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Role of Risk Management in Minimizing the Rising Cost of Technology

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Introduction

A poll of U.S. managers 2015 revealed that strategic, cultural, and skill-related concerns took precedence over technological challenges in digitalization initiatives, proving that managers' digital competence aids in designing organizations' strategies during the digital era (Ukko et al., 2019). To address this pressing issue, it is essential to explore the role of risk management in minimizing the escalating cost of technology. By prioritizing utilizing information technology systems, organizations can leverage advanced tools and systems to enhance their cost efficiency and financial performance (Şahin & Topal, 2016). Furthermore, embracing digital strategies and sustainability efforts enables businesses to optimize resource allocation, improve operational efficiency, and mitigate risks associated with inadequate technological integration or sustainability practices (Ukko et al., 2019). Incorporating machine learning techniques into risk management practices empowers institutions to predict and manage risks accurately, ranging from credit and market risks to liquidity and operational risks (Leo et al., 2019). In today's rapidly changing technological landscape, organizations must proactively adopt risk management strategies that incorporate technology to effectively mitigate the challenges posed by the rising cost of technology (Şahin & Topal, 2016). Implementing ISO 31000, an international standard for risk management enhances organizational risk management practices by providing a clear framework and systematic approach for identifying, assessing, and managing risks (Dewantara et al., 2022).

Literature Review

Introduction

The rising cost of technology and insufficient risk management knowledge affect several institutions' and companies' financial performance (Şahin & Topal, 2016). The necessity to solve this problem is the rising cost of technology and insufficient risk management strategies that impact companies, is to ensure economic viability and competitive position in a landscape of rapidly evolving technology. The literature review herein has made sure to include only those articles that talk about the role of risk management in minimizing the rising cost of technology. The factors reviewed in this literature review include the usage of information technology, technological integration, risk management, and machine learning. The literature review utilized databases such as ProQuest and EBSCO Host, available through the Monroe College Library, to gather relevant information for the study. The search terms used to gain relevant articles for the literature included information technology, financial performance, cost, and risk management.

Review of Literature

Cost and Performance in Turkish Firms

Şahin and Topal (2016) conducted research 2016 based on businesses in ISO 1000 in Turkey. The study aimed to determine the technologies that affect each performance criterion and to what degree. The authors used the methodology of experimental research. The researchers performed correlation analyses to find the relationships between information technology (IT) users and performance indicators. The process of statistical analysis involved software known as IBM SPSS Statistics 21, and the authors used regression models to determine the relationships between selected variables. Forecasting and demand management systems have a favorable impact on cost and financial performance. Organizations can benefit from specific systems they incorporate in their operations. The usage of IT correlates with indicators of cost performance, which are unit production cost and unit material cost (Şahin & Topal, 2016).

Similarly, Sahin and Topal (2016) conducted a study 2016 to determine the different kinds of technologies that impact various business performance criteria and to what degree and direction. The authors collected data from ISO 1000 businesses in Turkey and embarked on an experimental research method to analyze the performance indicators and the use of IT. To determine the impact of IT utilization on the level of the financial performance of these businesses, the researchers conducted a correlation analysis. The authors used IBM SPSS Statistics 21 software to perform the statistical analyses. The authors used regression models for cost performance, and IT use level relationships. The study analysis showed that forecasting or demand management systems positively impact cost and financial performance (Şahin & Topal, 2016). Businesses have better financial performance when they include EDI and ERP systems in their activities. Also, the use of IT affects cost performance indicators like the unit product and unit material cost and financial performance indicators like asset profitability, sales, and asset turnover.

Sustainability in Finnish SMEs

Similar observations were made by Ukko et al. (2019) conducted a study in Finland in 2019 to investigate the role of a business sustainability strategy. The researchers used the survey to determine whether small businesses benefited financially from their digitization strategy. The authors used a combination of survey research and quantitative analysis. The authors used online questionnaires sent to 6,816 SMEs, with 280 good feedbacks. The study reviewed existing literature to determine whether a viable relationship exists between digital and sustainability strategies of businesses. The authors also developed four hypotheses to test through their research. The study's findings support that companies should direct adequate managerial attention toward technology and sustainability to achieve high financial performance. The study observed that companies could gain a competitive advantage and improve performance by allocating more effort and resources to the virtual world. Furthermore, the study suggests that managers prioritizing digital strategies can mitigate the risks associated with misidentifying and misallocating processes and resources. By focusing on digital strategies, managers can optimize resource allocation, enhance operational efficiency, and minimize potential pitfalls from inadequate technological integration or sustainability practices (Ukko et al., 2019). These findings highlight the importance of a balanced managerial approach encompassing technology and sustainability considerations for sustained success in today's business landscape.

