role of directors, particularly, independent directors in a transaction market – China and in a developed market- UK. In “Auditor Change and Corporate Governance: Audit Committee Reputation”, I provide a new empirical evidence that reputation is a strong incentive to independent directors to work diligently. I select audit committee in the UK as the study object because their roles on board are well-defined and the reputation cost for audit committee member is larger than that for other directors. Firstly, this chapter shows that the probability of auditor change increases with the proportion of reputable members. Second, reputable members tend to switch an auditor which offers a high audit quality, measured by better brand-name, bigger size, and higher independence. This chapter further shows that the reduce discretionary accruals, a proxy for earnings management, only follows an audit change driven/approved by the audit committee, rather than involuntary auditor change (market shock). In “CEO Dismissal, Compensation and Topics of Board Meetings: The Case of China”, I provide a better understanding of how board activity affects board effectiveness in linking CEO compensation/dismissal to firm performance. There are six major topics discussed in board meetings. Our results show that turnover-performance sensitivity is weaker when there is a higher frequency of board meetings discussing the nomination of directors and top management. Moreover, the link between CEO compensation and firm performance is enhanced only when directors meet more often to discuss growth strategies for the use of IPO proceeds, investment and acquisitions. These sensitivities are not influenced by meeting frequency of other topics. It also sheds lights on how board monitoring of different decisions at board meetings modifies the connection between CEO interests and firm performance, then affect the quality of corporate governance. In “The Hidden Information Content: Evidence from the Tone of Independent Director Reports”, I utilise a Naïve Bayesian machine learning algorithm combining with the Chinese word segmentation to inspect the information content (the tone) of independent director report, a unique disclosure of independent director. This chapter firstly examines the determinants of a report tone, firms with younger independent directors, more directors with accounting expertise, more board committees, more board meetings, less leverage, and controlled by private shareholders tend to have more positive IDRs. The chapter further tests whether the tone in the report has predicted power to the future performance given that the tone of reports is based on director’s overall satisfactions of the firm. The average tone of the IDRs is positively associated with future firm performance after controlling other factors that influence firm performance. Moreover, the negative tone of IDRs is negatively correlated with firm performance for firms with greater monitoring necessities

The detection of fraudulent financial statements using textual and financial data

Das Vertrauen in die Korrektheit veröffentlichter Jahresabschlüsse bildet ein Fundament für funktionierende Kapitalmärkte. Prominente Bilanzskandale erschüttern immer wieder das Vertrauen der Marktteilnehmer in die Glaubwürdigkeit der veröffentlichten Informationen und führen dadurch zu einer ineffizienten Ressourcenallokation. Zuverlässige, automatisierte Betrugserkennungssysteme, die auf öffentlich zugänglichen Daten basieren, können dazu beitragen, die Prüfungsressourcen effizienter zuzuweisen und stärken die Resilienz der Kapitalmärkte indem Marktteilnehmer stärker vor Bilanzbetrug geschützt werden. In dieser Studie steht die Entwicklung eines Betrugserkennungsmodells im Vordergrund, welches aus textuelle und numerische Bestandteile von Jahresabschlüssen typische Muster für betrügerische Manipulationen extrahiert und diese in einem umfangreichen Aufdeckungsmodell vereint. Die Untersuchung stützt sich dabei auf einen umfassenden methodischen Ansatz, welcher wichtige Probleme und Fragestellungen im Prozess der Erstellung, Erweiterung und Testung der Modelle aufgreift. Die Analyse der textuellen Bestandteile der Jahresabschlüsse wird dabei auf Basis von Mehrwortphrasen durchgeführt, einschließlich einer umfassenden Sprachstandardisierung, um erzählerische Besonderheiten und Kontext besser verarbeiten zu können. Weiterhin wird die Musterextraktion um erfolgreiche Finanzprädiktoren aus den Rechenwerken wie Bilanz oder Gewinn- und Verlustrechnung angereichert und somit der Jahresabschluss in seiner Breite erfasst und möglichst viele Hinweise identifiziert. Die Ergebnisse deuten auf eine zuverlässige und robuste Erkennungsleistung über einen Zeitraum von 15 Jahren hin. Darüber hinaus implizieren die Ergebnisse, dass textbasierte Prädiktoren den Finanzkennzahlen überlegen sind und eine Kombination aus beiden erforderlich ist, um die bestmöglichen Ergebnisse zu erzielen. Außerdem zeigen textbasierte Prädiktoren im Laufe der Zeit eine starke Variation, was die Wichtigkeit einer regelmäßigen Aktualisierung der Modelle unterstreicht. Die insgesamt erzielte Erkennungsleistung konnte sich im Durchschnitt gegen vergleichbare Ansätze durchsetzen.Fraudulent financial statements inhibit markets allocating resources efficiently and induce considerable economic cost. Therefore, market participants strive to identify fraudulent financial statements. Reliable automated fraud detection systems based on publically available data may help to allocate audit resources more effectively. This study examines how quantitative data (financials) and corporate narratives, both can be used to identify accounting fraud (proxied by SEC’s AAERs). Thereby, the detection models are based upon a sound foundation from fraud theory, highlighting how accounting fraud is carried out and discussing the causes for companies to engage in fraudulent alteration of financial records. The study relies on a comprehensive methodological approach to create the detection model. Therefore, the design process is divided into eight design and three enhancing questions, shedding light onto important issues during model creation, improving and testing. The corporate narratives are analysed using multi-word phrases, including an extensive language standardisation that allows to capture narrative peculiarities more precisely and partly address context. The narrative clues are enriched by successful predictors from company financials found in previous studies. The results indicate a reliable and robust detection performance over a timeframe of 15 years. Furthermore, they suggest that text-based predictors are superior to financial ratios and a combination of both is required to achieve the best results possible. Moreover, it is found that text-based predictors vary considerably over time, which shows the importance of updating fraud detection systems frequently. The achieved detection performance was slightly higher on average than for comparable approaches

