عرض العناصر حسب علامة : الاستثمار
الإثنين, 03 أكتوبر 2022 13:27
أدوات التحويل الحاكمة
مع اعتماد المزيد من المؤسسات للتحليلات والأتمتة، يمكن للمدققين الداخليين المساعدة في تقييم المخاطر وإنشاء إطار عمل للحوكمة.
معلومات إضافية
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المحتوى بالإنجليزية
Governing Transformative Tools
As more organizations adopt analytics and automation, internal auditors can assist in assessing risks and establishing a governance framework.
Gregory Kogan, Daniel Gaydon, and Douglas M. BoyleOctober 14, 2021Comments
Competitive excellence demands the implementation of data analytics and automation technologies, such as robotic process automation (RPA) and self-service data analytics. These technologies allow organizations to collate and analyze data from massive data sets that are too large to compile in database and spreadsheet applications. In some cases, they can download a trial version and quickly build databases.
Applications like this have driven global organizations to increase their investments in data analytics and automation technologies to streamline repetitive manual processes into powerful and effective automated processes. Annual worldwide spending on RPA technology is projected to grow from $3.6 billion to $42 billion over the next five years, according to Zinnov, a global management consulting company based in Bangalore, India.
Yet, while intelligent automation can provide significant financial and operational benefits, it also can cause considerable reputational, regulatory, financial, and operational damage when it goes wrong. For example, if automation is left unattended, it could lead to errors in critical processes that affect accounting and financial reporting outputs. Internal audit can assist executives and the board in assessing these risks and establishing a governance framework in anticipation of exponential organizationwide adoption of automation and analytics applications.
MEASURING ROI
The driving force behind investments in process automation lies in the potential for realizing large annual cost savings, especially when these technologies are scaled throughout the organization. “For a mid-table Fortune 1000 organization with around $20 billion in revenue and 50,000 employees, automating 20% of estimated addressable activity through RPA could result in $30 million of bottom-line impact each year,” Deloitte reports in The Robots Are Ready. Are You?
C-level executives responding to a 2020 Protiviti survey say the biggest benefits of process automation include increased productivity, better quality, stronger competitive market position, higher customer satisfaction, greater speed, and employee satisfaction from elimination of mundane tasks. However, respondents report encountering obstacles such as inability to prioritize potential RPA initiatives, concerns about cybersecurity and data privacy, high implementation costs, difficulty in scaling applications, and making a convincing business case.
While the development time of RPA projects typically ranges from several weeks to a few months, self-service data analytics projects can be deployed even faster. Simple processes can be automated within a few hours or a few days.
Traditionally, return on investment (ROI) on automation is measured by how many hours are saved. Both RPA and self-service analytics have demonstrated high ROI, when comparing resources invested in the automation projects to the value returned through capacity creation and efficiency. Value is realized by redeploying employee hours saved elsewhere, contributing to organizational productivity (see “Capabilities of RPA and Self-service Data Analytics” below).
ASSESSING RISK
To maintain risk transparency, it is essential for internal audit to create a risk-scoring mechanism that assesses each automation project based on applicable risk dimensions. Starting with the model risk methodology Allan Sammy describes in his June 2018 Internal Auditor article, “Auditing Analytic Models,” his scorecard can be expanded to include key metrics specifically pointed toward automated accounting and finance processes:
Complexity. If the automation deployment is more complex in terms of processing steps, technologically, or is specialized/customized in a way that makes it more intricate, these deployments score higher on the complexity scale.
Economic loss. An increased level of precision is required when failure could result in a direct or explicit economic loss to a client or counterparty.
Consumer. Regulatory risk will be higher if the automation deployment produces outputs for reports that are intended for external regulators and will be audited
or examined.
Success rate. A historical computation compiles the success rate of the automation run over a prescribed reporting period, such as a month, quarter, or year.
Dependency. When automation deployments produce outputs that serve as inputs into other automation deployments, dependency is higher, because an error in this type of automation will permeate other processes.
