Financial Model Research Articles

Data-driven financial models for sustainable SME growth: Integrating green finance into small and medium enterprise strategies

In recent years, the increasing urgency to address climate change and environmental degradation has prompted a shift towards sustainable business practices, particularly within the realm of small and medium enterprises (SMEs). This paper explores the integration of green finance into the strategic frameworks of SMEs, examining how financial instruments and funding mechanisms can support environmentally sustainable practices while fostering economic growth. By assessing the current landscape of green finance, including green loans, bonds, and impact investing, the study identifies barriers SMEs face in accessing these resources. It highlights successful case studies where SMEs have effectively utilized green finance to implement energy-efficient technologies, sustainable supply chains, and eco-friendly product innovations. Furthermore, the paper proposes a strategic model for SMEs to incorporate green finance into their operations, emphasizing the importance of aligning with sustainability goals, enhancing stakeholder engagement, and leveraging partnerships with financial institutions. The findings underscore that integrating green finance not only contributes to environmental sustainability but also enhances the competitive advantage and resilience of SMEs in an evolving market landscape.

The Future Healthy Countdown 2030 consensus statement: core policy actions and measures to achieve improvements in the health and wellbeing of children, young people and future generations.

This consensus statement recommends eight high-level trackable policy actions most likely to significantly improve health and wellbeing for children and young people by 2030. These policy actions include an overarching policy action and span seven interconnected domains that need to be adequately resourced for every young person to thrive: Material basics; Valued, loved and safe; Positive sense of identity and culture; Learning and employment pathways; Healthy; Participating; and Environments and sustainable futures. Provide financial support to invest in families with young children and address poverty and material deprivation in the first 2000 days of life. Establish a national investment fund to provide sustained, culturally relevant, maternal and child health and development home visiting services for the first 2000 days of life for all children facing structural disadvantage and/or adversity. Implement a dedicated funding model for Aboriginal and Torres Strait Islander community-controlled early years services across the country to ensure these services are fully resourced to provide quality early learning and integrated services grounded in culture and community. Properly fund public schools, starting by providing full and accountable Schooling Resource Standard funding for all schools, with immediate effect for schools in communities facing structural disadvantage. Establish legislation and regulation to protect children and young people aged under 18 years from the marketing of unhealthy and harmful products. Amend the electoral act to extend the compulsory voting age to 16 years. Legislate an immediate end to all new fossil fuel projects in Australia. Establish a federal Future Generations Commission with legislated powers to protect the interests of future generations. Together, these achievable evidence-based policies would significantly improve children and young people's health and wellbeing by 2030, build a strong foundation for future generations, and provide co-benefits for all generations and society.

How can manufacturers identify the conditions for financially viable product-as-a-service?

IntroductionWith the much-needed transformation from linear to more circular resource flows, it is imperative for enterprises to understand their financial prospects. Transforming towards Product-as-a-Service (PaaS) with circular elements introduces new considerations that must be addressed to ensure profitability and sustainability. However, there is a lack of comprehensive financial assessments based on empirical cases to guide companies in assessing the lucrativeness of their transformations. This paper addresses this gap by proposing a simple-to-use and flexible financial assessment model for PaaS, helping practitioners identify the conditions necessary for financial viability from both provider and user perspectives.MethodsGrounded in transdisciplinary research, this study focuses on a construction machine manufacturer's transformation from a traditional one-off sales business model to PaaS. The transformation is analysed through the development of a life cycle costing financial assessment model that addresses relevant cost drivers.ResultsUsing discounting methods, the model can help practitioners generate scenarios to identify feasible solutions for profitable PaaS setups. Additionally, the paper presents an analytical procedure to identify conditions for a financially viable PaaS. The procedure includes scenario-based analysis that accounts for systemic changes often necessary for successfully realising PaaS.DiscussionBy following the proposed procedure, along with the financial assessment model, manufacturers can streamline their financial assessments to identify necessary changes. For the analysed case company, the modelling results indicate that it must redesign its products for PaaS to outperform its previous business model.

