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AI in 2024: turning potential into progress

By Aisha Mendez, Associate Partner for AI & Automation at Infosys Consulting UK

Dictionaries’ “words of the year” can offer a headline insight into the worldwide events, emotions, and ideas that dominated the previous twelve months. And in 2023, there was only one contender.

Collins Dictionary was the most direct, simply selecting “AI” as its defining 2023 word. Meanwhile, Cambridge Dictionary picked “hallucinate” and Merriam-Webster chose “authentic”— not for their traditional definitions, but for their new connections to generative AI and its intermittent production of both genuine and false information.

Simply, AI dominated business and public discussions last year. But some sceptics continue to dismiss it as hype, while less technologically literate users remain unsure or unwilling to embrace it. I can say with confidence that AI is not only here to stay, but that it’s perhaps the most revolutionary technology of our lifetimes to date. So, this year businesses must prioritise AI to stay ahead of competitors, unlock unprecedented productivity gains, and embrace the cutting-edge of technological development.

Aisha Mendez

Taking AI to the next level in 2024

An exciting and unique element of generative AI is that it can be used by almost anyone – you don’t need to be a traditional coder or even an expert in AI at all. This massively widens the possibilities for its application within a business, as well as by consumers.

Generative AI can do so much more than provide conversational responses to written questions. From automating code generation to synthesising pharmaceutical molecules, the technology is a multi-tool of digital transformation. It can be harnessed for personalised marketing at scale, predictive analytics, and even creating digital art. In the realm of cybersecurity, generative models can simulate network behaviour to identify vulnerabilities before they’re exploited. In my personal working life, I rely on a suite of ‘helpers’, from ChatGPT to MidJourney and Gamma (the latter is especially useful, because who actually enjoys pulling PowerPoints together?).” 

Generative AI is poised to be a transformative force across industries, reshaping how we solve complex problems, generate content, and even make decisions. Its applications are only limited by our imagination. Ignoring this technology doesn’t just mean missing out on incremental improvements, but risks making a company obsolete as competitors leverage AI to revolutionize workflows and customer experiences. It’s not just a game-changer; it’s table stakes for future relevance. So, how can you successfully harness it in 2024 and beyond?

My top tips for integrating AI into your business

First things first: stop overthinking it. Generative AI isn’t some esoteric riddle wrapped in an enigma; it’s a tool. A fantastic, gloriously complex tool, but a tool, nonetheless. Start by looking at your business processes and asking, “Where am I tired of saying, ‘There must be a better way!’?” That’s your sweet spot for generative AI. As for who should be around the table, you need your decision-makers, of course—the CEO and CTOs—but please don’t ignore your front-line workers. They know the processes better than anyone. Add a few sceptics in for good measure; you need people who’ll ask the hard questions.

In the journey to implement generative AI technologies, a multidisciplinary approach is not just beneficial—it’s essential. Naturally, IT and Operations are cornerstone departments, responsible for the technical implementation and ongoing support of these solutions. They function as the backbone of any AI initiative. However, the ecosystem that sustains and governs generative AI is complex and touches upon various areas of an organisation. For instance, Legal and Compliance teams; they help navigate the regulatory landscape and ethical considerations around AI use, ensuring that the organisation’s policies reflect the highest standards of responsible conduct.

Also, as job roles evolve, HR becomes central to the change management process, ensuring a smooth transition for staff and maintaining organisational health. Business changes around generative AI that impact employees must be announced in a manner that helps ensure it’s used/seen in a positive way. Leaders often communicate change as if they’re announcing a weather report: factual and devoid of emotion. But change is emotional! Especially when it’s about something as life-altering as AI. Lead with empathy, not just facts.

Be sure to introduce a Generative AI Use Policy, but please make it understandable. Legal jargon is as appealing as soggy chips. A well-crafted policy will educate your team on the potential pitfalls, from accuracy to copyright issues. Remember, a policy isn’t there to cover your back; it’s there to empower your people. Speaking of rules and regulations, let’s look at the wider evolutions happening across the AI industry.

How lawmakers and tech companies can safely foster future innovation

At the UK AI Summit in November, 28 countries agreed to work together to combat the risks posed by AI development under the ‘Bletchley Declaration’, while the UK and the US also announced the creation of collaborative AI Safety Institutes for the research and testing of emerging AI.

I was thrilled to see participating nations unite to address common challenges and formulate a cohesive approach to responsible AI development. But while regulations are necessary as we move into 2024, we should also prioritise the nurturing of innovation. Supporting start-ups and smaller AI firms with incentives, funding, and access to data is key to fostering continued progress in AI development.

