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The generative AI revolution is here – but is your cloud network ready to embrace it?

Paul Gampe, Chief Technology Officer, Console Connect

Generative Artificial Intelligence is inserting itself into nearly every sector of the global economy as well as many aspects of our lives. People are already using this groundbreaking technology to query their bank bills, request medical prescriptions, and even write poems and university essays.

In the process, generative AI has the potential to unlock trillions of dollars in value for businesses and radically transform the way we work. In fact, current predictions suggest generative AI could automate up to 70 percent of employees’ time today.

Paul Gampe

But regardless of the application or industry, the impact of generative AI can be most keenly felt in the cloud computing ecosystem.

As companies rush to leverage this technology in their cloud operations, it is essential to first understand the network connectivity requirements – and the risks – before deploying generative AI models safely, securely, and responsibly.

Data processing

One of the primary connectivity requirements for training generative AI models in public cloud environments is affordable access the scale of datasets. By their very definition, large language models (LLM) are extremely large. To train these LLMs requires vast amounts of data and hyper-fast compute      and the larger the dataset the more the demand for computing power.

The enormous processing power required to train these LLMs is only one part of the jigsaw. You also need to manage the sovereignty, security, and privacy requirements of the data transiting in your public cloud. Given that 39 percent of businesses experienced a data breach in their cloud environment in 2022, it makes sense to explore the private connectivity products on the market which have been designed specifically for high performance and AI workloads.

Regulatory trends

Companies should pay close attention to the key public policies and regulation trends which are rapidly emerging around the AI landscape. Think of a large multinational bank in New York that has 50 mainframes on its premises where they keep their primary computing capacity; they want to do AI analysis on that data, but they cannot use the public internet to connect to these cloud environments because many of their workloads have regulatory constraints. Instead, private connectivity affords them the ability to get to where the generative AI capability exists and sits within the regulatory frameworks of their financing industry.

Even so, the maze of regulatory frameworks globally is very complex and subject to change. The developing mandates of the General Data Protection Regulation (GDPR) in Europe, as well as new GDPR-inspired data privacy laws in the United States, have taken a privacy-by-design approach whereby companies must implement techniques such as data mapping and data loss prevention to make sure they know where all personal data is at all times and protect it accordingly.

Sovereign borders

As the world becomes more digitally interconnected, the widespread adoption of generative AI technology will likely create long-lasting challenges around data sovereignty. This has already prompted nations to define and regulate their own legislation regarding where data can be stored, and where the LLMs processing that data can be housed.

Some national laws require certain data to remain within the country’s borders, but this does not necessarily make it more secure. For instance, if your company uses the public internet to transfer customer data to and from London on a public cloud service, even though it may be travelling within London, somebody can still intercept that data and route it elsewhere around the world.

As AI legislation continues to expand, the only way your company will have assurance of maintaining your sovereign border may be to use a form of private connectivity while the data is in transit. The same applies to AI training models on the public cloud; companies will need some type of connectivity from their private cloud to their public cloud where they do their AI training models, and then use that private connectivity to bring their inference models back.

Latency and network congestion
Latency is a critical factor in terms of interactions with people. We have all become latency sensitive, especially with the volume of voice and video calls that we experience daily, but the massive datasets used for training AI models can lead serious latency issues on the public cloud.

For instance, if you’re chatting with an AI bot that’s providing you customer service and latency begins to exceed 10 seconds, the dropout rate accelerates. Therefore, using the public internet to connect your customer-facing infrastructure with your inference models is potentially hazardous for a seamless online experience, and a change in response time could impact your ability to provide meaningful results.

Network congestion, meanwhile, could impact your ability to build models on time. If you have significant congestion in getting your fresh data into your LLMs it’s going to start to backlog, and you won’t be able to achieve the learning outcomes that you’re hoping for. The way to overcome this is by having large pipes to ensure that you don’t encounter congestion in moving your primary data sets into where you’re training your language model.

Responsible governance

One thing everybody is talking about right now is governance. In other words, who gets access to the data and where is the traceability of the approval of that data available?