Mitigating the pro-cyclicality of Basel II

Policy discussions on the recent financial crisis feature widespread calls to address the pro-cyclicaleffects of regulation. The main concern is that the new risk-sensitive bank capital regulation (Basel II) may amplify business cycle fluctuations. This paper compares the leading alternative procedures that have been proposed to mitigate this problem. We estimate a model of the probabilities of default (PDs) of Spanish firms during the period 1987 2008, and use the estimated PDs to compute the corresponding series of Basel II capital requirements per unit of loans. These requirements move significantly along the business cycle, ranging from 7.6% (in 2006) to 11.9% (in 1993). The comparison of the different procedures is based on the criterion of minimizing the root mean square deviations of each adjusted series with respect to the Hodrick-Prescott trend of the original series. The results show that the best procedures are either to smooth the input of the Basel II formula by using through the cycle PDs or to smooth the output with a multiplier based on GDP growth. Our discussion concludes that the latter is better in terms of simplicity, transparency, and consistency with banks’ risk pricing and risk management systems. For the portfolio of Spanish commercial and industrial loans and a 45% loss given default (LGD), the multiplier would amount to a 6.5% surcharge for each standard deviation in GDP growth. The surcharge would be significantly higher with cyclically-varying LGD

Machine Learning-Driven Decision Making based on Financial Time Series

L'abstract è presente nell'allegato / the abstract is in the attachmen

Essays on the New Blockchain-Based Digital Financial Market : Risks and Opportunities

