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Getting ready for VAT digitisation: automation is key

Source: Finance Derivative

hristiaan Van Der Valk, Vice President for Strategy and Regulatory at Sovos, says technology will power real strategic success for companies required to follow continuous transaction controls (CTCs).

A growing number of governments and businesses around the world are adopting digital-first approaches for a multitude of processes, resulting in a need to move away from traditional paper-based invoicing and embrace real-time tax reporting. This trend has been largely led by Latin American countries such as Brazil, Chile and Mexico. Through adopting real-time reporting via electronic invoicing systems, they have been able to better understand their economies, reduce fraud, and close VAT gaps.

The shift to continuous transaction controls (CTCs) allows transaction data to be automatically streamed to governments, reducing the need for resource-intensive business systems and document audits for tax administrations. Through the use of rich, standardised data, tax authorities are able to compute a business’s tax liability. Businesses are generally not required to be heavily involved in this process.

With this requirement – combined with invoicing – businesses would be able to avoid filing periodic tax returns, relieving them of the burden of running VAT compliance teams and filing reports that bring no benefit. The practice, however, calls for a more comprehensive data management approach and proactive data reconciliation across different sources of government-controlled transaction data. For this reason, companies need access to a high-quality dataset in case they must challenge government-determined tax liability.

It can be problematic to have poor data quality in a VAT environment that relies heavily on legacy reporting. For example, there have been instances in which reports were inconsistent or didn’t correspond to accounting data in audits. Consequently, fines or penalties may be imposed. However, in the world of CTCs the consequences of data quality issues are of a very different magnitude. Your financial and physical supply and demand chains can practically grind to a standstill if your data isn’t approved by the tax administration – especially in nations where the tax administration ‘clears’ the invoice in real-time such as in Italy, Mexico and Brazil.

Many businesses with responsibilities in VAT jurisdictions are missing something important here. Beginning to utilise automation and other more specialised tools for producing VAT returns is a critical step toward harnessing the benefits from the mandated transition to CTCs as opposed to focusing on the challenges.

Manual is outdated

A lot of businesses are still using manual processes like spreadsheets to manage their VAT compliance, which essentially involves the time-consuming production and submission of VAT returns.

Through implementing technology like automated rules in software, companies can maximise the validity of VAT data. As well as simplifying and re-risking VAT reporting activities, the effort required to design the steps to enhance data using automated rules engines means establishing structured definitions of ‘what’s wrong with your transaction data?’ These definitions can then be used to identify the cause of quality concerns in upstream business processes and address them in order to dramatically improve CTC readiness.

For many businesses, the majority of quality concerns are down to the manual and paper-based processes used in internal workflows and trading partner relationships. Therefore, automation will play a vital role in properly preparing for CTCs.

Preparing data in this manner for VAT enforcement means that a business is paving the way for a more data-driven approach to compliance in general. Companies will increasingly be required to coordinate data being submitted to tax administrations automatically from a range of business process and accounting systems, once CTCs and other VAT digitisation initiatives become operational.

Keeping up to date with the expanding scope of information that is handed over to tax administrations in these automated data transmissions is crucial, so that companies can maintain a level of control over the image of their business operations that is constructed for the tax authorities.

As well as this, a business may benefit from this insight across data encompassing the full supply chain and transactions.  For instance, this information gathered could be turned into tactics to help with strategic planning.

Business leaders may reduce expenses, boost resilience, and improve controls by automating tax and business operations and adopting a data-driven approach to compliance, allowing for a more accurate and detailed understanding of granular reporting needs.

Organisations should prioritise the building of dashboards utilising modern analytics tools to prepare for this huge transition. It’s also important to have a well-organised evidence base with clean digital archives. Technology and the insight it brings will be the driving factor for real strategic success as economies recover from the pandemic.

Data flow is key

As tax authorities and governments work to reduce VAT gaps, greater visibility into corporate databases is at the top of their agenda. This is accomplished through the government’s digitisation of all tax reporting, in which data is delivered at regular intervals that correspond to the flow of transactions and the government’s data requirements.

It is imperative that transaction data, relevant primarily for VAT purposes (though not exclusively), be received in a transactional manner. Meanwhile, other types of information, like payment data or inventory movement, may be requested on a weekly or monthly basis, whereas broader accounting data might be requested more frequently.

The introduction of CTCs should not be viewed as an IT formality, but as the first step in tax administrations gaining easy, timely and effective access to source data. The digitisation of tax will enable administrations to access data on a regular basis, as well as at a granular level.