Financial toxicity of total cancer care immunotherapy patients and caregivers: impacts of COVID-19 pandemic and inflation.

Financial toxicity, cancer-treatment-related financial harm, is associated with expensive treatments like immunotherapy. The purpose of this study was to explore financial toxicity among advanced cancer patients receiving immunotherapies and their caregivers and, secondarily, to study how recent inflation and the COVID-19 pandemic impacted these experiences. Advanced cancer patients receiving immunotherapies and their caregivers were recruited to participate in semi-structured interviews about supportive care needs from 2022 to 2023. The Comprehensive Score for Financial Toxicity was collected. Guided by Jones et al.'s cancer financial toxicity model, the content analysis was conducted by two trained coders using NVIVO R1. Sixteen patients and 10 caregivers (including 7 dyads) across 5 states participated in interviews in 2022-2023. Participants averaged 63.43years (SD = 12.75), and patients received an average of 14.6months of immunotherapy (SD = 9.415). The majority lived in non-metropolitan areas (67%) and were white (95%). Three theory-driven themes were developed: (1) Sources of Financial Toxicity, (2) Buffers of Financial Toxicity, and (3) Consequences of Financial Toxicity. Inflation was added to financial toxicity for non-metropolitan dwelling participants due to increased prices of gas and accommodation. Social support systems buffered the impact of financial toxicity. Material and psychological impacts of financial toxicity disproportionately affected younger and privately insured participants. While immunotherapy patients face high medical costs of treatment, the burdens of accessing treatment for people living at a distance from the cancer center can exacerbate financial toxicity. Clinicians and researchers should also consider external financial pressures such as national economic impacts that compound the financial toxicity of treatment.

Genomic Surveillance of Foodborne Pathogens: Advances and Obstacles

Context: The genomic surveillance of foodborne pathogens in the United States has grown exponentially in the past decade, grounded in a powerful combination of novel sequencing technologies, bioinformatic approaches, data-sharing networks, and metadata harmonization efforts. This practice report examines recent advances in genomic epidemiology as applied to food safety programs and delineates State, Tribal, Local, and Territorial infrastructure necessary for continued life-saving improvements in public health. Program: National databases of foodborne pathogen genomes, along with data sharing and evaluation networks such as GenomeTrakr and PulseNet, have transformed how connections are made among isolates and how root causes of outbreaks are determined, allowing much more timely interventions to protect public health. Freely available bioinformatics tools such as GalaxyTrakr and the National Center for Biotechnology Information Pathogen Detection database have allowed laboratories with limited local computing resources to participate in surveillance efforts and contribute to traceback investigations. Implementation: In this report, we describe advances in genomic epidemiology that have occurred over the past decade and examine obstacles to fully implementing this technology within State, Tribal, Local, and Territorial public health systems. Evaluation: Despite a clear return on investment from governmental expenditures on genomic surveillance of foodborne pathogens, we identify significant obstacles to further sustained progress. These obstacles include workforce gaps, ineffective data sharing, and lack of constitutive and sustained funding. Discussion: Many public health laboratories face major obstacles to widespread and routine adoption of genomic surveillance technologies. While whole genome sequencing has become an integral part of routine public health microbiology, the seamless integration of these protocols into the existing practices, laboratory workflows, and information systems remains challenging. Centralized efforts to address these issues include (1) support through the Food and Drug Administration Laboratory Flexible Funding Model, (2) training and proficiency assessments, (3) open-source, standardized protocols for collecting high-quality genomic data, and (4) open access informatics software.

Next generation tissue biobanking: quality assured, financed, and integrated?