Similarly, we need to acknowledge the underrepresentation of female-led AI start-ups in funding. We must foster a more inclusive environment within the AI industry, and this should extend to funding channels, so female-founded AI companies have equal access to the investment opportunities required for responsible AI development. This issue of diversity is not just about fairness — it’s utterly crucial for mitigating biases and discrimination within AI systems. AI learns from the humans building and using it, so ensuring it isn’t skewed or stunted because only a select few are involved in it is important.

Progress this year will likely involve encouraging venture capital firms to adopt more inclusive policies, fostering an environment where all founders are subjected to fair scrutiny, and actively promoting diversity in the AI ecosystem. A diverse development team translates to more comprehensive and effective solutions. The future of work isn’t human vs. machine; it’s human and machine—co-creating value in ways we’ve just started to realise.

Channelling AI’s potential for good

If 2023 was the year of AI discovery and experimentation, 2024 is the time to get serious about using it for tangible progress. Here, getting your employees on board is crucial.

Minimising fears, whilst maximising excitement around generative AI, transparency and vision-setting, are paramount. Employees should be part of the conversation from the get-go, and continually involved in AI’s role within the organization. Open dialogues create a space for staff to voice concerns and for leadership to address them head-on, setting the record straight that AI is a tool to augment, not replace, human capabilities. Moreover, re-skilling and upskilling programs are non-negotiables. This year, many businesses will likely invest in a training ecosystem that demystifies AI and empowers employees to leverage it in their roles. When people see first-hand how these tools make their work more impactful, concerns often give way to enthusiasm.

Lastly, celebrate the wins, big and small, achieved through human-AI collaboration. Showcase these as case studies to the entire organization. This not only fosters a positive narrative around AI but also instils a culture of innovation. By making the workforce part of the AI journey, you replace fear with ownership and future-proof your human capital. AI is here to stay—but it’s still no match for your people’s wisdom, empathy, and creativity.

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Business

What can the West learn from the Arabian Gulf’s payments revolution?

Hassan Zebdeh, Financial Crime Advisor at Eastnets

A decade ago, paying for coffee at a small café in Riyadh meant fumbling with cash – or, at best, handing over a plastic card. Today, locals casually wave smartphones over terminals, instantly settling the bill, splitting it among friends, and even transferring money abroad before their drink cools.

This seemingly trivial scene illustrates a profound truth: while the West debates incremental upgrades to ageing payment systems, the Arabian Gulf has leapfrogged straight into the future. As of late 2024, Saudi Arabia achieved a remarkable 98% adoption rate for contactless payments in face-to-face transactions, a significant leap from just 4% in 2017.

Align financial transformation with a bold national vision

One milestone that exemplifies the Gulf’s approach is Saudi Arabia’s launch of its first Swift Service Bureau. While not the first SSB worldwide, its presence in the Kingdom underscores a broader theme: rather than rely on piecemeal upgrades to older infrastructure, Saudi Arabia chose a proven yet modern route, aligned to Vision 2030, to unify international payment standards, enhance security, and reduce operational overhead.

And it matters, because in a region heavily reliant on expatriate workers whose steady stream of remittances powers whole economies. The stakes for frictionless cross-border transactions are unusually high. Rather than tinkering around the edges of an ageing system, Saudi Arabia opted for a bold and coherent solution, deliberately aligning national pride and purpose with practical financial innovation. It’s a reminder that infrastructure, at its best, doesn’t merely enable transactions; it reshapes how people imagine the future.

Make regulation a launchpad, not a bottleneck

Regulation often carries the reputation of an overprotective parent – necessary, perhaps, but tiresome, cautious to a fault, and prone to slowing progress rather than enabling it. It’s the bureaucratic equivalent of wrapping every new idea in bubble wrap and paperwork. Yet Bahrain has managed something rare: flipping the narrative entirely. Instead of acting solely as gatekeepers, Bahraini regulators decided to become collaborators. Their fintech sandbox isn’t merely a regulatory innovation; it’s psychological brilliance, transforming a potentially adversarial relationship into a partnership

Within this curated environment, fintech firms have launched practical experiments with striking results. Take Tarabut Gateway, which pioneered open banking APIs, reshaping how banks and customers interact. Rain, a cryptocurrency exchange, tested compliance frameworks safely, quickly becoming one of the Gulf’s trusted crypto players. Elsewhere, startups trialled AI-driven identity verification and seamless cross-border payments, all under the watchful yet adaptive guidance of Bahraini regulators. Successes were rapidly scaled; failures offered immediate lessons, free from damaging legal fallout. Bahrain proves regulation, thoughtfully applied, can genuinely empower innovation rather than restrict it.