On the other hand, Ukko et al. (2019) performed research in 2019 in Finland regarding how three business areas, namely sustainability, technology, and finance, connect to benefit the business. The study aimed to establish a connection between these three areas of companies, to know the definite stand to take when incorporating these strategies. This paper presents the analysis and findings on the relationship between these three critical components of businesses to help managers make effective managerial decisions in running their businesses. The report categorizes the management and operational competencies necessary to implement a digital business strategy. The authors used survey research and quantitative analysis to collect data from Finnish SMEs through online questionnaires. The researchers decided to communicate with the survey respondents using mail, providing all the information regarding the requirements of the questionnaire. The number of businesses that responded to the questionnaire was 280, showing a response rate of 4.8% out of the valid ones considering that 986 emails were invalid. According to the researchers, the ANOVA test helped confirm that the study was good to go despite the nominal non-response rate. Ukko et al. assert that managers of businesses can make more financial progress, achieving more success in that section if they embrace technology and leverage it with sustainability (2019). Companies must take more significant strides toward virtuality to perform better and gain a competitive advantage. Consequently, businesses that have a clear strategy for the cyber world are more efficient since they are less likely to misidentify and misallocate processes and resources.

Machine Learning in Banking Risk Management

Similarly, Leo et al. (2019) researched papers published after 2007 to identify businesses' progress since the worldwide economic downturn. The researchers were concerned about how banks managed to handle and control multiple risks they faced over the years after the crisis by reviewing existing articles. The paper used a literature review of existing documents. The authors used several reliable databases to find pieces on the topic. The research involved a search of two keywords that were machine learning. The study also analyzed risk areas, including credit, market, liquidity, and operational risks. The paper revealed that machine learning (ML) techniques are crucial for banks since they allow banks to predict different risks more appropriately. Banks must incorporate research and models in their risk management functions to predict or estimate the three types of risks that the authors specify in the study (Leo et al., 2019).

Leo et al. (2019) researched papers published after 2007 to show the developments in the banking industry, especially in matters of risk management. Significant academic and industrial research attention has highlighted the progress and downfalls of the banking industry, especially concerning the financial turmoil of 2007. This paper uses existing literature to highlight banks' developments when managing uncertainties. The article also delves into those areas that stakeholders may need to investigate and conduct further research regarding banks and the industry. The authors use a literature review methodology of all relevant existing literature that sheds light on risk management regarding these financial institutions. The authors embarked on research databases that were reliable to the context of the study. The investigation of the study was strategically timed to capture the progress banks have made ever since the market crash in 2007. However, earlier reports were also considered if referenced in recent publications. Two keywords were used to search for relevant articles to conduct the literature review. The analyzed risk areas included credit, market, liquidity, and operational risks. The research articles in the study focus on estimating key elements that affect the uncertainty and profitability of the businesses under discussion. The predictive models that institutions used to find certain factors were of great value to the profitability and progress of banking financial institutions (Leo et al., 2019). ML techniques have demonstrated superior performance to traditional statistical methods regarding classification and predictive accuracy. However, financial institutions must stay cautious of the biases that affect data since they can also affect their prediction strategies.

Analysis of Literature

The rising cost of technology has been a constant challenge for most companies, leaving risk management as the only resort to mitigating this challenge. The factor contributing to the rising cost of technology is low strategizing and utilization of risk management strategies by these companies. The methods used to collect data for each article were unique as Şahin and Topal (2016) used experimental research. On contrary Ukko et al. (2019) employed survey research and quantitative analysis while Leo et al. (2019) conducted a systematic literature review. The focus by Şahin & Topal (2016) focused on the cost and performance of firms, examining the impact of information technology on financial and cost performance indicators. Similarly, Ukko et al. (2019) explore the relationship between sustainability strategies, technology, and the financial performance of SMEs. Leo et al. (2019) researched to examine the progress and utilization of machine learning techniques in banking risk management. While the first two articles by Şahin and Topal (2016) and Ukko et al. (2019) established study contexts, Turkey and Finland, respectively, the third article did not specify the study context.