This doctoral thesis consists of five original essays on the risks and opportunities of the new blockchain-based digital financial market. The purpose of this dissertation is to analyze, identify, and, if possible, predict some of the major risks in the market for blockchain-based digital assets. It analyzes how crypto-specific characteristics are associated with solvency risk, sustainability risk, seclusion risk, and sentiment risk. On top of that, it also sheds light on the opportunity side of this financial innovation. The first essay of this dissertation specifically focuses on cryptocurrency for solvency risks. To forecast potential cryptocurrency default at an early stage, this study focuses on variables that are part of the information set of the investor 1 month at most after the start of trading for a cryptocurrency. The results of this research show that bankruptcies among cryptocurrencies are predictable. The second essay explores energy risk as a fundamental market-driving force for the pricing of cryptocurrency. Cryptocurrencies using a high-energy-consumption consensus protocol are riskier than others because their mining costs are more exposed to changes in energy price. Surprisingly, the study finds that energy consumption does not seem to play a role in pricing cryptocurrency. The third essay hypothesizes that privacy coins form a distinct submarket in the cryptocurrency market, shedding light on seclusion risk. It shows that privacy coins and non-privacy coins are two distinct asset markets within the cryptocurrency market. The fourth essay is about news media sentiment risk. It explores whether news media sentiments have an impact on Bitcoin volatility. It also differentiates financial sentiment and psychological sentiment and finds that financially optimistic investors are driving the Bitcoin market. On the other hand, the fifth essay in this dissertation analyzes opportunities, especially the funding opportunity in the widely known category of new digital assets defined as crypto tokens. It analyzes the determinants of the success of initial coin offerings and finds that initial-coin-offering investors are largely guided by their emotions when making investment decisions. Surprisingly, regulatory framework has not yet become a priority among policymakers. Therefore, this doctoral dissertation not only facilitates future research, but also helps regulators in shaping the future of blockchain-based financial technologies.Tämä väitöskirja koostuu viidestä esseestä, jotka käsittelevät uuden lohkoketjupohjaisen digitaalisen rahoitusmarkkinan riskejä ja mahdollisuuksia. Väitöskirjan tarkoituksena on analysoida, tunnistaa ja mahdollisuuksien mukaan ennustaa joitakin lohkoketjupohjaisten digitaalisten varojen markkinoiden suurimpia riskejä. Siinä analysoidaan, miten kryptovaluuttakohtaiset ominaisuudet liittyvät vakavaraisuusriskiin, kestävyysriskiin, eristäytymisriskiin ja sentimenttiriskiin. Tämän lisäksi se valottaa myös tämän rahoitusinnovaation mahdollisuuksia. Tämän väitöskirjan ensimmäisessä esseessä keskitytään erityisesti kryptovaluuttaan maksukyvyttömyysriskinä. Tässä tutkimuksessa keskitytään muuttujiin, jotka ovat sijoittajan saatavilla korkeintaan 1 kuukausi sen jälkeen, kun kaupankäynti kryptovaluutalla on alkanut. Tämän tutkimuksen tulokset osoittavat, että kryptovaluuttojen konkurssit ovat ennustettavissa. Toisessa esseessä tutkitaan energiariskiä markkinoita ohjaavana voimana kryptovaluutan hinnoittelussa. Kryptovaluutat, jotka käyttävät paljon energiaa kuluttavaa konsensusprotokollaa, ovat muita riskialttiimpia, koska niiden louhintakustannukset ovat alttiimpia energian hinnan muutoksille. Yllättäen tutkimuksessa todetaan, että energiankulutuksella ei näytä olevan merkitystä kryptovaluuttojen hinnoittelussa. Kolmannessa esseessä hypoteesina on, että yksityisyyskolikot muodostavat erillisen alamarkkinan kryptovaluuttamarkkinoilla, ja tutkimus tarkastelee näiden eristäytymisriskiä. Siinä osoitetaan, että yksityisyyskolikot ja ei-yksityisyyskolikot ovat kaksi erillistä omaisuuserämarkkinaa kryptovaluuttamarkkinoilla. Neljäs essee käsittelee uutismedian sentimenttiriskiä. Siinä tutkitaan, vaikuttaako uutismedian sentimentti Bitcoinin volatiliteettiin. Siinä myös erotetaan toisistaan taloudellinen sentimentti ja psykologinen sentimentti ja todetaan, että taloudellisesti optimistiset sijoittajat ohjaavat Bitcoin-markkinoita. Väitöskirjan viidennessä esseessä analysoidaan mahdollisuuksia, erityisesti rahoitusmahdollisuuksi, liittyen laajalti tunnettuihin digitaalisiin tokeneihin. Siinä havaitaan, että näihin omaisuuseriin sijoittavat sijoittajat toimivat pitkälti tunteidensa ohjaamina sijoituspäätöksiä tehdessään. Yllättävää kyllä, sääntelykehyksestä ei ole vielä tullut poliittisten päättäjien prioriteettia. Siksi tämä väitöskirja ei ainoastaan tue tulevaa tutkimusta, vaan auttaa myös viranomaisia lohkoketjupohjaisten rahoitusteknologioiden tulevaisuuden määrittelyssä.fi=vertaisarvioitu|en=peerReviewed