Prioritise cross-border interoperability and unified standards

Cross-border payments have long been a maddening puzzle – expensive, sluggish, and unpredictably complicated. Most Western banks seem resigned to this reality, treating the spaghetti-like mess of correspondent banking relationships as a necessary evil. Yet Gulf states looked at this same complexity and saw not just inconvenience, but opportunity. Instead of battling against the tide, they cleverly redirected it, embracing standards like ISO 20022, which neatly streamline data exchange and slash friction from global transactions.

Examples abound: Saudi Arabia’s adoption of ISO 20022 through its Swift Service Bureau will notably accelerated cross-border transactions and improve transparency. The UAE and Saudi Arabia also jointly piloted Project Aber, a digital currency initiative that significantly reduced settlement times for interbank payments. Similarly, Bahrain’s collaboration with fintechs has simplified previously burdensome remittance processes, reducing both cost and complexity.

Target digital ecosystems for financial inclusion

One of the most intriguing elements of the Gulf’s payments transformation is the speed and enthusiasm with which consumers embraced new technologies. In Bahrain, mobile wallet payments surged by 196% in 2021, contributing to a nearly 50% year-over-year increase in digital payment volumes. Similarly, Saudi Arabia experienced a near tripling of mobile payment volumes in the same year, with mobile transactions accounting for 35% of all payments. 

The West, by contrast, still struggles with financial inclusion. In the U.S., millions remain unbanked or underbanked, held back by distrust, geographic isolation, and high fees. Digital solutions exist, but widespread adoption has lagged, partly because major institutions view inclusion as a long-term aspiration rather than an immediate priority. The Gulf shows that when digital tools are made integral to daily life, rather than optional extras, the barriers to financial inclusion quickly dissolve.

The road ahead

As the Gulf region continues to refine its payment systems experimenting with digital currencies, advanced data protection laws, and AI-driven compliance the ripple effects will be felt far beyond the GCC. Western players can treat these developments as an external threat or as a chance to rejuvenate their own approaches.

Ultimately, if you want a glimpse of where financial services may be headed towards integrated platforms, real-time international transactions, and widespread digital inclusion – the Gulf experience is a prime example of what’s possible. The question is whether other markets will step up, follow suit, and even surpass these achievements. With global financial landscapes evolving at record speed, hesitation carries its own risks. The Arabian Gulf has shown that bold bets can pay off; perhaps that’s the most enduring lesson for the West.

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Business

Unlocking business growth with efficient finance operations

Rob Israch, President at Tipalti

The UK economy has faced a turbulent couple of years, meaning now more than ever, businesses need to stay agile. With Reeves’s national insurance hikes now fully in play and global trade tensions casting a shadow over the landscape, the coming months will present a crucial opportunity for businesses to decide how to best move forward. 

That said, it’s not all doom and gloom. The latest official figures show that the UK’s economy unexpectedly grew at a rate of 0.5% in February – a welcome sign of resilience. But turning this momentum into sustainable growth will hinge on effective financial management – essential for long term success.

Although many are currently prioritising stability, sustainable growth is still within reach with the right approach. By making use of data and insights from the finance team, companies can pinpoint efficient paths to expansion. However, this relies on having real-time information at their fingertips to support agile, well-timed decisions.

While achieving growth may be tough to come by this year, businesses can stay on track by adopting a few essential strategies. 

Improving efficiency by eliminating finance bottlenecks

Growth is the ultimate goal for any business, but it must be managed carefully to ensure long-term sustainability. Uncertain times present an opportunity to eliminate inefficiencies and build a strong foundation for future success.

A significant bottleneck for many businesses is the finance function’s reliance on manual processes for invoice processing, reporting and reconciliation. These tasks are not only time-consuming but also introduce errors, delays and inefficiencies. As a result, finance teams become stretched thin. Our recent survey found that, on average, over half (51%) of accounts payable time is spent on manual tasks – severely limiting finance leaders’ ability to drive strategic growth.

Repetitive tasks such as data entry, reconciliation, and approvals require considerable time and effort, slowing down decision-making and increasing the risk of inaccuracies. Given the critical role that finance plays in guiding business strategy, these inefficiencies and errors create significant roadblocks to growth.  