“Risk Assessment of an Automated Process” (below) is an example of how a scorecard can be applied in an accounting or finance department. Each unique automation deployment risk is scored according to five dimensions unique to the automation environment of those functions. Internal auditors can use this method to assess the risk of each individual automation project deployment, which is usually related to a specific process such as a bank reconciliation.
Because each automation deployment has a different degree of risk related to complexity, economic loss, ultimate consumer, success rate, and dependency, each project will carry a risk score across these five dimensions. By documenting the total risk of individual projects and their related processes, internal auditors can provide management with risk transparency over the automation portfolio and design risk responses strategically.
GOVERNING THE DIGITAL ENVIRONMENT
As companies deploy automation and analytics to accelerate routine processes and create efficiency, the biggest threat to success in scaling these programs is the lack of governance over the risks and controls in this new digital environment. Many organizations that have embraced digital transformation may still be operating under fragmented legacy governance structures that have failed to keep pace with the growth in data analytics tools. Worse yet, governance may be an afterthought, even as build after build propagates dependency after dependency, incrementally adding risk to the data analytics portfolio.
This governance vacuum is compounded by a regulatory gap. For example, in the highly regulated world of accounting and finance, currently there is a lack of specific regulations or guidance on how to establish stable governance and internal controls for automated processes.
Companies are subject to a variety of regulations and governance frameworks such as Section 404 of the U.S. Sarbanes-Oxley Act of 2002, The Committee of Sponsoring Organizations of the Treadway Commission’s Internal Control–Integrated Framework and Enterprise Risk Management–Integrating
With Strategy and Performance, and the U.S. Federal Reserve Data/Model Governance framework. Each mandates that internal controls be effective, risks be managed, and quality of data inputs be high. However, existing laws and frameworks fall short of offering specific guidelines on how to assess the added risks that arise from operating in this new, automated processing environment. Internal audit can lead the governance effort over analytics and automation programs by focusing on three areas.
Training on Analytics and Automation Capabilities Internal audit can contribute to effectively auditing and mitigating risks in the automation and analytics environment by understanding these tools and their capabilities. This includes ensuring that training and development in this area are available throughout the organization.
Leading Through the Analytics and Automation Governance Committee The governance of analytics and automation programs usually occurs through an automation center of excellence or multidisciplinary governance committee. Internal audit should interface with these functions and take a leadership role in overseeing deployments of these technologies. This can enable internal audit to ensure that appropriate internal controls and end-to-end process assurance are embedded into the deployments from the onset.
Identifying High-ROI Analytics and Automation Opportunities Internal auditors can leverage their deep knowledge of organizational processes to advise management by identifying high-ROI analytics and automation opportunities throughout the organization, which can be challenging to find. By taking this proactive role, internal audit can contribute to the success of scaling the analytics and automation.
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تكنولوجيا المعلومات
موسومة تحت
الثلاثاء, 07 سبتمبر 2021 11:17
فوائد الاستثمار في التكنولوجيا السحابية
هناك خياران يمكن من خلالهما الاستثمار في السحابة، إنشاء بيئة سحابية داخلية او اختيار الخدمات السحابية من مزود الخدمة ومع ذلك كن مطمئناً لأن الاستثمار في السحابة سيكون مفيداً لأعمالك المحاسبية. فميا يلي بعض فوائد الاستثمار في التكنولوجيا السحابية:
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تكنولوجيا المعلومات
موسومة تحت
الثلاثاء, 24 مايو 2022 07:30
إنفوجرافيك.. حوافز الاستثمار في المملكة العربية السعودية والإمارات العربية المتحدة للشركات الأجنبية
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إنفوجرافيك
الثلاثاء, 24 مايو 2022 12:51
حوافز الاستثمار في المملكة العربية السعودية والإمارات العربية المتحدة للشركات الأجنبية
يؤثر الاستثمار الأجنبي المباشر على النمو الاقتصادي والتنمية بطريقة مباشرة بالمساهمة في تكوين رأس المال الثابت وبطريقة غير مباشرة من خلال قنوات تشكل مؤثرات خارجية متعلقة بالاستثمار الأجنبي المباشر
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دراسات و تقارير
الإثنين, 11 يناير 2021 13:36
كيف يمكن للتكنولوجيا المالية أن تساعد المحاسبة في تقديم بيانات استثمار موثوقة وفي الوقت المناسب؟
لا تدوم الفرص طويلاً، لا سيما في عالم المال سريع الحركة
معلومات إضافية
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المحتوى بالإنجليزية
How fintech can help accounting deliver timely, trustworthy investment data
By Ted Meissner
Opportunities don’t stick around long, especially in the fast-moving financial world. When you’re managing a large, diverse portfolio, you need to respond quickly when opportunities arise, and you need up-to-the-minute data to act with any confidence. But accounting and investment pros can’t audit sources and verify data quickly enough to ensure the information is both updated and accurate. Without insight into the source and age of data and fresh analytics, they’re operating at a huge disadvantage.
