Informe Financiero del Director e Informe del Auditor Externo. 1 de enero del 2023 – 31 de diciembre del 2023

Esta publicación presenta el Informe Financiero de la Organización Panamericana de la Salud (OPS) correspondiente al 2023. Certificados y aprobados para su publicación por el Director de la Organización, los estados financieros se han elaborado siguiendo el principio contable de devengo, de conformidad con las Normas Internacionales de Contabilidad del Sector Público. Además de los estados financieros y sus notas, el informe conƟene un análisis del rendimiento financiero de la OPS en el 2023. Las secciones sobre ingresos, contribuciones voluntarias, compras, gastos, situación financiera, reservas, inversiones, divisas y pasivos por prestaciones al personal van acompañadas de cifras y cuadros. Sin embargo, este informe va más allá de la información financiera para destacar también algunos logros de la Organización en el 2023. Estos logros se relacionan con los esfuerzos conƟnuos de la OPS por encabezar iniciaƟvas innovadoras en la Región de las Américas para llevar a una mayor escala las acciones en el ámbito de la salud y su labor para ayudar a los países a proteger los logros en materia de salud pública, recuperarse mejor del impacto de la pandemia de COVID-19 y construir para fortalecerse. En el 2023, la OPS también procuró fomentar el compromiso, facilitar la cooperación, aclarar soluciones y centrar los esfuerzos en reducir las brechas de desigualdad en la Región. Los logros seleccionados se refieren, por ejemplo, a los esfuerzos de la OPS para fortalecer la atención primaria de salud, ayudar a responder a las emergencias de salud y los desastres, aumentar la resiliencia y la preparación de los sistemas de salud, abordar las enfermedades transmisibles prevenibles, hacer frente a la creciente carga de enfermedades no transmisibles, izar la bandera de la salud mental, recuperar las tasas de vacunación y acelerar la transformación digital de la salud pública. También se hace referencia a la labor constante por agilizar los sistemas y procesos internos al poner en marcha la iniciaƟva OPS Adelante.

Do the unusual resignations of independent directors affect auditors' professional judgment?

In Kangmei's first trial judgment, where the independent directors faced significant joint and several liabilities, it triggered a "wave" of resignations among independent directors of listed companies. Auditors auditing financial reports of these companies might consider this a significant signal, raising the question: does this signal influence their professional judgment? The study examines the relationship between the resignation of independent directors and auditors' professional judgment in A-share listed companies, following Kangmei's initial trial. This examination is conducted across three dimensions: audit pricing, audit input, and audit opinion.The findings indicate that the unusual resignations of independent directors prompt uditors to pay increased attention to the risk of material misstatements by clients, primarily reflected in audit pricing. However, these resignations do not significantly impact audit input or the judgment of audit opinions. Furthermore, this research enriches the existing literature on audit pricing and the role of independent directors, while also unveiling the specific pathways through which the departure of independent directors impacts auditors' professional judgment.

Financial Report of the Director and Report of the External Auditor. 1 January – 1 December 2023

This publication presents the Financial Report of the Pan American Health Organization (PAHO) for 2023. Certified and approved for publication by the Director of the Organization, the financial statements have been prepared on the accrual basis of accounting in accordance with the International Public Sector Accounting Standards. In addition to the financial statements and notes thereto, the report presents an analysis of PAHO’s financial performance in 2023. Sections on revenue, voluntary contributions, procurement, expenses, financial position, reserves, investments, foreign exchange, and employee liabilities are accompanied by figures and tables. However, this report goes beyond the financial information to also highlight selected achievements of the Organization in 2023. These achievements relate to PAHO’s ongoing efforts to spearhead innovative initiatives in the Region of the Americas to scale up health action and its work to help countries to protect public health gains, recover better from the impact of the COVID-19 pandemic, and build stronger. In 2023, PAHO also sought to foster commitment, enable cooperation, shed light on solutions, and focus efforts on reducing inequality gaps across the Region. The selected achievements concern, for example, PAHO’s efforts to strengthen primary health care, help respond to health emergencies and disasters, increase health system resilience and preparedness, tackle preventable communicable diseases, address the growing burden of noncommunicable diseases, raise the flag for mental health, bring immunization rates back on track, and accelerate the digital transformation of public health. Also mentioned is the ongoing work to streamline internal systems and processes through the initiation of PAHO Forward.