The pressure on finance leaders is therefore immense and while 71% of UK business leaders believe CFOs should take a central role in corporate growth initiatives, they are simply lost in a sea of manual processes and number crunching. In fact, 82% of finance leaders admit that excessive manual finance processes are hindering their organisation’s growth plans for the year ahead. To remedy this, businesses must embrace automation.

Achieving sustainable growth with automation

By replacing manual spreadsheets with automated solutions, finance teams can eliminate administrative burdens and focus on strategic initiatives. Automation simplifies critical finance tasks like bank feeds, coding bookkeeping transactions and invoice matching. Beyond this, it can also help alleviate the strain of more complex and time-intensive responsibilities, including tax filings, invoices and payroll.

The benefits of automation extend far beyond time saving, to accuracy, improving business visibility and enabling real-time financial insights. With fewer errors and faster-data processing, finance leaders can shift their focus to high-value tasks like driving strategy, identifying risks and opportunities and determining the optimal timing for growth investments.

Attracting investors with operational efficiency 

Once businesses have minimised time spent on administrative tasks, they can focus on the bigger picture: growth and securing investment. With access to cheap capital becoming increasingly difficult, businesses must position themselves wisely to attract funding.  

Investors favour lean, efficient companies, so demonstrating that a business can achieve more with fewer resources signals a commitment to financial prudence and sustainability. By embracing automation, companies can showcase their ability to manage operations efficiently, instilling confidence that any new investment will be spent and used wisely.

Economic uncertainty provides an opportunity to reassess business foundations and create more agile operations. Refining workflows and eliminating bottlenecks not only improves performance but also strengthens investor confidence by demonstrating a long-term commitment to financial health.

Additionally, strong financial reporting and effective cash flow management are crucial to standing out to investors. Clear, real-time insights into financial health demonstrate resilience and highlight a business’ resilience and readiness for growth.

The growth journey ahead

Though the landscape remains tough for UK businesses, sustainable growth is still achievable with a clear and focused strategy. By empowering finance leaders to step into more strategic and high-level decision making roles, organisations can stay resilient and agile amid ongoing economic headwinds.

UK businesses have fought to stay afloat, so now is the time to rebuild strength. By embracing more strategic financial management to build resilience, they can set the stage for long-term, sustainable growth, whatever the economic climate brings.

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Business

The Consortium Conundrum: Debunking Modern Fraud Prevention Myths

By Husnain Bajwa, SVP of Product, Risk Solutions, SEON


As digital threats escalate, businesses are desperately seeking comprehensive solutions to counteract the growing complexity and sophistication of evolving fraud vectors. The latest industry trend – consortium data sharing – promises a revolutionary approach to fraud prevention, where organisations combine their data to strengthen fraud defences.

It’s understandable how the consortium data model presents an appealing narrative of collective intelligence: by pooling fraud insights across multiple organisations, businesses hope to create an omniscient network capable of instantaneously detecting and preventing fraudulent activities.

And this approach seems intuitive – more data should translate to better protection. However, the reality of data sharing is far more complex and fundamentally flawed. Overlooked hurdles reveal significant structural limitations that undermine the effectiveness of consortium strategies, preventing this approach from fulfilling its potential to safeguard against fraud. Here are several key misconceptions about how consortium approaches fail to deliver promised benefits.


Fallacy of Scale Without Quality


One of the most persistent myths in fraud prevention mirrors the trope of enhancing a low-resolution image to reveal more explicit details. There’s a pervasive belief that massive volumes of consortium data can reveal insights not present in any of the original signals. However, this represents a fundamental misunderstanding of information theory and data analysis.

To protect participant privacy, consortium approaches strip away critical information elements relevant to fraud detection. This includes precise identifiers, nuanced temporal sequences and essential contextual metadata. Through the loss of granular signal fidelity required to anonymise information to make data sharing viable, said processes skew data while eroding its quality and reliability. The result is a sanitised dataset that bears little resemblance to the rich, complex information needed for effective fraud prevention. Further, embedded reporting biases from different entities can likewise exacerbate quality issues. Knowing where data comes from is imperative, and consortium data frequently lacks freshness and provenance.

Competitive Distortion is a Problem


Competitive dynamics can impact the efficacy of shared data strategies. Businesses today operate in competitive environments marked by inherent conflicts, where companies have strategic reasons to restrict their information sharing. The selective reporting of fraud cases, intentional delays in sharing emerging fraud patterns and strategic obfuscation of crucial insights can lead to a “tragedy of the commons” situation, where individual organisational interests systematically degrade the potential of consortium information sharing for the collective benefit.