As companies transition from manual data entry into this new world of automated data exchange, they should concentrate on why this change is important rather than how it is happening. The real prize here is not getting the ‘plumbing’ to work according to government specifications; focusing on this ‘how’ question means that companies may be missing out on a potentially critical business enabler, but equally they may be inadvertently setting themselves up for much higher levels of compliance risk.

With the introduction of CTCs and various forms of detailed digital reporting, companies should be prepared to be exposed to much more stringent audits. The reason for this is that data quality or consistency issues will gradually become more transparent to tax administration teams, which will increasingly be enabled to respond to even the smallest inconsistencies that may previously have gone under the radar with surgical precision.

The higher level of visibility allows tax authorities to cross-check more company data, its trading partners and third parties’ data. These abilities will be vastly improved as more governments complement CTC requirements with mandates for SAF-T and similar electronic auditing requirements. Through thorough analysis of this growing mass of real-time and historic data, a firm’s operations can be fully understood.

Successfully adapting to CTCs means investing in the journey rather than the destination. As everything becomes more digitised, organisations must stay on top of these changes and maintain the same level of data insights as tax authorities do. There will be a growing need for this as more countries introduce CTC regimes (both France and Germany are on the horizon).

Adapting business tools to deliver better data insights is essential to facilitating tax digitisation, both to satisfy global tax authorities and to achieve a competitive advantage in the market. In short, companies should remain fully alert and prepared to ensure a smooth transition and successful outcome of CTCs, which are the logical next step on the road to business transparency.

The domino effect of CTCs

The willingness of autonomous governments to accept digital tax reporting will determine how widespread its implementation becomes. Following more than a decade of success with these methods in Latin America, governments all over Europe, for example, have made major moves toward introducing CTCs. In doing so, there is a great deal of preparation that international companies need to do which can take a considerable amount of time and resources.

In all jurisdictions with indirect tax systems, moving toward increasingly digitised tax controls is the only path. With real-time data, governments can better understand and analyse their country’s economic health, while also enhancing fiscal controls and reducing fraud. It’s just a matter of time until these digital programmes become standard practice on a global level, as countries all across the world begin to recognise their success in reducing fraud, increasing efficiency and closing VAT gaps.

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Business

Driving business success in today’s data-driven world through data governance

Source: Finance derivative

Andrew Abraham, Global Managing Director, Data Quality, Experian

It’s a well-known fact that we are living through a period of digital transformation, where new technology is revolutionising how we live, learn, and work. However, what this has also led to is a significant increase in data. This data holds immense value, yet many businesses across all sectors struggle to manage it effectively. They often face challenges such as fragmented data silos or lack the expertise and resources to leverage their datasets to the fullest.

As a result, data governance has become an essential topic for executives and industry leaders. In a data-driven world, its importance cannot be overstated. Combine that with governments and regulatory bodies rightly stepping up oversight of the digital world to protect citizens’ private and personal data. This has resulted in businesses also having to comply e with several statutes more accurately and frequently.

We recently conducted some research to gauge businesses’ attitudes toward data governance in today’s economy. The findings are not surprising: 83% of those surveyed acknowledged that data governance should no longer be an afterthought and could give them a strategic advantage. This is especially true for gaining a competitive edge, improving service delivery, and ensuring robust compliance and security measures.

However, the research also showed that businesses face inherent obstacles, including difficulties in integration and scalability and poor data quality, when it comes to managing data effectively and responsibly throughout its lifecycle.

So, what are the three fundamental steps to ensure effective data governance?

Regularly reviewing Data Governance approaches and policies

Understanding your whole data estate, having clarity about who owns the data, and implementing rules to govern its use means being able to assess whether you can operate efficiently and identify where to drive operational improvements. To do that effectively, you need the right data governance framework. Implementing a robust data governance framework will allow businesses to ensure their data is fit for purpose, improves accuracy, and mitigates the detrimental impact of data silos.

The research also found that data governance approaches are typically reviewed annually (46%), with another 47% reviewing it more frequently. Whilst the specific timeframe differs for each business, they should review policies more frequently than annually. Interestingly, 6% of companies surveyed in our research have it under continual review.

Assembling the right team

A strong team is crucial for effective cross-departmental data governance.  

The research identified that almost three-quarters of organisations, particularly in the healthcare industry, are managing data governance in-house. Nearly half of the businesses surveyed had already established dedicated data governance teams to oversee daily operations and mitigate potential security risks.

