Practical Capital 2026

Our latest edition of Practical Capital brings together three topics that are shaping the future of investing and family offices: artificial intelligence, data and reporting, and the growing threat of fraud. While each presents its own challenges and opportunities, they share a common theme: technology is becoming increasingly powerful, but its value depends on how it’s applied.

At CapGen, we believe that successful innovation is not about adopting the latest technology for its own sake. Whether implementing AI, building robust consolidated reporting capabilities, or strengthening fraud prevention frameworks, the objective is to improve outcomes and support clients more effectively. Achieving this requires a disciplined approach, combining the right technology with strong governance, high-quality data, and human expertise.

In the following articles, we explore how we’re approaching AI adoption across the business, why consolidated reporting remains a highly valuable but complex capability, and how organisations can respond to the rapidly evolving fraud landscape. While the technologies and risks may differ, the underlying message is the same: long-term value is created not by the tools themselves, but by the controls and people that sit behind them.

At CapGen, our approach to implementing AI has been deliberate and selective. Rather than applying AI across the business, we have established a framework to assess where it can genuinely add value, and also where it may not be the right solution. This means we carefully evaluate each potential use case, ensuring that AI is deployed only where it can meaningfully support outcomes, rather than pursuing it for its own sake.

Our strategic objectives remain unchanged. We believe AI is simply another tool within our existing toolkit, albeit a powerful one.

To understand where AI can truly add value across the business, we have developed a structured framework for assessing and prioritising AI use cases. This framework goes beyond efficiency or cost reduction, and includes factors such as risk mitigation, enhanced controls, improved decision-making, and the ability to conduct deeper, more comprehensive analysis. We also assess the risks associated with the data used, considering factors such as data quality and the reliability of sources.

These assessments are applied across a wide range of potential use cases, from the legal team conducting fund reviews to the research team carrying out due diligence on fund managers, ensuring AI is deployed where it can deliver the most meaningful value.

In some cases, AI may not reduce the time required to complete a task and may even introduce additional steps, but if it significantly improves the quality, insight, or robustness of the final output, we consider that a valuable outcome. Conversely, some solutions we explored were ultimately discarded because we did not believe they improved existing processes.

The quality of AI output is ultimately determined by the quality of the inputs. Recognising this, we set AI up for success by providing clear instructions, well-defined parameters and high-quality source data. The more specific the environment, the more reliable the outcome. Rather than giving AI unrestricted access to vast amounts of information, we carefully define where it should look, what it should do, and what it should not do. This disciplined approach reduces the risk of inaccurate results and increases the likelihood of generating meaningful insights.

Alongside our framework for identifying and prioritising AI use cases, we have established a robust governance and control structure to ensure AI continues to deliver benefits and be used responsibly.

This includes the creation of an internal agent register, with every AI agent required to go through a formal approval process before deployment. As part of that process, we assess factors such as the sensitivity of the data available to the agent, its intended purpose, and the level of autonomy it’s permitted. Strict controls are in place around what AI can and cannot do. For example, an agent may be allowed to draft an email, but it would never be permitted to send one independently.

These safeguards reflect the nature of our business and the importance of maintaining appropriate oversight. While AI can automate a wide range of tasks, our approach is guided by what is right for us, rather than what may be technically possible. Relationships are central to our service, and although AI may support activities such as investment research and analysis, we would not use it to communicate directly with clients, nor would we allow it to propose and execute investment decisions.

The existence of a capability does not justify its use. Every application of AI must support our objectives and operate within clearly defined parameters.

A key part of our approach has been investing in our people through training programmes. We have delivered AI overview sessions to help colleagues develop a practical understanding of how these tools work, where they can add value, and where their limitations lie. By understanding the technology that underpins AI, people are better equipped to interpret its outputs and recognise why it can occasionally produce unexpected or inaccurate responses. These results become easier to understand when viewed in the context of how large language models are trained.

We want our colleagues to understand that AI is not a solution for every problem. It may be useful for tasks involving content generation, analysis and coding, but it is not simply a more sophisticated search engine or a dedicated calculation tool. By helping colleagues understand its strengths and limitations, we can encourage the responsible and effective use of AI.