Moreover, when direct competitors share data, organisations often limit their contributions to non-sensitive fraud cases or withhold high-value signals that reduce the effectiveness of the consortium dynamics.

Anonymisation’s Hidden Costs


Consortiums are compelled to aggressively anonymise data to sidestep the legal and ethical concerns of operating akin to de facto credit reporting agencies. This anonymisation process encompasses removing precise identifiers, truncating temporal sequences, coarsening behavioural patterns, eliminating cross-entity relationships and reducing contextual signals. Such extensive modifications limit the data’s utility for fraud detection by obscuring the details necessary for identifying and analysing nuanced fraudulent activities.

These anonymisation efforts, needed to preserve privacy, also mean that vital contextual information is lost, significantly hampering the ability to detect fraud trends over time and diluting the effectiveness of such data. This overall reduction in data utility illustrates the profound trade-offs required to balance privacy concerns with effective fraud detection.

The Problem of Lost Provenance


In the critical frameworks of DIKA (Data, Information, Knowledge, Action) and OODA (Observe, Orient, Decide, Act), data provenance is essential for validating information quality, understanding contextual relevance, assessing temporal applicability, determining confidence levels and guiding action selection. However, once data provenance is lost through consortium sharing, it is irrecoverable, leading to a permanent degradation in decision quality.

This loss of provenance becomes even more critical at the moment of decision-making. Without the ability to verify the freshness of data, assess the reliability of its sources or understand the context in which it was collected, decision-makers are left with limited visibility into preprocessing steps and a reduced confidence in their signal interpretation. These constraints hinder the effectiveness of fraud detection efforts, as the underlying data lacks the necessary clarity for precise and timely decision-making.

The Realities of Fraud Detection Techniques


Modern fraud prevention hinges on well-established analytical techniques such as rule-based pattern matching, supervised classification, anomaly detection, network analysis and temporal sequence modelling. These methods underscore a critical principle in fraud detection: the signal quality far outweighs the data volume. High-quality, context-rich data enhances the effectiveness of these techniques, enabling more accurate and dynamic responses to potential fraud.

Despite the rapid advancements in machine learning (ML) and data science, the fundamental constraints of fraud detection remain unchanged. The effectiveness of advanced ML models is still heavily dependent on the quality of data, the intricacy of feature engineering, the interpretability of models and adherence to regulatory compliance and operational constraints. No degree of algorithmic sophistication can compensate for fundamental data limitations.

As a result, the core of effective fraud detection continues to rely more on the precision and context of data rather than sheer quantity. This reality shapes the strategic focus of fraud prevention efforts, prioritising data integrity and actionable insights over expansive but less actionable data sets.

Evolving Into Trust & Safety: The Imperative for High-Quality Data


As the scope of fraud prevention broadens into the more encompassing field of trust and safety, the requirements for effective management become more complex. New demands, such as end-to-end activity tracking, cross-domain risk assessment, behavioural pattern analysis, intent determination and impact evaluation, all rely heavily on the quality and provenance of data.

In trust and safety operations, maintaining clear audit trails, ensuring source verification, preserving data context, assessing actions’ impact, and justifying decisions become paramount.

However, the nature of consortium data, which is anonymised and decontextualised to protect privacy and meet regulatory standards, cannot fundamentally support clear audit trails, ensure source verification, preserve data context, and readily assess the impact of actions to justify decisions. These limitations showcase the critical need for organisations to develop their own rich, contextually detailed datasets that retain provenance and can be directly applied to operational needs to ensure that trust and safety measures are comprehensive, effectively targeted, and relevant.

Rethinking Data Strategies


While consortium data sharing offers a compelling vision, its execution is fraught with challenges that diminish its practical utility. Fundamental limitations such as data quality concerns, competitive dynamics, privacy requirements and the critical need for provenance preservation undermine the effectiveness of such collaborative efforts. Instead of relying on massive, shared datasets of uncertain quality, organisations should pivot toward cultivating their own high-quality internal datasets.

The future of effective fraud prevention lies not in the quantity of shared data but in the quality of proprietary, context-rich data with clear provenance and direct operational relevance. By building and maintaining high-quality datasets, organisations can create a more resilient and effective fraud prevention framework tailored to their specific operational needs and challenges.

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