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.
Embedded Finance: The Opportunity Ahead
By Eduardo Martinez Garcia, CEO & Co-founder of Toqio
The current financial landscape is undergoing a significant transformation, disrupting the long-established dominion of major banks and other large financial institutions. Embedded finance, a concept that has thrived in the realm of digital consumer products, is now steadily infiltrating the corporate domain, poised to revolutionize the financial sector further.
This paradigm shift is manifesting in a multitude of ways, with digital embedded finance increasingly becoming an integral part of corporate digital offerings. Distributor payment processing, lending services for suppliers, and supply chain financing are all becoming commonplace – the versatility of corporate embedded finance knows no bounds. Despite the diverse applications the core objectives remain consistent, including enhancing B2B processes, mitigating risks, and fortifying business relationships.
Corporate embedded finance promises to deliver substantial value over the course of the next decade. A burgeoning opportunity beckons, estimated to be worth an astonishing USD 3.7 trillion over the next five years alone. Remarkably, more than 50% of businesses have expressed a preference for cash flow financing through platforms rather than traditional banks, as per a report by McKinsey. The shift observed in consumer embedded finance adoption is creeping into the B2B landscape, and moving more quickly all the time. Consequently, if the high level of adoption of consumer embedded finance carries over into the B2B space, and it’s certainly expected to, we’re genuinely looking at the next big thing.
Customers are no longer passive passengers in their financial journeys; they have emerged as the navigators, steering the industry’s course while financial institutions focus on risk management. Banks and non-banking financial institutions (NBFIs) remain pivotal, but their control of products is waning. Companies, intimately acquainted with their customers and partners, possess a deeper understanding of their collaborative ecosystem. Consequently, they are better equipped to tailor their financial offerings to meet the needs of their business relationships.
Take Amazon, for instance, which has been offering loans to small businesses operating on its platform for years. Amazon evaluates risk based on a merchant’s payment history, sales volume, projected revenue, and other critical data points. This approach enables Amazon to provide additional value to its sellers while securing a foothold in the financing market. The close rapport Amazon shares with its small business partners positions it with substantially less risk compared to conventional banks.
Shopify has also ingeniously woven embedded finance into the very fabric of its offering. While its core service revolves around delivering an efficient, subscription-based e-commerce platform, it also provides payment processing and lending services, among a myriad of other financial solutions. Shopify boasts an extensive reservoir of data, allowing it to make informed decisions about the financial products it can offer to merchants, all while keeping risk to a minimum.
Historically, financial products have fallen within the purview of major corporations either through partnerships with third parties or in-house service creation. Nevertheless, the rise of digital channels has expedited the decentralization of financial services, and it’s snowballing. Companies spanning various industries, from automakers to retail giants, are recognizing the immense untapped potential in taking control of many functions traditionally handled by financial institutions. While financial institutions will endure, their role is evolving. Their strengths are assessment, management, and specialized services. They must pivot towards analyzing data from a multitude of sources, diving into data lakes to provide genuinely useful risk assessments.
Incumbent banks have demonstrated their staying power and adaptability time and time again, mostly due to being able to leverage their size and relative dependability. They’ve capitalized on their vast customer bases, regulatory compliance expertise, and extensive branch networks to maintain a competitive edge. Additionally, incumbent banks have finally begun to recognize the need to adapt to changing customer expectations and digital transformation.
The future of core banking is likely to strike a balance between fintech disruptors and established incumbents. Collaboration and partnerships between incumbents and fintech startups tend to drive innovation, offering customers cutting-edge digital experiences. Big banks are probably going to find their place in the market modified, and not necessarily in a bad way.
Incumbents and financial behemoths have long been oriented toward long-term financial products, such as 30-year mortgages. But what about short-term business loans? Consider the restaurateur seeking a swift three-month loan to renovate a kitchen or the farmer unable to repay a loan until the crops are harvested and sold, a process spanning six months or more. For traditional banks, these scenarios represent short-term debts, a situation they tend to avoid. This presents a prime opportunity for companies to tailor products that cater to these specific needs, allowing them to define the space.
The evolution of embedded finance is commencing with payments, as it represents one of the least regulated segments in finance, offering ample room for innovation. Credit, closely trailing payments in significance, holds paramount importance. What’s really exciting is that as corporate giants blaze the trail, they pave the way for others to follow suit. This means that small and medium-sized enterprises will also be able to get involved, making embedded finance more inclusive within a given business ecosystem.
Eduardo Martinez Garcia is the CEO & Co-Founder of Toqio. He is an avid entrepreneur who has set up and run successful global ventures in the UK, Spain, and South Africa over the course of the last 20 years.