Biobanks are essential for biomedical research, particularly in the era of personalized medicine. In Germany, 36biobanks have been established over the past decade that are connected under the German Biobank Alliance (GBA). These biobanks store high-quality biological samples along with clinical data to support research projects. Biobanks can be integrated, handling both tissue and liquid samples, or set up as separate entities depending on specific requirements.Tissue biobanking is especially complex due to the invasive nature of tissue collection and the non-replicability of the samples. Close collaboration between clinics, pathologists, IT specialists, and biobank managers is crucial to ensure the quality of samples and promote interdisciplinary research.The integration of pathology and biobanking is key, both organizationally and technically. Shared IT systems, standardized protocols, and collaborative governance structures are vital for efficient data management. Quality assurance, ethical guidelines, and data protection are critical to maintaining public trust and legal compliance.Long-term financial models are needed to ensure the sustainability of biobanks. The GBA supports emerging biobanks through its "Starterkit" initiative, offering guidance and best practices to help new biobanks develop.Tissue biobanks are indispensable for advancing the understanding of diseases and developing new therapies. However, they must adhere to strict ethical and legal standards to maximize their scientific and societal value.

Keep Title IX compliance in mind when revenue‐sharing with student‐athletes

The NCAA, together with the Power Conferences, settled a series of federal antitrust lawsuits this past May by agreeing to establish a pay‐for‐play system for its Division I student‐athletes. This new financial structure requires that colleges and universities share 20–22% of their athletics department revenue with their student‐athletes, capped at $20 million per year. No part of the proposed settlement agreement addresses, however, how this new financial model would impact gender equity, which is noteworthy because of the ongoing debate as to whether Title IX applies to issues surrounding compensation.

EFFECT OF PUBLIC PRIVATE PARTNERSHIP FINANCING STRUCTURE ON COMPLETION OF GEOTHERMAL ENERGY DEVELOPMENT PROJECTS IN KENYA

Objective: To determine the effect of Public Private Partnership (PPP) financing structure on the completion of geothermal energy development projects in Kenya. Theoretical Framework: The study used agency and public choice theories to analyze the dynamics between PPP financing structure and completion of geothermal energy development projects. Methodology: A cross-sectional census survey in Kenya surveyed 48 geothermal energy development projects, collecting quantitative data through structured questionnaires and qualitative insights from industry regulators, financiers, and practitioners. A combination of descriptive, correlation, and linear regression statistical models were applied. Multiple diagnostics tests and data triangulation were performed. Results and Discussion: The study results provide strong statistical evidence depicting a positive relationship between PPP financing structure and the completion of geothermal energy development projects in Kenya. The findings suggest that as the level of PPP involvement increases, so does the likelihood of faster project completion. The study also reveals that a balanced PPP financing structure has a substantial effect on the completion of geothermal energy development projects. The analysis demonstrates that a hybrid PPP financing structure comprising recommended proportions of private and government equity, commercial and concessional loans, hybrid finance, and grants significantly affects project completion outcomes. Research Implications: The study emphasizes the significance of a structured PPP financing model, comprising private and government equity, concessional and commercial loans, hybrid finance, and mixed grants, in mitigating inherent PPP risks for enhanced project completion outcomes. In addition, effective government support measures and robust delivery capability of developers jointly influence the two variables in a significant manner. Originality/Value: This study uniquely analyzes the influence of PPP financing structure on the completion of geothermal energy development projects in Kenya, integrating quantitative and qualitative data for a comprehensive perspective, thus offering essential insights for stakeholders.

Reliability-Centric Maintenance Planning for Bridge Infrastructure: A Novel Method Based on Improved Electric Fish Optimization