Additionally, the other differences involved the methodologies considered in each study. Şahin and Topal (2016) used experimental research, using correlation analyses and regression models to determine the relationship between the utilization of information technology and performance indicators. Ukko et al. (2019) combined survey research and quantitative analysis, using online questionnaires to collect data. The researchers then examined the relationship between sustainability strategies, technology, and financial performance. Leo et al. (2019) used a literature review to analyze existing documents investigating machine learning techniques in banking risk management.

The three articles highlight the potential benefits of leveraging technology and digital space strategies, stating they are crucial for driving financial success and competitive advantage in companies. According to Şahin and Topal (2016), using technology can benefit firms. The authors specify that information technology can positively impact various companies' and businesses' financial and cost performance indicators. Likewise, Ukko et al. (2019) found that integrating digital strategies and technology in various business operations will benefit businesses in many ways. This strategy allows businesses to enjoy operational efficiency, better resource allocation, and optimal financial performance. Similarly, Leo et al. (2019) affirm that machine learning techniques play a crucial role not only in predicting but also managing various risks like credit, market, and operations that are in the banking sector. The findings of these articles suggest that incorporating technology like information technology systems and machine learning techniques can contribute to risk management that will improve financial performance and operational efficiency.

Discussion

Introduction to Discussion

The rising cost of technology and insufficient risk management knowledge pose significant challenges to the financial performance of institutions and companies (Şahin & Topal, 2016). In today's rapidly evolving technological landscape, companies must address this problem to ensure economic viability and maintain a competitive position. Insufficient risk management strategies contribute to the escalating cost of technology, impeding companies from optimizing their financial performance and adapting to technological advancements (Şahin & Topal, 2016; Ukko et al., 2019). This problem affects a wide range of institutions and companies across various sectors that heavily rely on technology for their operations and strive to remain competitive in the market. The literature review conducted for this study encompasses articles that specifically address the role of risk management in minimizing the rising cost of technology. Through this review, several key factors have emerged, including the usage of information technology, technological integration, risk management practices, and machine learning techniques (Şahin & Topal, 2016; Ukko et al., 2019; Leo et al., 2019). By examining these factors, the literature review aims to shed light on the strategies and approaches that companies can adopt to effectively manage the challenges posed by the increasing cost of technology. The selected articles provide valuable insights into the connection between risk management practices and financial performance, offering guidance on how organizations can navigate the evolving technological landscape while ensuring cost efficiency and sustainable growth. The population affected by the rising cost of technology and insufficient risk management knowledge encompasses various institutions and companies across industries. For instance, Şahin and Topal (2016) conducted their research on ISO 1000 businesses in Turkey, providing insights into the impact of information technology on these companies' costs and financial performance. Similarly, Ukko et al. (2019) focused on small and medium-sized enterprises (SMEs) in Finland, exploring the relationship between sustainability strategies, technology, and financial performance. By addressing the challenges these specific populations face, the studies contribute to the broader understanding of how risk management strategies can benefit companies of different sizes and operating in diverse contexts (Şahin & Topal, 2016; Ukko et al., 2019).

Evidence-Based Recommendation

Recommendations from Literature Review

Companies should prioritize utilizing information technology (IT) systems and tools to enhance their cost and financial performance (Şahin & Topal, 2016). Implementing forecasting and demand management systems has been found to positively impact cost performance indicators, such as unit production cost and unit material cost (Şahin & Topal, 2016). Therefore, companies should consider integrating these systems into operations to improve cost efficiency and optimize financial outcomes. Second, businesses should adopt digital strategies and prioritize sustainability to achieve high financial performance (Ukko et al., 2019). Allocating sufficient managerial attention and resources to technology and sustainability can lead to competitive advantage and improved financial outcomes (Ukko et al., 2019). By embracing technology and leveraging it with sustainability practices, companies can optimize resource allocation, enhance operational efficiency, and minimize risks associated with inadequate technological integration or sustainability practices (Ukko et al., 2019). Furthermore, financial institutions should explore machine learning (ML) techniques in their risk management functions (Leo et al., 2019). ML techniques have demonstrated superior performance in predicting and managing various risks, including credit, market, liquidity, and operational risks (Leo et al., 2019). Incorporating ML models and research in risk management can enable banks to make more accurate risk assessments and improve their overall financial performance (Leo et al., 2019). Companies and institutions can benefit from evidence-based recommendations to address the challenges associated with the rising cost of technology and insufficient risk management knowledge. These recommendations include utilizing information technology systems, embracing digital strategies and sustainability efforts, and incorporating machine learning techniques in risk management practices. By implementing these recommendations, organizations can enhance their cost efficiency, financial performance, and competitive position in today's rapidly evolving technological landscape.