Hype, Hysteria & Hope: AI’s Evolutionary Journey and What it Means for Financial Services
Source: Finance Derivative
Written by Gabriel Hopkins, Chief Product Officer at Ripjar
Almost a year to the day since ChatGPT launched, the hype, hysteria, and hope around the technology shows little signs of abating. In recent weeks OpenAI chief Sam Altman was removed from his position, only to return some days later. Rishi Sunak hosted world leaders at the UK’s AI Safety Summit, interviewing the likes of Elon Musk in front of an assembly of world leaders and tech entrepreneurs. While behind the scenes, AI researchers are rumoured to be close to even more breakthroughs within weeks.
What does it all mean for those industries that want to benefit from AI but are unsure of the risks?
It’s possible that some forms of machine learning – what we used to call AI – have been around for a century. Since the early 1990s, those tools have been a key operational element of some banking, government, and corporate processes, while being notably absent from others.
So why the uneven adoption? Generally, that has been related to risk. For instance, AI tools are great for tasks like fraud detection. It’s a well-established that an algorithm can do things that analysts simply can’t by reviewing vast swathes of data in milliseconds. And that has become the norm, particularly because it is not essential to understand each and every decision in detail.
Other processes have been more resistant to change. Usually, that’s not because an algorithm couldn’t do better, but rather because – in areas such as credit scoring or money laundering detection – the potential for unexpected biases to creep in is unacceptable. That is particularly acute in credit scoring when a loan or mortgage can be declined due to non-financial characteristics.
While the adoption of older AI techniques has been progressing year after year, the arrival of Generative AI, characterised by ChatGPT, has changed everything. The potential for the new models – both good and bad – is huge, and commentary has divided accordingly. What is clear is that no organisation wants to miss out on the upside. Despite the talk about Generative and Frontier models, 2023 has been brimming with excitement about the revolution ahead.
A primary use case for AI in the financial crime space is to detect and prevent fraudulent and criminal activity. Efforts are generally concentrated around two similar but different objectives. These are thwarting fraudulent activity – stopping you or your relative from getting defrauded – and adhering to existing regulatory guidelines to support anti-money laundering (AML), and combatting the financing of terrorism (CFT).
Historically, AI deployment in the AML and CFT areas has faced concerns about potentially overlooking critical instances compared to traditional rule-based methods. Within the past decade, and other regulators initiated a shift by encouraging innovation to help with AML and CFT cases. Despite the use of machine learning models in fraud prevention over the past decades, adoption in AML/CFT has been much slower with a prevalence for headlines and predications over actual action. The advent of Generative AI looks likely to change that equation dramatically.
One bright spot for AI in compliance over the last 5 years, has been in customer and counterparty screening, particularly when it comes to the vast quantities of data involved in high-quality Adverse Media (aka Negative News) screening where organisations look for the early signs of risk in the news media to protect themselves from potential issues.
The nature of high-volume screening against billions of unstructured documents has meant that the advantages of machine learning and artificial intelligence far outweigh the risks and enable organisations to undertake checks which would simply not be possible otherwise.
Now banks and other organisations want to go a stage further. As Generation AI models start to approach AGI (Artificial General Intelligence) where they can routinely outperform human analysts, the question is when, and not if, they can use the technology to better support decisions and potentially even make the decisions unilaterally.
AI Safety in Compliance
The 2023 AI Safety Summit was a significant milestone in acknowledging the importance of AI. The Summit resulted in 28 countries signing a declaration to continue meetings to address AI risks. The event led to the inauguration of the AI Safety Institute, which will contribute to future research and collaboration to ensure its safety.
Though there are advantages to having an international focus on the AI conversation, the GPT transformer models were the primary focus areas during the Summit. This poses a risk of oversimplifying or confusing the broader AI spectrum for unaccustomed individuals. There is a broad range of AI technologies with hugely varying characteristics. Regulators and others need to understand that complexity. Banks, government agencies, and global companies must exert a thoughtful approach to AI utilisation. They must emphasise its safe, careful, and explainable use when leveraged inside and outside of compliance frameworks.
The Road Ahead
The compliance landscape demands a review of standards for responsible AI use. It is essential to establish best practices and clear objectives to help steer organisations away from hastily assembled AI solutions that compromise accuracy. Accuracy, reliability, and innovation are equally important to mitigate fabrication or potential misinformation.
Within the banking sector, AI is being used to support compliance analysts already struggling with time constraints and growing regulatory responsibilities. AI can significantly aid teams by automating mundane tasks, augmenting decision-making processes, and enhancing fraud detection.
The UK can benefit from the latest opportunity. We should cultivate an innovation ecosystem with is receptive to AI innovation across fintech, regtech, and beyond. Clarity from government and thought leaders on AI tailored to practical implementations in the industry is key. We must also be open to welcoming new graduates from the growing global talent pool for AI to fortify the country’s position in pioneering AI-driven solutions and integrating them seamlessly. Amid industry change, prioritising and backing responsible AI deployment is crucial for the successful ongoing battle against all aspects of financial crime.