The effect of auditor's cooperation with independent financial advisors on the reliability of performance commitment-Based on the moderating effect of managerial overconfidence.

Based on the sample of major asset restructuring transactions of Shanghai and Shenzhen A-share listed companies from 2009 to 2018, this paper uses Logit model to examine the impact of auditors ' cooperation experience with independent financial advisors on the reliability of performance commitments, and to examine the moderating effect of management overconfidence on the relationship between the two. The results show that the cooperation experience between auditors and independent financial advisors is significantly positively correlated with the reliability of performance commitment, and the closer the cooperation experience is, the easier the performance commitment will be realized, this has played a financial intermediary team effect. Further analysis shows that in the context of management overconfidence, the positive relationship between financial intermediaries ' cooperation experience and the reliability of performance commitment is stronger. The research results enrich the research on the influencing factors of M & A performance commitment and the economic consequences of financial intermediaries ' cooperation, and help the transaction subjects to rationally view performance commitment and regulators to improve policies and regulations.

Виконання бюджету у сфері охорони здоров’я: тематичне дослідження: Україна: серія аналітичних записок.

Цей звіт був підготовлений на початку 2022 року і, отже, є узагальненою картиною виконання бюджету України, як це було напередодні початку війни. Знадобляться роки, щоб належним чином врахувати вплив війни на системи та процеси виконання бюджету на охорону здоров’я та оцінити, наскільки стійкими вони будуть після цього жахливого потрясіння. Однак швидкий моніторинг діяльності уряду через чотири місяці в нових реаліях дає обнадійливі сигнали про те, що багато, якщо не більшість інституційних рамок, про які йдеться в цьому звіті, є міцними й повністю функціональними.

Budget execution in health: case study: Ukraine. Health policy papers series

This report was finalized in early 2022 and is therefore a snapshot of Ukraine’s budget execution as it was just before the start of the war. It will take years to duly account for the impact of the war on the systems and processes of health budget implementation, and to assess how resiliently they will have emerged from this horrendous disruption. However, rapid monitoring of the government’s activities four months into the new reality is giving encouraging signals that much if not most of the institutional framework discussed in this report is holding strong and is fully functional.

Intelligent Financial Auditing Model Based on Deep Learning.

The entire auditing process is complicated and tedious and requires a lot of human resources. Therefore, the intelligent development of auditing is the general trend. In order to improve the audit quality, this paper establishes an intelligent financial audit model that can predict the audit opinion of the consolidated financial statements. This paper proposes an audit opinion prediction model based on the fusion of deep belief neural network (DBN) and long-short term memory (LSTM). First, an indicator system is established for audit opinions, and multiple financial parameters are used to describe possible audit opinions. On this basis, a DBN network is designed to complete deep feature extraction and used for LSTM training. According to the prediction model obtained by training, the subsequent audit opinion can be scientifically predicted. In the experiment, the method in this paper is tested based on financial audit related data sets and compared with the prediction results of traditional multilayer perceptron (MLP), convolutional neural network (CNN), and LSTM models. The results verify the validity and reliability of the model in this paper.

Does Signing Auditor's Reputational Promotion Ease the Financing Constraints of Audited Firms?

