Executive Summary

This Business Case analyzed the opportunity to expand sustainable financing operations in agribusiness through Agribusiness Receivables Certificates (CRA) linked to the Responsible Commodities Facility (RCF) model. The objective was to assess how the RCF CRA could overcome operational limitations, integrating satellite monitoring, external audits, technical eligibility criteria, and verifiable metrics, while preserving the economic viability of the financing. To this end, the causal factors limiting the program’s expansion were mapped using an Ishikawa diagram. Three strategic alternatives were evaluated, and a decision matrix indicated the most aligned one. The evaluation methodology was based on the periodic collection of operational, financial, and socio-environmental data, comparing them with an existing baseline. The analysis identified that the program’s scalability was restricted by challenges in data governance, territorial monitoring, and eligibility processes. As a result, the implementation of an integrated operational framework was recommended, focusing on the standardization of socio-environmental criteria, integration of geospatial databases, continuous monitoring, and improvement of impact reporting. The proposed solution proved to be the most suitable alternative for promoting the program’s sustainable growth, with the expectation of increasing the financed volume, reducing operational costs, expanding the monitored area under conversion-free production criteria, and strengthening institutional credibility, thereby contributing to a more sustainable agricultural financial market.

Keywords: Agribusiness; Cerrado; RCF CRA; ESG; Sustainable financing.

A copper mine in Marabá (PA) operated without a formal management process for grounding systems and SPDA (Lightning Protection System), which generated a backlog of non-conformities and threatened ISO 14001 certification, essential for revenue. The work aimed to structure a formal management model for these assets, capable of addressing the real causes of the problem. To this end, the Ishikawa Diagram was applied to identify the structural causes of non-conformities, distributing them into categories such as methods and materials. Subsequently, the GUT Matrix was used to prioritize the most critical causes, such as the absence of a management procedure and inspection plan. Five solution alternatives were evaluated using a multi-criteria decision matrix and a feasibility study. The alternative of structured and phased internal management until 2030 (Alternative 5) was recommended, obtaining the highest score (122 points), with the hybrid model serving as punctual support for external expertise in critical phases. The implementation plan envisioned five phases until 2030, including mapping and documentary sanitation, priority technical adequacy, model consolidation and expansion, and maturity. The main goal was to achieve 100% of the mapped and adequate buildings, and eliminate findings in ISO 14001 audits. It was concluded that the proposed model transformed reactive management into a proactive process, with defined responsibilities and performance indicators, ensuring regulatory compliance, technical predictability, and operational continuity of the plant.

Keywords: Grounding; Asset management; ISO 14001; Mining; SPDA.

The global pursuit of decarbonization has intensified interest in harnessing biogenic CO2, especially from corn ethanol biorefineries, which generate concentrated and still undervalued CO2. This Business Case evaluated the economic-financial viability of producing and marketing liquefied CO2 through the implementation of a capture, purification, and liquefaction unit in a corn ethanol biorefinery in Brazil. The study considered a nominal capacity of 150 t/day, analyzing the potential market, the necessary investment, operational costs, and economic results, using indicators such as Net Present Value (NPV), Internal Rate of Return (IRR), and discounted payback. The project required an estimated investment of R$ 93.4 million and potentially produced 49,875 t/year of liquefied CO2. Under the adopted assumptions, it presented an NPV of R$ 22.1 million, an IRR of 19.5% per year, a discounted payback of 10.5 years, and a break-even price of R$ 727/t. Market analysis indicated a dimension compatible with the proposed production, but highlighted the need for regional demand validation and advance contracting of a significant portion of the capacity. It was concluded that the project was economically viable, with a margin of 19.2% before the NPV reached zero, however, its attractiveness depended on the confirmation of the net selling price, the investment, and energy consumption. It was recommended to proceed to commercial validation and basic engineering, conditioning the final investment decision on the confirmation of these variables, leveraging the operational continuity of corn biorefineries to transform fermentation CO2 into a commercial product.

Keywords: Biorefinery; Liquefied CO2; Corn ethanol; Economic viability.

The conduct of monetary policy in Brazil, particularly under the inflation targeting regime, has been widely debated due to its possible impacts on inflation and economic activity. The study aimed to evaluate the effectiveness of Brazilian monetary policy, guided by the Selic rate, in controlling inflation, and to investigate its possible social costs during the period from 1999 to 2024. For this purpose, quarterly data on Gross Domestic Product (GDP), Broad Consumer Price Index (IPCA), Selic rate, and exchange rate, extracted from the Central Bank of Brazil, were used. The methodology employed a Vector Error Correction Model (VECM), preceded by stationarity and cointegration tests, and complemented by Impulse Response Function and Variance Decomposition analyses. The results indicated that inflation showed a strong inertial component, being predominantly explained by its own dynamics, while shocks in interest rates and exchange rates demonstrated a statistically limited impact on the IPCA. Additionally, it was found that GDP did not respond significantly to variations in the Selic rate, suggesting low sensitivity of economic activity to monetary policy during the analyzed period. In summary, it was concluded that monetary policy demonstrated limited effectiveness in controlling inflation, without, however, generating direct and significant social costs on Gross Domestic Product, which acts as the main driver of job creation.

Keywords: Cointegration; Econometrics; Inflationary inertia; Inflation targets; Gross Domestic Product.