There are several reasons why reliable data is so hard to come by. The need to reconcile information from multiple sources is a big part of the problem. Data is often siloed throughout the organization, and input from numerous departments is anything but consistent. When managers must sort through stale data, updates, revisions and inconsistencies, it’s difficult to trust the information. They’re not alone in their frustration. The concern extends up to the C suite, where the chief financial and operations officers (CFOs and COOs) and chief information officer (CIO) are looking for solid data to support sound decisions and satisfy investment committees.
Fortunately, fintech can help address this problem. State-of-the-art accounting solutions provide full transparency on the quality of the data, revisions, corrections and approvals. That results in trustworthy data — the foundation for smart, fast, strategic decisions.
Data is inconsistent and inaccessible
With a manual process, it’s difficult to ensure data consistency and availability. Multi-asset data comes from a number of sources, including fund managers and accountants, sometimes including outside contractors. Often, they use different formats and timetables, which can make it hard to collate data. Handling data collection manually is a slow, tedious process full of duplication and prone to human error. Once the information has been gathered, someone has to take the time to reconcile the results into something that makes sense.
That’s easier said than done. When staff members handling different functions import and rekey details into a variety of applications, data can be stuck in those apps and siloed in those departments. Many individuals and departments maintain separate spreadsheets for their own purposes and don’t share all the information across the organization.
Given these obstacles, it’s easy to understand why it’s hard to get accurate data that is up to date, consistent across the organization and ultimately reliable.
Productivity suffers
It’s not unusual for accountants to handle all non-investment functions in an investment firm, including tax and compliance functions as well as accounting. In addition, they’re often assigned responsibility for performance reporting and contribution/attribution analysis. That’s all well within their capability, but it’s hard to accomplish using substandard tools such as spreadsheets.
The situation gets even more complicated when the work isn’t handled in-house but outsourced to outside accounting firms. When debits and credits are booked externally, there can be a lack of detailed audit trails for internal accountants to follow. Additional problems can arise when third parties don’t know what form the data should take. Companies are unhappy when data isn’t ready when needed or is difficult to reconcile.
Shadow systems add to the complexity. These workarounds often require companies to redo the work they’re paying an outside vendor to deliver. That extra step may provide more confidence in data, but it’s expensive and inefficient, and it can wind up creating yet another data silo.
Faced with these realities, accountants can feel they’re unable to provide their best work despite their best efforts. Spending hours on routine tasks such as rekeying data into diverse systems rather than doing productive value-added work is a waste of their time and talent, leading to job frustration.
Technology is the answer
Automation can resolve many of these problems. Fintech software providers offer next-generation solutions that ingest data, record it once and distribute it to the appropriate systems for portfolio accounting, performance reports and analyses, and private investment tracking. Indexing provides both an audit trail and insight into data quality, and algorithms can be used to analyze key indicators and assign data a confidence rating.
The investment industry now has the tools to solve the longstanding problems it has had with data. By harnessing technology, firms can enjoy more control and enhanced efficiency and have more confidence in the integrity of their data. In the end, this will give them more time to manage portfolios and deliver even more valuable service to their clients.