Based on the senior certified public accountants selected by the Chinese Institute of Certified Public Accountants and data drawn from China's A-share listed companies from 2014 to 2019, this study studies the influence mechanism of signing auditors' personal reputational promotion on corporate financing constraints. The results show that the improved reputation of signing auditors will help ease the financing constraints faced by companies. Moreover, compared with that of signing auditors from Big Four accounting firms, the improved reputation of signing auditors from non-Big Four firms has a more significant effect on alleviating the financing constraints of enterprises. In addition, private enterprises and small and medium-sized enterprises face more severe financing constraints than state-owned enterprises and large enterprises, and the reputational promotion of signing auditors can better alleviate the financing constraints of the former two types of enterprises. The research conclusions provide theoretical and data-driven support for constructing audit reputation mechanisms in China and improving the financing capabilities of enterprises.

Bayesian inference of local government audit outcomes.

The scandals in publicly listed companies have highlighted the large losses that can result from financial statement fraud and weak corporate governance. Machine learning techniques have been applied to automatically detect financial statement fraud with great success. This work presents the first application of a Bayesian inference approach to the problem of predicting the audit outcomes of financial statements of local government entities using financial ratios. Bayesian logistic regression (BLR) with automatic relevance determination (BLR-ARD) is applied to predict audit outcomes. The benefit of using BLR-ARD, instead of BLR without ARD, is that it allows one to automatically determine which input features are the most relevant for the task at hand, which is a critical aspect to consider when designing decision support systems. This work presents the first implementation of BLR-ARD trained with Separable Shadow Hamiltonian Hybrid Monte Carlo, No-U-Turn sampler, Metropolis Adjusted Langevin Algorithm and Metropolis-Hasting algorithms. Unlike the Gibbs sampling procedure that is typically employed in sampling from ARD models, in this work we jointly sample the parameters and the hyperparameters by putting a log normal prior on the hyperparameters. The analysis also shows that the repairs and maintenance as a percentage of total assets ratio, current ratio, debt to total operating revenue, net operating surplus margin and capital cost to total operating expenditure ratio are the important features when predicting local government audit outcomes using financial ratios. These results could be of use for auditors as focusing on these ratios could potentially speed up the detection of fraudulent behaviour in municipal entities, and improve the speed and quality of the overall audit.

Audit Data Analysis and Application Based on Correlation Analysis Algorithm.

Traditional audit data analysis algorithms have many shortcomings, such as the lack of means to mine the hidden audit clues behind the data, the difficulty of finding increasingly hidden cheating techniques caused by the electronic and networked environment, and the inability to solve the quality defects of the audited data. Correlation analysis algorithm in data mining technology is an effective means to obtain knowledge from massive data, which can complete, muffle, clean, and reduce defective data and then can analyze massive data and obtain audit trails under the guidance of expert experience or analysts. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounds the research status and significance of audit data analysis and application; elaborates the development background, current status, and future challenges of correlation analysis algorithm; introduces the methods and principles of data model and its conversion and audit model construction; conducts audit data collection and cleaning; implements audit data preprocessing and its algorithm description; performs audit data analysis based on correlation analysis algorithm; analyzes the hidden node activation value and audit rule extraction in correlation analysis algorithm; proposes the application of audit data based on correlation analysis algorithm; discusses the relationship between audit data quality and audit risk; and finally compares different data mining algorithms in audit data analysis. The findings demonstrate that by analyzing association rules, the correlation analysis algorithm can determine the significance of a huge quantity of audit data and characterise the degree to which linked events would occur concurrently or sequentially in a probabilistic manner. The correlation analysis algorithm first inputs the collected audit data through preprocessing module to filter out useless data and then organizes the obtained data into a format that can be recognized by data mining algorithm and executes the correlation analysis algorithm on the sorted data; finally, the obtained hidden data is divided into normal data and suspicious data by comparing it with the pattern in the rule base. The algorithm can conduct in-depth analysis and research on the company's accounting vouchers, account books, and a large number of financial accounting data and other data of various natures in the company's accounting vouchers; reveal its original characteristics and internal connections; and turn it into an audit. People need more direct and useful information. The study results of this paper provide a reference for further researches on audit data analysis and application based on correlation analysis algorithm.