This strategic investment highlights the proactive approach to enhancing data practices to achieve a competitive edge and improve their financial performance. The emphasis on organisational focus highlights the pivotal role of dedicated teams in upholding data integrity and compliance standards.

Choose data governance investments wisely

With AI changing how businesses are run and being seen as a critical differentiator, nearly three-quarters of our research said data governance is the cornerstone to better AI. Why? Effective data governance is essential for optimising AI capabilities, improving data quality, automated access control, metadata management, data security, and integration.

In addition, almost every business surveyed said it will invest in its data governance approaches in the next two years. This includes investing in high-quality technologies and tools and improving data literacy and skills internally.  

Regarding automation, the research showed that under half currently use automated tools or technologies for data governance; 48% are exploring options, and 15% said they have no plans.

This shows us a clear appetite for data governance investment, particularly in automated tools and new technologies. These investments also reflect a proactive stance in adapting to technological changes and ensuring robust data management practices that support innovation and sustainable growth.

Looking ahead

Ultimately, the research showed that 86% of businesses recognised the growing importance of data governance over the next five years. This indicates that effective data governance will only increase its importance in navigating digital transformation and regulatory demands.

This means businesses must address challenges like integrating governance into operations, improving data quality, ensuring scalability, and keeping pace with evolving technology to mitigate risks such as compliance failures, security breaches, and data integrity issues.

Embracing automation will also streamline data governance processes, allowing organisations to enhance compliance, strengthen security measures, and boost operational efficiency. By investing strategically in these areas, businesses can gain a competitive advantage, thrive in a data-driven landscape, and effectively manage emerging risks.

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The Benefits of EV Salary Sacrifice: A Guide for Employers and Employees

As the UK government continues to push for greener initiatives, electric cars have become increasingly popular. The main attraction for both employers and employees is the EV salary sacrifice scheme.

By participating in an EV salary sacrifice scheme, both employers and employees can enjoy cost savings and contribute to environmental sustainability along the way! This article will delve into the specifics of how these schemes operate, the financial advantages they offer, and the broader positive impacts on sustainability.

We will provide a comprehensive overview of the mechanics behind EV salary sacrifice schemes and discuss the various ways in which they benefit both employees and employers, ultimately supporting the transition to a greener future in the UK.

What is an EV Salary Sacrifice Scheme?

An EV salary sacrifice scheme is a flexible financial arrangement that permits employees to lease an EV through their employer. The key feature of this scheme is that the leasing cost is deducted directly from the employee’s gross salary before tax and National Insurance contributions are applied. By reducing the taxable income, employees can benefit from substantial savings on both tax and National Insurance payments. This arrangement not only makes EVs more affordable for employees but also aligns with governmental incentives to reduce carbon emissions.

For employers, implementing an EV salary sacrifice scheme can lead to cost efficiencies as well. The reduction in National Insurance contributions on the employee’s reduced gross salary can offset some of the costs associated with administering the scheme. Additionally, such programmes can enhance the overall benefits package offered by the employer, making the company more attractive to prospective and current employees.

Benefits for Employees

1. Tax and National Insurance Savings

By opting for an EV salary sacrifice scheme, employees can benefit from reduced tax and National Insurance contributions. Since the lease payments are made from the gross salary, the taxable income decreases, resulting in substantial savings.

2. Access to Premium EVs

Leading salary sacrifice car schemes often provide access to high-end electric vehicles that might be otherwise unaffordable. Employees can enjoy the latest EV models with advanced features, contributing to a more enjoyable and environmentally friendly driving experience.

3. Lower Running Costs

Electric vehicles typically have lower running costs compared to traditional petrol or diesel cars. With savings on fuel, reduced maintenance costs, and exemptions from certain charges (such as London’s Congestion Charge), employees can enjoy significant long-term financial benefits.

4. Environmental Impact

Driving an electric vehicle reduces the carbon footprint and supports the UK’s goal of achieving net-zero emissions by 2050. Employees can take pride in contributing to a cleaner environment.

Benefits for Employers

1. Attract and Retain Talent

Offering an EV salary sacrifice scheme can enhance an employer’s benefits package, making it more attractive to potential recruits. It also helps in retaining current employees by providing them with valuable and cost-effective benefits.

2. Cost Neutrality

For employers, EV salary sacrifice schemes are often cost-neutral. The savings on National Insurance contributions can offset the administrative costs of running the scheme, making it an economically viable option.