Using AI to support positive outcomes in alternative provision
By Fleur Sexton
Fleur Sexton, Deputy Lieutenant West Midlands and CEO of dynamic training provider, PET-Xi, with a reputation for success with the hardest to reach,
discusses using AI to support excluded pupils in alternative provision (AP)
Exclusion from school is often life-changing for the majority of vulnerable and disadvantaged young people who enter alternative provision (AP). Many face a bleak future, with just 4% of excluded pupils achieving a pass in English and maths GCSEs, and 50% becoming ‘not in education, employment or training’ (NEET) post-16.
Often labelled ‘the pipeline to prison’, statistics gathered from prison inmates are undeniably convincing: 42% of prisoners were expelled or permanently excluded from school; 59% truanted; 47% of those entering prison have no school qualifications. With a prison service already in crisis, providing children with the ‘right support, right place, right time’, is not just an ethical response, it makes sound financial sense. Let’s invest in education, rather than incarceration.
‘Persistent disruptive behaviour’ – the most commonly cited reason for temporary or permanent exclusion from mainstream education – often results from unmet or undiagnosed special educational needs (SEN) or social, emotional and mental health (SEMH) needs. These pupils find themselves unable to cope in a mainstream environment, which impacts their mental health and personal wellbeing, and their abilities to engage in a positive way with the curriculum and the challenges of school routine. A multitude of factors all adding to their feelings of frustration and failure.
Between 2021/22 and 2022/23, councils across the country recorded a 61% rise in school exclusions, with overall exclusion figures rising by 50% compared to 2018/19. The latest statistics from the Department for Education (DfE), show pupils with autism in England are nearly three times as likely to be suspended than their neurotypical peers. With 82% of young people in state-funded alternative provision (AP) with identified special educational needs (SEN) and social emotional and mental health (SEMH) needs, for many it is their last chance of gaining an education that is every child’s right.
The Department for Education’s (DfE) SEND and AP Improvement Plan (March 2023).reported, ‘82% of children and young people in state-place funded alternative provision have identified special educational needs (SEN) 2, and it (AP) is increasingly being used to supplement local SEND systems…’
Some pupils on waiting lists for AP placements have access to online lessons or tutors, others are simply at home, and not receiving an education. In oversubscribed AP settings, class sizes have had to be increased to accommodate demand, raising the pupil:teacher ratio, and decreasing the levels of support individuals receive. Other unregulated settings provide questionable educational advantage to attendees.
AI can help redress the balance and help provide effective AP. The first challenge for teachers in AP is to engage these young people back into learning. If the content of the curriculum used holds no relevance for a child already struggling to learn, the task becomes even more difficult. As adults we rarely engage with subjects that do not hold our interest – but often expect children to do so.
Using context that pupils recognise and relate to – making learning integral to the real world and more specifically, to their reality, provides a way in. A persuasive essay about school uniforms, may fire the debate for a successful learner, but it is probably not going to be a hot topic for a child struggling with a chaotic or dysfunctional home life. If that child is dealing with high levels of adversity – being a carer for a relative, keeping the household going, dealing with pressure to join local gangs, being coerced into couriering drugs and weapons around the neighbourhood – school uniform does not hold sway. It has little connection to their life.
Asking the group about the subjects they feel strongly about, or responding to local news stories from their neighbourhoods, and using these to create tasks, will provide a more enticing hook to pique their interest. After all, in many situations, the subject of a task is just the ‘hanger’ for the skills they need to learn – in this case, the elements of creating a persuasive piece, communicating perspectives and points of view.
Using AI, teachers have the capacity to provide this individualised content and personalised instruction and feedback, supporting learners by addressing their needs and ‘scaffolding’ their learning through adaptive teaching.
If the learner is having difficulty grasping a concept – especially an abstract one – AI can quickly produce several relevant analogies to help illustrate and explain. It can also be used to develop interactive learning modules, so the learner has more control and ownership over their learning. When engaged with their learning, pupils begin to build skills, increasing their confidence and commitment.
Identifying and discussing these skills and attitudes towards learning, with the pupil reflecting on how they learn and the ways they learn best, also gives them more agency and autonomy, thinking metacognitively.
Gaps in learning are often the cause of confusion, misunderstandings and misconceptions. If a child has been absent from school they may miss crucial concepts that form the building blocks to more complex ideas later in their school career. Without providing the foundations by filling in these gaps and unravelling the misconceptions, new learning may literally be impossible for them to understand, increasing frustration and feelings of failure. AI can help identify those gaps, scaffold learning and build understanding.
AI is by no means a replacement for teachers or teaching assistants, it is purely additional support. Coupled with approaches that promote engagement with learning, AI can enable these disadvantaged young people to access an education previously denied them.
According to the DfE, ‘All children are entitled to receive a world-class education that allows them to reach their potential and live a fulfilled life, regardless of their background.’ AI can help support the most disadvantaged young people towards gaining the education they deserve, and creating a pathway towards educational and social equity.