Bridge infrastructure provides an important effect on contemporary transportation networks, and its upkeep is significant for ensuring public safety and reducing economic impacts. Nevertheless, the aging and degradation of bridge structures present considerable challenges for asset managers, who must navigate the necessity of maintenance against constrained financial resources. Conventional maintenance approaches typically emphasize reactive repairs, which can result in elevated lifecycle expenses and risk structural integrity. This paper introduces an innovative framework aimed at optimizing bridge maintenance expenditures while maintaining structural safety. The proposed methodology incorporates a reliability-based deterioration model, an intervention effect model, a financial model, and an optimization model empowered by an Improved Electric Fish Optimization (IEFO) algorithm. The framework is demonstrated through a case study of a reinforced bridge framework designed according to the standards of Canadian highway bridge design. The findings illustrate that the proposed methodology can substantially lower lifecycle costs by investigating the most economical maintenance strategies, including minor repairs that can postpone the necessity for expensive major interventions. The optimal scenario identified by the IEFO algorithm yielded lower equivalent uniform annual costs in comparison with the traditional scenario focused solely on major repairs. This research advances the field of data-driven maintenance planning for bridge infrastructure, empowering asset managers to make well-informed decisions that effectively balance cost and safety considerations.

"All of these things interact, that's why it's such a wicked problem": Stakeholders' perspectives of what hinders low back pain care in Australia and how to improve it.

Low-quality care for low back pain (LBP) is pervasive in Australia. Drivers of low-quality care have been identified elsewhere and include misconceptions about LBP, vested interests and limited funding for evidence-based interventions. Yet, the literature that identified such drivers is not specific to the Australian context, and therefore, it is likely to represent only part of the local problem. This study aimed to determine where the most influential drivers of LBP care are in the Australian healthcare system and what could be done to address them. Clinical leaders from various disciplines, academics, hospital managers, policy-makers, consumers involved in LBP advocacy, board members of relevant health profession boards and private insurers were invited to participate in one-on-one interviews. Interviews were transcribed verbatim. Interview data were analysed using content analysis. We interviewed 37 stakeholders. Challenges that hinder LBP care in Australia included variability in care and inconsistent messages, funding models that are not supportive of appropriate care for LBP, the community's understanding of LBP, vested interests and commercial forces, difficulties in accessing timely and affordable conservative care, neglect of social determinants and health inequities, short consultations, siloed practices, uncertainties that stem from gaps in evidence and the experience of having LBP, individual and contextual variability, the mismatch between evidence and practice, the Australian healthcare system itself, the lack of political will and acknowledgement of LBP as a public health issue, stigma, the need to improve human aspects and the compensation system. When discussing factors that could improve LBP care, participants raised collaboration, changes in funding, improvement of access to - and affordability of - models of care and care pathways, public health campaigns targeting LBP, enhancement of policy and governance, increasing and better training the workforce, consideration of inequities, making improvements in information sharing and reforming the worker's compensation sector. LBP is a wicked problem, influenced by several systemic factors. An agenda for system change in the LBP landscape should be guided by a collaborative, coherent and integrated approach across sectors to enhance quality of care and system efficiency for those who seek and provide care.

Financial Performance Evaluation using Financial Distress models with reference to Dabur India Ltd

The global FMCG business is expected to reach close to $15000 billion by 2025 in the current era of e-commerce. Accordingly, FMCG is identified as the fourth-largest sector in India. One of the top businesses in India is Dabur India Ltd. As a result, we tried to evaluate the financial patterns and performance during the previous ten years. The main objective of this study is to assess the financial positions with respect to profitability, solvency, liquidity, etc. For the study, the ratio analysis techniques are employed and Financial Distress of Dabur India Ltd is analysed by Altman's Z-Score Model and Zmijewski Model. The study's overall conclusion unequivocally shows that Dabur is benefiting from positive financial performance across the board. This could assist Dabur India in maintaining a strong market share and a leading position in the FMCG industry.