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موضوعات متنوعة
الخميس, 09 سبتمبر 2021 07:54
دراسة ماجستير: شركات الوساطة وأثرها على تنمية سوق فلسطين للأوراق المالية
يعتبر السوق المالي (البورصة) مرأة الاقتصاد الذي يتواجد به، حيث تقوم الأسواق المالية بدور حيوي يتمثل في تعبئة المدخرات وإعادة توظيفها بما يخدم عملية التنمية للقطاعات الاقتصادية المختلفة مما يعود بالفائدة على المجتمع بأسره. كما أنه لا يوجد اقتصاد قوي في دولة تفتقر إلى سوق مالي قوي لأنه أهم مكونات الاقتصاد الوطني وأحد أهم آليات تجميع وتوجيه الموارد المالية وتوظيفها في المشروعات الاستثمارية
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رسائل ماجستير و دكتوراة
الخميس, 09 سبتمبر 2021 07:56
دراسة ماجستير: دور محاسبة المسئولية في تحقيق الميزة التنافسية في الشركات الصناعية السعودية
لم يعد يقتصر دور المحاسبة على تسجيل الأحداث التاريخية فقط وإنما تعددت أدوارها لتصبح المساهم الأكبر في عملية إعداد وتقديم الخطط المستقبلية للشركة، وامتد عمل المحاسب ايضاً إلى وضع آليات وأدوات يمكن من خلالها تقييم الأداء ومعرفة مدى إنحراف المنشآت عن مسارها، ومن هنا ظهرت المحاسبة الإدارية كعلم يبحث في هذه الجوانب من خلال ما تقدمه من معلومات مالية تفيد مدراء المنظمات من تحديد الأهداف المستقبلية بالإستعانة بهذه المعلومات المالية لتفيدهم في إتخاذ قراراتهم ووضع خططهم المستقبلية
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رسائل ماجستير و دكتوراة
الخميس, 09 سبتمبر 2021 08:00
دراسة ماجستير: دراسة اقتصادية وقياسية لظاهرة التضخم في الجزائر
تسعى الجزائر كغيرها من الدول النامية جاهدة إلى مسايرة التقدم ومواكبة التطورالحضاري الذي يعرفه العالم، فبعد الاستقلال وجدت الجزائر نفسها مضطرة لتحسين سياساتها الاقتصادية محاولة منها للالتحاق بركب الدول المتقدمة فراحت تعمل على النهوض باقتصادها منتهجة في بداية الأمر سياسة الاقتصاد المخطط ضمن الإطار العام للتوجيهات التي تبنتها القيادات السياسية آنذاك
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رسائل ماجستير و دكتوراة
الخميس, 09 سبتمبر 2021 08:54
دراسة ماجستير: استخدام مدخل القيمة الإقتصادية المضافة في تقييم الأداء المحاسبي للشركات
شهد العالم ولا يزال يشهد تحولات وتطورات كبيرة على جميع المجالات خاصة الجانب الاقتصادي منها ، ومن أهمها تناقص أهمية عوامل الإنتاج المادية مقابل تزايد أهمية العوامل غير المادية (غير ملموسة) ، والتي تتمثل في التدريب والتطوير والمعرفة والتكنولوجيا وغيرها من العوامل
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رسائل ماجستير و دكتوراة
موسومة تحت
الخميس, 25 نوفمبر 2021 13:52
دراسة ماجستير: أثر التطبيقات المحاسبية المختلفة لعقود الاستئجار على قرارات الاستثمار في ليبيا
تعتبر قرارات التمويل من أهم القرارات التي تتخذها إدارة الوحدة الاقتصادية لما لها من تأثير جوهري على مستوى أداء الوحدة الاقتصادية فقد تلجأ إدارة الوحدة إلى مصادر التمويل التقليدية المتمثلة في الاقتراض أو إصدار أوراق مالية أو قد تلجأ إلى استخدام أساليب التمويل المبتكرة التي استحدثتها الهندسة المالية Financial Engineering
معلومات إضافية
- البلد ليبيا
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رسائل ماجستير و دكتوراة