3. Corporate Social Responsibility (CSR)

Implementing an EV salary sacrifice scheme demonstrates a commitment to sustainability and corporate social responsibility. This can improve the company’s public image and align with broader environmental goals.

4. Employee Well-being

Providing employees with a cost-effective means to drive electric vehicles can contribute to their overall well-being. With lower running costs and the convenience of driving a new EV, employees may experience reduced financial stress and increased job satisfaction.

How to Implement an EV Salary Sacrifice Scheme

1. Assess Feasibility

Evaluate whether an EV salary sacrifice scheme is feasible for your organisation. Consider the number of interested employees, potential cost savings, and administrative requirements.

2. Choose a Provider

Select a reputable provider that offers a range of electric vehicles and comprehensive support services. Ensure they can handle the administrative tasks and provide a seamless experience for both the employer and employees.

3. Communicate the Benefits

Educate your employees about the advantages of the scheme. Highlight the financial savings, environmental impact, and access to premium EV models. Provide clear guidance on how they can participate in the programme.

4. Monitor and Review

Regularly review the scheme’s performance to ensure it continues to meet the needs of your employees and the organisation. Gather feedback and make adjustments as necessary to enhance the programme’s effectiveness.

Conclusion

The EV salary sacrifice scheme offers a win-win situation for both employers and employees in the UK. With significant financial savings, access to premium vehicles, and a positive environmental impact, it’s an attractive option for forward-thinking organisations. By implementing such a scheme, employers can demonstrate their commitment to sustainability and employee well-being, while employees can enjoy the benefits of driving an electric vehicle at a reduced cost.

Adopting an EV salary sacrifice scheme is a step towards a greener, more sustainable future for everyone.

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Business

Machine Learning Interpretability for Enhanced Cyber-Threat Attribution

Source: Finance Derivative

By: Dr. Farshad Badie,  Dean of the Faculty of Computer Science and Informatics, Berlin School of Business and Innovation

This editorial explores the crucial role of machine learning (ML) in cyber-threat attribution (CTA) and emphasises the importance of interpretable models for effective attribution.

The Challenge of Cyber-Threat Attribution

Identifying the source of cyberattacks is a complex task due to the tactics employed by threat actors, including:

  • Routing attacks through proxies: Attackers hide their identities by using intermediary servers.
  • Planting false flags: Misleading information is used to divert investigators towards the wrong culprit.
  • Adapting tactics: Threat actors constantly modify their methods to evade detection.

These challenges necessitate accurate and actionable attribution for:

  • Enhanced cybersecurity defences: Understanding attacker strategies enables proactive defence mechanisms.
  • Effective incident response: Swift attribution facilitates containment, damage minimisation, and speedy recovery.
  • Establishing accountability: Identifying attackers deters malicious activities and upholds international norms.

Machine Learning to the Rescue

Traditional machine learning models have laid the foundation, but the evolving cyber threat landscape demands more sophisticated approaches. Deep learning and artificial neural networks hold promise for uncovering hidden patterns and anomalies. However, a key consideration is interpretability.

The Power of Interpretability

Effective attribution requires models that not only deliver precise results but also make them understandable to cybersecurity experts. Interpretability ensures:

  • Transparency: Attribution decisions are not shrouded in complexity but are clear and actionable.
  • Actionable intelligence: Experts can not only detect threats but also understand the “why” behind them.
  • Improved defences: Insights gained from interpretable models inform future defence strategies.

Finding the Right Balance

The ideal model balances accuracy and interpretability. A highly accurate but opaque model hinders understanding, while a readily interpretable but less accurate model provides limited value. Selecting the appropriate model depends on the specific needs of each attribution case.

Interpretability Techniques

Several techniques enhance the interpretability of ML models for cyber-threat attribution:

  • Feature Importance Analysis: Identifies the input data aspects most influential in the model’s decisions, allowing experts to prioritise investigations.
  • Local Interpretability: Explains the model’s predictions for individual instances, revealing why a specific attribution was made.
  • Rule-based Models: Provide clear guidelines for determining the source of cyber threats, promoting transparency and easy understanding.

Challenges and the Path Forward

The lack of transparency in complex ML models hinders their practical application. Explainable AI, a field dedicated to making models more transparent, holds the key to fostering trust and collaboration between human and machine learning. Researchers are continuously refining interpretability techniques, with the ultimate goal being a balance between model power and decision-making transparency.

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