The research investigated how governance mechanisms and internal controls, applied to “Legal Operations” practices, can strengthen the financial management and budgetary predictability of a legal department in a multinational company. The study aimed to diagnose critical points of the legal budget cycle, from forecasting to payment, and identify process improvements, indicators, and responsibilities between the legal and financial departments. To this end, an applied qualitative research was conducted, configured as a case study. Data collection included interviews with professionals from the legal and financial areas, documentary analysis of cost spreadsheets (2022-2024) and compliance policies, as well as mapping of the legal expenses flow. The results revealed fragilities in interdepartmental coordination, notably in the definition of cost centers and the use of budgetary control instruments. Gaps were observed in process monitoring and in the integration of information from external firms, as well as opportunities for routine automation and improvement of management indicators. Budgetary predictability was found to be impacted by exogenous factors, such as the dynamics of the Judiciary, and endogenous factors, such as the quality of information and the governance of the budget cycle. It was concluded that budgetary predictability depends on the maturity of governance applied to processes, data, and operational routines. A governance and control model for the legal budget was proposed, focusing on process standardization, strengthening monitoring, and improving decision-making, including process mapping, risk and control matrix, and performance indicators.

Keywords: Automation; Internal controls; Corporate governance; Legal Operations; Budgetary predictability.

The risk of early settlement in pre-fixed credit portfolios constituted a relevant challenge for Asset and Liability Management (ALM) in financial institutions, as it generated cash flow asymmetries and inefficiencies in hedging strategies. The work aimed to comparatively evaluate the predictive performance of traditional econometric and statistical models versus machine learning algorithms in estimating the Monthly Mortality Rate (SMM). To this end, a real database of credit operations originated between 2016 and 2025 was used, totaling approximately 500 million observations. Models such as Historical CPR, Beta Regression, Quantile Regression, Logistic Regression, Cox Proportional Hazards, and LightGBM were evaluated, with performance measured by Mean Absolute Error (MAE) and validated through temporal cross-validation with an expanded window. The results demonstrated the superiority of non-linear approaches, with the LightGBM model showing the best performance in the test period (Jan/2024 to Jul/2025), reducing MAE by 34.21% compared to the historical benchmark. Additionally, interpretability techniques based on SHAP values and survival analysis were employed to identify the contract rate spread, market rate, and bond age as the main economic determinants of prepayment. The application of the proposed model improved the accuracy of cash flow estimates and provided favorable evidence for refining the calculation of effective duration and the sizing of the institutional liquidity buffer, suggesting that more flexible models can optimize ALM management.

Keywords: Machine learning; ALM Management; Hedge; Financial modeling; Interest rate risk.

The development of iOS mobile applications can be conducted under imperative and reactive architectures, directly impacting debugging and maintenance practices. The objective was to establish the impact of architectural choice on debugging and error correction in iOS applications, evaluating the automatic detectability of failures, the traceability of reports, and the utility of logs. An experimental study was conducted, in which two functionally equivalent native applications were developed with UIKit (imperative) and SwiftUI/Combine (reactive). Four controlled error scenarios were inserted, classified as explicit crashes and silent errors. Data were collected with Firebase Crashlytics and Xcode Debugger in forty sessions, and these were analyzed by descriptive statistics and content analysis. The results revealed that, for state inconsistencies, the UIKit architecture generated immediate crashes and automatic reports, while SwiftUI suppressed the crash and produced a silent warning invisible to automatic tools. For forced unwrapping, the architecture proved irrelevant. In silent scenarios, neither architecture offered automatic observability, which highlighted the limitations of the tools. It was concluded that the reactive architecture, by abstracting state control mechanisms, reduced explicit errors but introduced silent failures with lower traceability. The architectural decision must consider the implications for production monitoring, requiring manual log instrumentation in SwiftUI/Combine projects for errors that would be automatically captured in UIKit.

Keywords: Combine; Maintainability; Observability; SwiftUI; UIKit.

Commercial management in the B2B healthcare sector faced constant challenges, requiring strategic vision and sharp attention to delivering results. The study investigated how the implementation of a CRM (Customer Relationship Management) system contributed to mitigating the loss of historical information and enhancing customer retention in the face of selling costs. A qualitative-quantitative approach of an exploratory-descriptive nature was adopted, and data were collected through a questionnaire answered by 42 professionals in the commercial area, working in the industry or in healthcare segment companies. The results revealed that, although 71.4% of respondents used computerized CRM, organizational culture imposed strong resistance, confirmed by 57.1% of professionals who relied on manual methods, such as diaries and isolated spreadsheets, for data recording and retention. A gap in training was also evident, as 24.4% of respondents rarely or never received specific training. The research inferred that the underreporting of data was not solely due to a lack of technology or technological failure, but to a deficiency in the strategic management of people and processes. The vision of the need for integrated management to generate competitive intelligence and sales predictability was reinforced, and attention was drawn to the need for more frequent training and development. Mitigating the cost of selling and enhancing customer retention depend on consistent integration between human capital and technology, generating managerial assets to increase commercial production and strategic data retention.

Keywords: Training; Sales strategy; Customer management; Strategic management; Commercial intelligence.

The growing complexity of technology projects demanded approaches capable of balancing control, efficiency, and adaptability to constant changes, as traditional management models showed limitations in dynamic environments. Technology project management was evaluated before the implementation of an agile method, improvements based on iterative practices were proposed, and post-implementation performance was reassessed, seeking to identify gains in operational efficiency and adaptability throughout the project lifecycle. The research employed a descriptive case study, with a qualitative approach, in two technology sector companies. Data were collected through structured questionnaires applied before and after the intervention, complemented by documentary analysis and systematic observation over ninety days of solution application. The results showed consistent improvement in planning flexibility, greater alignment with client needs, increased delivery predictability, and enhanced team productivity. A productivity gain was the most expressive indicator, with 85.7% total agreement on the improvement of team performance after adopting the *framework*. It was concluded that the structured implementation of the method improved the management of the analyzed projects, reinforcing the capacity to respond to changes and promoting greater business value generation.

Keywords: Organizational adaptation; Incremental delivery; Agile management; Iterative planning; Team productivity.

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