One of the biggest challenges we face is adoption, as everyone responds to AI differently. We’ve noticed that some rarely use it, while others rely on it extensively, and much of that variation comes down to trust. A common approach we’ve seen is “all or nothing”, meaning if AI produces a single error, some conclude it can’t be trusted at all. Part of our role is to help reset expectations around what "good" looks like. For example, AI may be able to generate 90% of what’s needed, with the remaining refinement provided through human expertise. Rather than dismissing the AI output because it’s imperfect, we encourage colleagues to view it as a starting point. The alternative is that someone generates the idea and then refines it via AI, effectively using it as a sounding board. Both are valuable.

More broadly, resistance to AI reflects a natural response to change. The technology is still relatively new, and its long-term impact remains uncertain. Media coverage often focuses on extreme outcomes, making some people understandably cautious about engaging with it. At the same time, others are highly enthusiastic and eager to incorporate it into every aspect of their work.

As with many transformative technologies, AI adoption appears to be following a familiar pattern: an initial wave of excitement and high expectations, followed by a period of disillusionment as limitations become apparent, before eventually settling into a more mature phase where organisations identify the specific use cases that deliver genuine and sustainable value.

Wealth today is often spread across multiple custodians, asset classes, jurisdictions, and structures. As this fragmentation grows, so does the need for consolidated reporting, which provides a single, coherent view of total wealth.

With assets scattered across providers and vehicles, understanding a family’s true financial position becomes difficult. Consolidated reporting brings everything together, enabling wealth owners and family office executives to see total exposure, concentration risks, cross portfolio performance, liquidity and cash flow, and asset allocation across the entire estate. Without this, decisions are made in silos, and often slowly.

When data is centralised and reliable, decision makers can respond quickly. Instead of evaluating each asset class or custodian separately, consolidated reporting allows for total wealth performance analysis. This is critical for understanding whether the overall strategy is working, not just individual components.

The key to consolidated reporting is the accuracy of the input data. If the data going in is wrong, the reporting will be wrong.

But the data is hard to collect and homogenise as it arrives in different formats, from different systems, with different levels of quality. Some assets, like private equity or real estate, don’t naturally fit into traditional reporting frameworks. Reconciling a yield curve with private equity returns, for example, requires deep technical expertise. Converting the huge amounts of input data into the right format is a monumental and sophisticated task.

AI is very useful for spotting patterns, identifying anomalies and accelerating analysis. But AI cannot fix incorrect or incomplete data, it cannot replace the complex human judgement required for multi asset consolidation, nor can it overcome privacy and governance constraints.

AI can potentially enhance consolidated reports one day, but only if the underlying data is accurate and well structured.

There are no quick wins in consolidated reporting. It is challenging and requires many hours of skilled time and labour. But when done well, the benefits are transformative, offering a much clearer understanding of total wealth.

Fraud in the UK is growing rapidly, driven by technology, geopolitical instability, and increasingly sophisticated criminal networks. It’s leaving businesses, consumers, and financial institutions exposed to unprecedented levels of risk.

Fraud is no longer a peripheral financial crime. It’s now the single largest category of crime in the UK, accounting for 43% of all offences.¹ The economic and social impact is staggering. Fraud drains an estimated £219 billion from the UK economy every year, undermining trust, destabilising businesses, and exploiting millions of individuals.²

In 2024, 4.1 million people in the UK fell victim to fraud; a 33% increase on the previous year.³ Identity fraud remains the most common form, fuelled by easy access to AI powered fraud tools, geopolitical instability, cost of living pressures and the proliferation of criminal marketplaces. These forces have created a perfect storm in which fraudsters innovate faster than organisations can defend.