The Political Economy of Variations in Energy Debt Financing by Two Chinese Policy Banks in Africa

ABSTRACTThis article examines the puzzle of why China's two policy banks, China Development Bank (CDB) and the Export‐Import Bank of China (Eximbank), have lending portfolios for power‐generation projects in Africa that have drastically different levels of carbon dioxide emissions. From the supplier side, Eximbank balances two imperatives: Beijing's ideational ambition as a new development provider to African recipients with sustainability commitments, and China's industrial goal to offshore non‐renewable capacity. In contrast, the CDB prioritizes its commercial interests, which results in the bank lending solely for coal projects. On the demand side, Eximbank's concessional capital has emerged as a second‐best option among international financial sources for renewable and hydropower generation projects. Conversely, CDB's market‐rate lending makes it the fiscal last resort for host countries seeking financial support for thermal‐power projects which are shunned by other financiers. This divergence can be understood through the polycentric development finance model, which captures the parallel decision‐making institutions governing Chinese energy financing in Africa. Specifically, the lending decisions of Eximbank are linked with institutionalized policy processes, translating priorities of Chinese and African state actors. Meanwhile, the loan origination processes of CDB are more independent of state actors, allowing greater autonomy for the financier to pursue commercial interests.

Simplifying acquisition of essential diagnostics: A comprehensive costing tool for anatomic pathology.

Histopathology is the core diagnostic tool for cancer in pathology laboratories around the world, but there are disparities in access to diagnostics globally. As recognition of the need for cancer care and treatment grows, especially in the wake of World Health Organization programs for cervical, breast, and pediatric cancers, policymakers and health care funders are seeking tools and processes that allow for the largest number of patients to receive a diagnosis at the lowest cost. As histopathology represents the most cost-effective diagnostic method by sheer number of tumor types and volume, understanding the detailed logistics and costs for histology as well as the impactful benefits of economies of scale (ie, larger volumes are less expensive per patient) and scope (ie, the multiple stains available after basic histology sectioning) is paramount to planning an effective publicly funded or government laboratory. Understanding the economic structure of a country's population along with the financial model of a histology laboratory also leads to a market understanding of private laboratories, which can provide services at a profit as well as pro bono services more cost-effectively than purely public laboratories. We have developed a comprehensive, scalable costing tool of a functioning histology laboratory that accounts for all feasible costs and variations in models of service. The tool allows for a standardized approach to selecting goods needed to provide histology services and serves as a guide for implementation of pathology services. Using the tool, laboratories can achieve self-sustainment and long-term financial health while incorporating a proportion of impoverished patients who cannot afford out-of-pocket expenses.

The intersection of financial modeling and public health: A conceptual exploration of cost-effective healthcare delivery

This review paper explores the intersection of financial modeling and public health, highlighting the importance of cost-effective healthcare delivery in contemporary health systems. Financial modeling serves as a crucial tool for policymakers, providing evidence-based insights that inform decision-making and optimize resource allocation. Key financial models, including cost-benefit analysis and predictive modeling, are examined for their applications in public health initiatives, particularly in areas such as preventive care and chronic disease management. The paper discusses core public health priorities—prevention, access, and quality—and the economic constraints faced by healthcare systems. Recommendations are provided for policymakers and healthcare professionals to enhance the application of financial models, emphasizing the need for training, investment in data infrastructure, and fostering cross-sector collaborations. By leveraging financial modeling, public health systems can achieve improved health outcomes while maximizing resource efficiency, ultimately contributing to a more sustainable and equitable healthcare landscape.. Keywords: Financial Modeling, Public Health, Cost-Effectiveness, Healthcare Delivery, Resource Allocation, Preventive Care.

Attribute Relevance Score: A Novel Measure for Identifying Attribute Importance

This study introduces a novel measure for evaluating attribute relevance, specifically designed to accurately identify attributes that are intrinsically related to a phenomenon, while being sensitive to the asymmetry of those relationships and noise conditions. Traditional variable selection techniques, such as filter and wrapper methods, often fall short in capturing these complexities. Our methodology, grounded in decision trees but extendable to other machine learning models, was rigorously evaluated across various data scenarios. The results demonstrate that our measure effectively distinguishes relevant from irrelevant attributes and highlights how relevance is influenced by noise, providing a more nuanced understanding compared to established methods such as Pearson, Spearman, Kendall, MIC, MAS, MEV, GMIC, and Phik. This research underscores the importance of phenomenon-centric explainability, reproducibility, and robust attribute relevance evaluation in the development of predictive models. By enhancing both the interpretability and contextual accuracy of models, our approach not only supports more informed decision making but also contributes to a deeper understanding of the underlying mechanisms in diverse application domains, such as biomedical research, financial modeling, astronomy, and others.