Implementing ISO 31000, an international standard for risk management, greatly enhanced the organization's risk management practices. The adoption of this standard provided a clear framework and systematic approach for identifying, assessing, and managing risks. The adoption of ISO 31000 allowed the organization to adopt a comprehensive and systematic approach to identifying risks, enabling them to anticipate potential risks and take preventive measures promptly (Dewantara et al., 2022). The standard guided conducting risk assessments, allowing the organization to evaluate risks based on their likelihood and potential impact. By implementing ISO 31000, the organization improved its risk assessment methodologies, resulting in a more accurate understanding of the risks. By implementing ISO 31000, the organization established a feedback loop that facilitated ongoing learning and refinement of its risk management practices (Dewantara et al., 2022). This step allowed them to adapt and respond effectively to emerging risks. Two key recommendations are highlighted to implement ISO 31000 and enhance risk management practices effectively. First, conducting a comprehensive gap analysis is essential to identify areas for improvement and establish a baseline for implementation. This analysis will help organizations understand their current risk management practices and identify gaps that must be addressed to align with ISO 31000 requirements. Second, providing training and awareness programs to employees at all levels is crucial. By educating and raising awareness about ISO 31000 principles, organizations can ensure a common understanding of risk management and foster a proactive risk assessment and mitigation culture. Additionally, training will equip employees with the necessary skills and knowledge to implement ISO 31000 effectively, enhancing risk management across the organization.

Conclusion

By offering a clear framework and systematic strategy for detecting, evaluating, and managing risks, the implementation of ISO 31000, an international standard for risk management, improves corporate risk management practices (Dewantara et al., 2022). Examining how risk management might be used to reduce the rising cost of technology is crucial to resolving this urgent problem. Organizations may use cutting-edge tools and systems to improve their cost-effectiveness and financial performance by emphasizing information technology systems (Şahin & Topal, 2016). Additionally, adopting digital strategies and sustainability initiatives helps companies to maximize resource allocation, enhance operational effectiveness, and reduce risks related to insufficient technology integration or sustainability standards (Ukko et al., 2019). Institutions may properly identify and manage risks, ranging from liquidity and operational risks to credit and market risks, by integrating machine learning techniques into their risk management procedures (Leo et al., 2019). In order to successfully minimize the issues provided by the growing cost of technology in today's fast-evolving technological ecosystem, firms must proactively embrace risk management techniques that include technology (Şahin & Topal, 2016). Managers' digital competence helps shape companies' strategies during the digital era, as evidenced by a survey of U.S. managers 2015, which showed that strategic, cultural, and skill-related concerns take precedence over technological issues in digitalization efforts (Ukko et al., 2019).

References

Dewantara, F., Egidius, E., & Amarilies, H. (2022, August). Implementation of Risk Management Based on ISO 31000 as a Risk Prevention Strategy for Diesel Fuel Receiving and Distribution Facilities. In  Proceedings of the 1st International Conference on Contemporary Risk Studies, ICONIC-RS 2022, 31 March-1 April 2022, South Jakarta, DKI Jakarta, Indonesia. http://dx.doi.org/10.4108/eai.31-3-2022.2320944

Leo, M., Sharma, S., & Maddulety, K. (2019). Machine learning in banking risk management: A literature review.  Risks,  7(1), 29. https://www.mdpi.com/2227-9091/7/1/29/pdf

Şahin, H., & Topal, T. (2016). The effect of the use of information technologies in businesses on cost and financial performance.  International Journal of Engineering Innovations and Research (IJEIR),  5(6), 394-402. https://www.researchgate.net/profile/Hasan-Sahin-22/publication/311952770_The_Effect_of_the_use_of_Information_Technologies_in_Businesses_on_Cost_and_Financial_Performance/links/5864cbac08ae6eb871adaa37/The-Effect-of-the-use-of-Information-Technologies-in-Businesses-on-Cost-and-Financial-Performance.pdf

Ukko, J., Nasiri, M., Saunila, M., & Rantala, T. (2019). Sustainability strategy as a moderator in the relationship between digital business strategy and financial performance.  Journal of Cleaner Production,  236, 117626. https://www.sciencedirect.com/science/article/pii/S095965261932476X