Expert thinking on productivity, intangible asset valuation, growth strategy, and building more valuable businesses.
How AI is transforming the Big Four's most valuable — and invisible — intangible assets, from proprietary models to training data and organisational capital.
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Most fund managers evaluate companies using metrics that capture less than half the picture. Here's the intangible asset blind spot and how to fix it.
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Consumer brands are among the most economically powerful intangible assets in existence — generating pricing power, customer loyalty, and distribution leverage over decades. Yet brand equity remains structurally underexploited as loan collateral. The structures to change this are established. The opportunity for PE-backed consumer businesses is substantial.
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I spent 30 years in structured finance, working across derivatives trading, cross-border M&A, and asset-backed securities. I watched trading floors evolve from human traders to algorithms to AI agents. Each transition created new intangible assets and new valuation challenges. Here is how financial services is building and valuing AI intangible assets.
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The commercial property sector has invested over £15 billion in PropTech in the past five years. Yet most property valuations fail to capture the intangible assets these technologies create. This is about to change — and it will radically reshape how commercial property is valued and traded.
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Private equity firms pride themselves on rigorous due diligence and data-driven value creation. Yet most PE investment processes are structurally blind to the intangible assets that account for the majority of portfolio company value. This gap creates both hidden risks and untapped opportunities.
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I spent thirty years valuing commercial property — tangible buildings with concrete returns and comparable sales. Then I moved into intangible asset valuation. At first, the transition seemed impossible. Then I realised: the skills transfer perfectly. Here is what property valuation teaches about valuing what you cannot see.
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Pharmaceuticals were among the first sectors to pioneer IP-backed financing through patent royalty securitisations. But the opportunity extends far beyond royalty streams. Drug patents, clinical data packages, regulatory approvals, and formulation know-how constitute a rich intangible asset base that most PE-backed pharma companies underexploit as collateral.
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When 92% of S&P 500 value is attributable to intangible assets but only 8% appears on balance sheets, there is a fundamental disconnect between reported financial position and economic reality. This thought experiment reconstructs a typical SaaS company's balance sheet as if intangibles were properly captured. The results are illuminating.
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Data is now formally recognised as productive capital by the System of National Accounts. But how do you value it on a balance sheet? Tony Hillier draws on 30 years of structured finance experience to map three valuation approaches — and where data assets fit into modern capital structures.
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National accounts now recognise R&D and software as capital assets. But the majority of intangible investment — organisational know-how, proprietary data, trained workforces, customer networks — still falls outside the measurement boundary. These are the seven categories that distort our understanding of productivity.
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Under current accounting standards, most AI development costs are expensed immediately — treated as period costs rather than capital investments. Yet new FASB guidance (ASU 2025-06) and SNA 2025 recognised data as productive capital. This creates a widening gap between economic reality and financial reporting. Here is how to navigate it.
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