The role of automated controls and streamlined compliance in managing risks in digital finance

This study investigates the role of automated controls and streamlined compliance in managing risk in digital finance institutions. Through a mixed-methods approach, combining quantitative analysis and qualitative insights from leading Indian digital finance companies (CRED, ZEST MONEY and PHONE PAY), the research examines the effectiveness of advanced technologies in enhancing risk management practices. The study found strong positive correlations between the adoption of automated controls and key performance metrics, including the fraud detection rate (0.68), regulatory reporting accuracy (0.72), and overall risk management effectiveness (0.75). Regression analysis revealed that automated control implementation was the strongest predictor of risk management effectiveness. A comparative analysis of different digital finance models highlights the varying challenges and benefits of implementing these technologies. This study proposes a holistic, future-proof framework that integrates AI, machine learning and blockchain for real-time risk monitoring, automated regulatory reporting and dynamic compliance management. This framework addresses the limitations of the current fragmented approaches and offers a scalable solution that is adaptable to evolving regulatory landscapes. The findings of this study have significant implications for practitioners and policymakers, emphasizing the need for investment in strong automated systems and adaptive regulatory frameworks. While acknowledging the limitations in sample size and longitudinal scope, this research provides a foundation for future studies and offers practical insights for enhancing risk management in the rapidly evolving digital finance sector. The study concludes that effective integration of automated controls and streamlined compliance is crucial for ensuring the resilience, integrity and sustainable growth of the digital finance ecosystem.

AI-Driven Personalization in Financial Services: Enhancing Customer Experience and Operational Efficiency

This article explores how emerging technologies are influencing personalization in the financial services sector. Personalized services enhance customer experience and promote financial inclusion. By leveraging big data and AI, financial institutions can collect and analyze customer data to offer tailored services. AI-driven analytics provide real-time insights for financial modeling, risk management, and automation. The integration of machine learning structures in financial services to meet individual customer needs, ensuring product customization. Emerging technologies promise greater accuracy and personalization, driving better financial outcomes within the industry. This technological advancement is crucial for the modern financial landscape, enhancing performance and customer satisfaction.

Return on Investment of Preoperative Anemia Management Programs in Cardiac Surgery: An Advisory From the Society of Cardiovascular Anesthesiologists Clinical Practice Improvement Committee With Endorsement by the Society for the Advancement of Patient Blood Management

Despite multiple recent guidelines recommending the diagnosis and treatment of anemia before elective cardiac surgery, few institutions have formal programs or methods in place to accomplish this. A major limitation is the perceived financial shortfall and the leadership buy-in required to undertake such an initiative. The purpose of this advisory from the Society of Cardiovascular Anesthesiologists (SCA) Clinical Practice Improvement Committee with endorsement by the Society for the Advancement of Patient Blood Management (SABM) is to provide an overview of preoperative anemia management programs with an emphasis on the associated financial implications. This advisory reviews the evidence for preoperative anemia management programs in both cardiac and noncardiac surgery, discusses options for managing preoperative anemia, provides novel financial modeling regarding the implementation of preoperative anemia management programs, and describes implementation challenges, potential solutions, and opportunities for improvement.