Without proper AI governance, there could be high consequences for companies that may result in commercial and reputational damage. A lack of supervision when implementing generative AI models on the cloud could easily lead to errors and violations, not to mention the potential exposure of customer data and other proprietary information. Simply put, the trustworthiness of generative AI all depends on how companies use it.

Examine your cloud architecture

Generative AI is a transformative field with untold opportunities for countless businesses, but IT leaders cannot afford to get their network connectivity wrong before deploying its applications.

Remember, data accessibility is everything when it comes to generative AI, so it is essential to define your business needs in relation to your existing cloud architecture. Rather than navigating the risks of the public cloud, the high-performance flexibility of a Network-as-a-Service (NaaS) platform can provide forward-thinking companies with a first-mover advantage.

The agility of NaaS connectivity makes it simpler and safer to adopt AI systems by interconnecting your clouds with a global network infrastructure that delivers fully automated switching and routing on demand. What’s more, a NaaS solution also incorporates the emerging network technology that supports the governance requirements of generative AI for both your broader business and the safeguarding of your customers.

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Business

Empowering banks to protect consumers: The impact of the APP Fraud mandate

Source: Finance Derivative

Thara Brooks, Market Specialist, Fraud, Financial Crime & Compliance at FIS

On the 7th October last year, the APP (Authorised Push Payment) fraud reimbursement mandate came into effect in the UK. The mandate aims to protect consumers, but it has already come under immense scrutiny, receiving both support and criticism from all market sectors. But what does it mean for banks and their customers?

Fraud has become a growing concern for the UK banking system and its consumers. According to the ICAEW, the total value of UK fraud stood at £2.3bn in 2023, a 104% increase since 2022, with estimates that the evolution of AI will lead to even bigger challenges. As the IMF points out, greater digitalisation brings greater vulnerabilities, at a time when half of UK consumers are already “obsessed” with checking their banking apps and balances.

These concerns have contributed to the implementation of the PSR’s (Payment Systems Regulator) APP fraud mandate, which was implemented to reimburse the victims of APP fraud. APP fraud occurs when somebody is tricked into authorising a payment from their own bank account. Unlike more traditional fraud, such as payments made from a stolen bank card, APP fraud previously fell outside the scope of conventional fraud protection, as the transaction is technically “authorised” by the victim.

The £85,000 Debate: A controversial adjustment

The regulatory framework for the APP fraud mandate was initially introduced in May 2022. The maximum level of mandatory reimbursement was originally set at £415,000 per claim. The PSR significantly reduced the maximum reimbursement value to £85,000 when the mandate came into effect, however, causing widespread controversy.

According to the PSR, the updated cap will see over 99% of claims (by volume) being covered, with an October review highlighting just 18 instances of people being scammed for more than £415,000, and 411 instances of more than £85,000, from a total of over 250,000 cases throughout 2023. “Almost all high value scams are made up of multiple smaller transactions,” the PSR explains, “reducing the effectiveness of transaction limits as a tool to manage exposure.”

The reduced cap makes a big difference on multiple levels. For financial institutions and payment service providers (PSPs), the lower limit means they’re less exposed to high-value claims. The reduced exposure to unlimited high-value claims has the potential to lower compliance and operational costs, while the £85,000 cap aligns with the Financial Services Compensation Scheme (FSCS) threshold, creating broader consistency across financial redress schemes.

There are naturally downsides to the lower limit, with critics highlighting significant financial shortfalls for victims of high-value fraud. The lower cap may reduce public confidence in the financial system’s ability to protect against fraud, particularly for those handling large sums of money, while small businesses, many of which often deal with large transaction amounts, may find the cap insufficient to cover losses.

The impact on PSPs and their customers

With PSPs responsible for APP fraud reimbursement, institutions need to take the next step when it comes to fraud detection and prevention to minimise exposure to claims within the £85,000 cap. Customers of all types are likely to benefit from more robust security as a result.