The corporate sector is facing a significant threat. 93% of UK companies experienced attempted fraud in 2024, and 42% suffered at least one successful attack. 79% of senior executives cite cyber risks as their top concern, as payment fraud is increasing in scale, sophistication and impact.⁴

According to the TrustPair 2025 UK Fraud Trends Report, the threat is evolving faster than internal controls, leaving organisations exposed to both financial and reputational damage.⁵

Invoice fraud continues to surge; this is when criminals intercept or manipulate legitimate payment processes. These criminals impersonate suppliers or service providers to trick businesses or individuals into sending money to fraudulent accounts. According to CCL Academy, in 2024 £50.3 million was lost across 3,110 cases.⁶

There are several key characteristics of this type of fraud to look out for:

• 70% target non‑personal (business) accounts
• Common methods include:
  • Email interception, often through compromised email accounts
  • Fake “change of bank details” notifications
  • Fraudulent payee redirection

These types of scams exploit trust and routine, making them both effective and difficult to detect.

Supplier related fraud is an under recognised risk in corporate environments. It’s when a supplier manipulates the purchasing process or misrepresents goods, services, or invoices to benefit financially at the expense of the buyer. It can occur at onboarding or during ongoing relationships.

Supplier fraud risks arise when criminals or dishonest insiders exploit weaknesses in procurement and payment processes. These risks include collusion between suppliers and staff, the use of fake or shell companies, and suppliers presenting false credentials or links to criminal activity. Fraudsters may also submit manipulated invoices, inflating prices, quantities, or goods. Or perhaps they may attempt payment diversion and account takeovers to redirect funds. Other tactics include invoice splitting to bypass approval thresholds and vendor email compromise attacks, where criminals impersonate legitimate suppliers to alter payment instructions.

Red flags to watch for:

• Vendor name inconsistencies
• Irregular invoice numbers
• Unusual goods or service descriptions
• Mismatched documentation
• Excessive secrecy or reluctance to share information
• High‑volume activity from new vendors
• Duplicate invoices
• Signs of document tampering

Document fraud refers to the illegal act of creating, altering, or using false documents to deceive individuals or organisations for personal gain. It underpins a wide range of financial crimes. The main types include:

• Imposters: the holder resembles the rightful owner
• Counterfeits: documents created from scratch
• Forgeries: genuine documents that have been altered

These techniques enable identity theft, supplier fraud, money laundering, and investment scams.

Impersonation fraud has become an increasingly common threat for investment firms, where criminals pose as legitimate businesses to deceive clients and divert funds. In many cases, fraudsters contact individuals while pretending to represent a genuine firm, often quoting the firm’s FCA registration number or other official sounding details to appear credible. Their objective may be to redirect investment sales or withdrawal requests, or to harvest personal and financial information for later misuse. Firms typically become aware of the impersonation only when they begin receiving complaints from targeted individuals who report being pressured, misled, or harassed by someone claiming to act on the firm’s behalf.

This type of fraud is difficult to prevent because the criminals operate entirely outside the firm’s systems, using cloned websites, spoofed email addresses, or manipulated caller IDs. However, firms can take steps to reduce the impact. Adding a warning banner on the FCA Register profile, publishing clear guidance on the firm’s official communication channels, and educating clients about verification procedures all help signal to the public that impersonation attempts may occur. While these measures cannot eliminate the risk, they do provide an important layer of protection by making it harder for fraudsters to exploit the firm’s identity.

The first step is acknowledging the scale of the threat. Fraud is not a rare event, it’s a systemic, persistent, and evolving risk.

Key actions include:

• Identify and assess fraud risks across all business functions
• Monitor for fraud indicators and behavioural red flags
• Ensure your controls remain fit for purpose and constantly evolve as the threats develop
• Promote a culture where fraud prevention is everyone’s responsibility

Fraud in the UK has reached a scale that demands urgent, coordinated action. Criminals are innovating rapidly, leveraging AI, exploiting global instability, and targeting both individuals and organisations with unprecedented sophistication.

The challenge is immense, but so is the opportunity for firms that invest in resilience, modernise their controls, and build a culture of vigilance.

¹ 2024-25 NECC Annual Report v0.7.pub

² Annual Fraud Indicator 2023

³ Crime in England and Wales - Office for National Statistics

⁴ 2025 UK Fraud Report Press Release

⁵ 2025 UK Fraud Trends and Insights

⁶ Compliance Updater - March 2024 | CCL Academy - UK

Capital Generation Partners LLP is authorised and regulated by the Financial Conduct Authority and is registered as an Investment Adviser by the US Securities and Exchange Commission.

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