Developing a Model for Sustainable Financing for Biodiversity Conservation in Namibian National Parks

Biodiversity conservation is essential for maintaining ecological balance and fostering sustainable development. Biodiversity conservation efforts in Namibia encompass activities such as monitoring protected areas, preserving natural resources, preventing poaching, adapting to environmental changes, promoting tourism, and engaging in forestry work. Despite these efforts, funding for biodiversity conservation is insufficient, thereby necessitating innovative strategies to secure additional financial resources. Consequently, this study evaluated the total economic costs and benefits of biodiversity and its conservation to create a sustainable financing model for biodiversity conservation in Namibian national parks. This study aimed to develop a model for sustainable financing of biodiversity conservation in national parks, specifically within the context of Namibia. The research addresses the chronic underfunding of conservation activities and explores innovative financial strategies to bridge the funding gap. The study was based on the philosophy of pragmatism, used a mixed-methods research approach, and employed a concurrent research design. For the quantitative aspect, the study used the census sampling approach on 60 respondents. For the qualitative aspect, the study used purposive sampling on nine participants. To collect data, both aspects used structured questionnaires which were self-administered online using Google Forms, whereby the questionnaire for the quantitative aspects comprised closed-ended questions, while the one for the qualitative constituted open-ended questions. The study employed various analytical tools to analyse the data, precisely the PLS-SEM in SmartPLS 4 software for the quantitative aspect and the reflexive thematic analysis with direct quotations in ATLAS.ti for the qualitative aspect. The quantitative aspect of the study ensured reliability in terms of internal consistency using Cronbach’s alpha and composite reliability using omega-a (rho_a). The quantitative aspect of the study used convergent validity based on the factor loading of the indicators and the average variance extracted (AVE), as well as discriminant validity using the Fornell-Lacker and Heterotrait-monotrait (HTMT) ratios. The findings indicate that effective financial management moderately and positively impacts the financial stability of biodiversity conservation in Namibia. Moreover, the study shows a strong positive and statistically significant correlation between sales revenue and financial stability in biodiversity conservation. However, numerous challenges hinder the financial stability of Namibia’s national parks. The study concludes that sales revenue should be a managerial focus in achieving financial stability. Drawing on these findings, a comprehensive model for sustainable financing was developed, which identifies key revenue streams and management practices crucial for long-term financial viability. The results of this study provide a noteworthy contribution to the current state of research, shedding new light on key issues and themes, and elucidating financial obstacles and opportunities pertinent to biodiversity conservation.

Unlocking financial innovation through strategic investments in information management: a systematic review

PurposeThe purpose of this study is to explore strategic investment in information management and its crucial role in driving financial innovation. By examining the integration of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), Blockchain, Big Data Analytics, Cloud Computing, Large Language Models (LLMs), Robotic Process Automation (RPA), Internet of Things (IoT), Cybersecurity Technologies, and Quantum Computing, this research aims to highlight how these technologies enhance decision-making, operational effectiveness, risk management, and compliance within the financial sector.MethodologyThe study employs a comprehensive literature review of existing research to analyze the impact of strategic investment in information management on financial innovation. Key technologies are identified and their applications in finance are discussed. The methodology includes synthesizing findings from various sources to present a cohesive understanding of the relationship between information management, technology, and financial innovation.ResultsThe results indicate that strategic investment in information management significantly enhances financial innovation by leveraging advanced technologies. AI and ML improve predictive analytics and customer personalization, Blockchain ensures secure transactions and transparency, Big Data Analytics enables data-driven decision-making, and Cloud Computing provides scalable solutions. LLMs enhance natural language processing capabilities, RPA automates repetitive tasks, IoT facilitates real-time monitoring, Cybersecurity Technologies protect financial data, and Quantum Computing offers potential breakthroughs in financial modeling and encryption.ImplicationThe implications of this study suggest that financial institutions should prioritize strategic investments in information management and the adoption of advanced technologies to stay competitive and resilient in the evolving financial landscape. Effective information management practices enable better decision-making, improved operational efficiencies, enhanced risk management, and regulatory compliance, ultimately fostering financial innovation.ContributionThis study contributes to the existing body of knowledge by providing a detailed analysis of the role of strategic investment in information management and its impact on financial innovation. It highlights the importance of integrating advanced technologies in financial practices and offers insights into how these technologies can be leveraged to achieve innovative solutions and improvements in the financial sector. The findings serve as a valuable resource for financial institutions, policymakers, and researchers interested in the intersection of technology and finance.