The Financial Conduct Authority’s (FCA’s) recommendations include strengthening controls during onboarding, improving transaction monitoring to detect suspicious activity, and optimising reporting mechanisms to enable swift action. Such controls are largely in line with the PSR’s own recommendations, with the institution setting out a number of steps in its final policy statement in December 2023 to mitigate APP scam risks.

These include setting appropriate transaction limits, improving ‘know your customer’ controls, strengthening transaction-monitoring systems and stopping or freezing payments that PSPs consider to be suspicious for further investigation.

All these measures will invariably improve consumer experience, increasing customers’ confidence to transact online safely, as well as giving them peace of mind with quicker reimbursement in case things go awry.

Going beyond the APP fraud mandate

If the PSR’s mandate can steer financial institutions towards implementing more robust security practices, it can only be a good thing. It’s not the only tool that’s shaping the financial security landscape, however.

In October 2024, the UK government introduced new legislation granting banks enhanced powers to combat fraud. An optional £100 excess on fraud claims has been introduced to encourage customer caution and combat moral hazards, while the Treasury has strengthened prevention measures by handing out new powers to high street banks to delay and investigate payments suspected of being fraudulent by 3 days. The extended processing time for suspicious payments may lead to delays in legitimate transactions, making transparent communication and robust safeguards essential to maintain consumer trust.

Further collaborative efforts, such as Meta’s partnership with UK banks through the Fraud Intelligence Reciprocal Exchange (FIRE) program, can also aid the fight against fraud. Thanks to direct intelligence sharing between financial institutions and the world’s biggest social media platform, FIRE enhances the detection and removal of fraudulent accounts across platforms such as Facebook and Instagram, not only disrupting scam operations, but also fostering a safer digital environment for users. The early stages of the pilot have led to action against thousands of scammer-operated accounts, with approximately 20,000 accounts removed based on shared data.

Additionally, education and awareness are crucial measures to protect consumers against APP fraud. Several high street banks have upgraded their banking channels to share timely content about the signs of potential scams, with increased public awareness helping consumers identify and avoid fraudulent schemes.

Improvements in policing strategies are also significantly contributing to the mitigation of APP fraud. Specialized fraud units within police forces have enhanced the precision and efficiency of investigations. The City of London Police and the National Fraud Intelligence Bureau are upgrading the technology for Action Fraud, providing victims with a more accessible and customer-friendly service. Collaborative efforts among police, banks, and telecommunications firms, exemplified by the work of the Dedicated Card and Payment Crime Unit (DCPCU), have enabled the swift exchange of information, facilitating the prompt apprehension of scammers.

How AI is expected to change the landscape

The coming months will be critical in assessing these changes, as institutions, businesses and the UK government work together to shape security against fraud in the ever-changing world of finance.

While fraud is a terrifyingly big business, it’s only likely to increase with the evolution of AI, making it even more critical that such changes are effective. According to PwC, “There is a real risk that hard-fought improvements in fraud defences could be undone if the right measures are not put in place to defend against fraud in an AI-enabled world.”

Chatbots can be used as part of phishing scams, for example, and AI systems can already read text and reproduce sampled voices, making it possible to send messages from “relatives” whose voices have been spoofed in a similar manner to deepfakes.

Along with other innovations, tools and collaborations, however, the APP fraud mandate, UK legislation and FIRE can all contribute towards redressing such technological advances. Together, this can give financial institutions a much-needed boost in the fight against fraud, providing a more secure future for customers.

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Business

After the tax deadline: Next steps for accountancy firms

Source: Finance Derivative

By Cameron Ford, UK General Manager of Silverfin

For many accountancy firms, tax season has ended. Now, leaders have a chance to reflect on their firm’s performance, how their people are feeling after the busiest period of the year, and consider how they might optimise people, processes and technology for the future.

As a former CFO with experience in senior accountancy roles across multiple firms, I know first-hand the challenges the year-end crunch presents. The intense weeks and months leading up to HMRC deadlines put immense pressure on infrastructure, exposing the limitations of legacy systems and the bottlenecks caused by manual workflows.

The post-busy-season presents a valuable opportunity to reassess and prepare for the next one. It’s also a time for firms to reflect on evolving client needs and proactively take action to deliver improved future outcomes. Firms should also evaluate whether their current technology is alleviating pressure during peak periods – or adding to the strain.

The risk of inaction

We are living in an era of profound technological change and fast-paced innovation. Firms that fail to evolve with the times will be left behind as more flexible and adaptive competitors race forward. The risk for slow movers is not just reduced competitiveness – its industry consolidation locking them out altogether.

For today’s leaders, the choice is no longer whether to transform – but which technologies to adopt. Accountancy firms now have access to an extensive array of powerful solutions. Data analytics tools are delivering insights to power better decision-making. Automation is streamlining workflows, reducing errors and freeing up valuable time to focus on strategic tasks. And the demand for fast, secure access to accurate and timely data is only growing.

Yet, as accountancy technology matures, new challenges are emerging that extend beyond traditional tech solutions as regulators become increasingly zealous. In the UK alone, two-thirds of current business taxes were introduced in the past decade, according to Thomson Reuters. That’s 13 out of 19 business taxes. The sheer pace of regulatory innovation demonstrates the need for accountancy firms to be agile and capable of transforming at speed, as their clients face an ever evolving and intricate tax landscape.

Future success depends on equipping firms with the ability to meet the demands of both customers and regulators, striking a balance that not only satisfies current expectations but also lays the groundwork for evolving future requirements.

Growing complexity

Corporate tax management illustrates the complex nature of today’s accounting landscape. Changing regulations, new post-Brexit tax requirements and global initiatives – such as the Organisation for Economic Cooperation and Development’s (OECD) Pillar Two, which introduces a global minimum corporate tax rate of 15% – are placing unprecedented demands on tax and accounting professionals.

The most effective response is to adopt specialised software that is designed to manage compliance and evolving regulatory requirements. While adopting new technology can seem daunting, it should be seen as an opportunity, not an obstacle. Yes, there may be initial friction and deployment challenges during the early stages of transformation, but these are temporary. As firms adapt to new tools and workflows, they unlock significant benefits – including streamlined processes, improved accuracy, and the ability to stay ahead of future changes in an increasingly dynamic tax environment.

AI transformation 

AI is rapidly emerging as a game-changing technology for many industries, including accountancy. It’s true value lies in acting as a partner and collaborator, taking on the heavy lifting of repetitive manual tasks, freeing up valuable hours so accountants have more time to focus on building stronger client relationships.

To be effective, AI relies on accurate real-time financial data that is easily accessed and stored in a standardised format. But before even considering training a model, firms must solve their lingering data issues. With multiple bookkeeping and large volumes of inconsistent and duplicated data, firms often struggle to extract meaningful insights.

Resolving these issues requires integrating data from various bookkeeping systems using techniques such as cloud syncs and AI enrichment tools. Data must also be stored in a unified format, properly catalogued and free from duplication to maximise its value.

By deploying AI on a foundation of clean, reliable and up-to-date data, accountancy firms can enhance their performance during peak seasons and better manage the pressures of increased demand. Plus, digital transformation and the deployment of advanced accountancy and compliance software also put firms in a stronger position to respond to new complexities and challenges that will inevitably emerge in this dynamic marketplace.

Peak season may be over, but now it’s time to plan for the next one, anticipating customer needs and proactively adapting to shifting demands.

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Business

Future-proofing financial services investment

Source: Finance Derivative

Adrian Ah-Chin-Kow, Global Commercial Director at leading software escrow company, Escode, discusses how the financial services sector can prepare for the increasing investment ahead of the government’s industrial growth strategy, Invest 2035, ensuring resilience against technological risks.

The UK’s proposed Invest 2035 strategy sets a bold vision: to elevate the UK as a global leader in high-growth sectors. Financial services are at the heart of this roadmap, tasked with driving innovation, sustainability, and competitiveness. But as we look towards the future, it’s critical that the sector strikes a careful balance between embracing strategic investments and maintaining operational resilience in the face of an increasingly complex technological risk landscape.

The digital transformation currently underway in financial services is set to accelerate even further as organisations adopt new technologies like artificial intelligence, blockchain, and cloud computing. These innovations hold immense potential for growth and efficiency, but they also introduce new layers of vulnerability. For financial services to thrive in this environment, firms need to ensure their technology infrastructure is resilient, reliable, and capable of withstanding disruption.

Growing risks in a digital-first world
As government and industry push forward with initiatives to digitise the financial services ecosystem, the sector is becoming more dependent on technology than ever before. With this reliance comes the inevitable rise of new risks—risks that can threaten operations, customer trust, and even the stability of markets.

We’ve seen first-hand the consequences of technology disruptions in this space. When key software providers experience outages or security breaches, the ripple effect can be significant, disrupting not just the companies involved but entire networks of financial institutions that depend on those systems. The impacts of such disruptions, particularly in a sector where reliability is paramount, can extend beyond the immediate downtime, eroding investor confidence and creating long-term reputational damage.

In a world that is becoming more interconnected by the day, it’s crucial that financial services organisations are prepared for these challenges. Protecting against technology failures and ensuring business continuity must be top priorities for any firm that wants to remain competitive in the years to come.

Operational resilience: The foundation of future growth
The ability to withstand and recover from disruption is at the core of what will define successful financial services firms in the future. Operational resilience is no longer just a regulatory requirement—it’s a business imperative that builds trust with investors, customers, and stakeholders. The strategies needed to build this resilience are varied, but there are a few critical components every organisation should consider.

  • Software Escrow: As financial institutions increasingly depend on digital tools, software escrow becomes a fundamental safeguard. We know how crucial escrow agreements are for protecting access to essential tools. If a provider fails or encounters insolvency, escrow ensures that critical software and intellectual property (IP) are held securely by a third party, ready to be released to the firm. In a sector where continuous access to technology is crucial, this arrangement offers peace of mind, ensuring core operations are protected from unexpected interruptions.
  • Stress-testing and Business Continuity: Regular stress-testing and comprehensive business continuity plans are essential components of any resilience strategy. By simulating disruptions, firms can identify weaknesses in their operations and put in place measures to address them. Continuity planning ensures that businesses can continue to operate, even under extreme circumstances, helping to mitigate the impacts of unanticipated events and minimise disruption to clients and markets.
  • Collaborative Resilience Standards: The interconnectivity of today’s financial ecosystem demands industry-wide standards. We’ve seen collaboration across both the private sector and with government initiatives become increasingly important. The UK’s Invest 2035 strategy offers an excellent foundation for fostering these partnerships, helping to establish resilience as a shared priority across the sector. We’re already seeing frameworks like the EU’s Digital Operational Resilience Act (DORA) lead the way in embedding resilience into the financial services supply chain. This kind of regulatory guidance helps institutions understand how to manage risks effectively, reducing overreliance on third-party providers and ensuring that firms can respond quickly to disruptions.

Collectively, these strategies reinforce the importance of being proactive rather than reactive when it comes to risk management. Operational resilience isn’t just about surviving the next crisis—it’s about building a foundation for long-term stability and growth in a rapidly changing environment.

Resilience as the key to securing Invest 2035
As we move towards Invest 2035, operational resilience will be the cornerstone of success. The financial services sector plays a pivotal role in driving economic growth and innovation, and its ability to adapt and respond to disruption will be key to maintaining the UK’s competitiveness on the global stage.

Embracing proactive resilience measures is the key to future success. By incorporating solutions like software escrow, stress-testing, and government-backed collaboration into their operational strategies, financial institutions can secure the UK’s position as a competitive, reliable investment hub.

Looking to the future, the ability to navigate these risks while maintaining operational integrity will determine whether financial services can continue to be the engine of economic growth in the UK. With the right safeguards in place, the sector can not only meet the goals of Invest 2035 but also build a reputation as a safe and dependable destination for global investment.

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