Introduction — The Digital Mirage
In the global financial industry, the rhetoric of transformation has become a ritual. Conference stages glow with slides about artificial intelligence, end-to-end automation, cloud-native architectures, real-time dashboards, blockchain proofs of concept, and next-generation operating models. Senior executives insist they are driving their organisations toward a fully digital future. Regulators increasingly expect it. Investors demand it.
And yet, behind this confident discourse lies a more uncomfortable truth: much of the financial system still relies on a technology born in the 1980s. From Wall Street’s trading floors to Luxembourg’s winding ecosystem of fund administrators and ManCos, Excel spreadsheets remain the invisible backbone of daily operations. They calculate NAVs, reconcile positions, aggregate exposures, compile regulatory data, and shape the balance sheets that sustain trillions of dollars in assets.
This is not a matter of occasional usage. It is structural dependency. In 2025, CFOTech reported that seven out of ten CFOs still rely heavily on Excel for planning, forecasting, and reporting. FundsTech interviewed hedge funds and found a similar pattern: nearly three-quarters confessed to relying on spreadsheets for portfolio analytics and risk workarounds. Wolters Kluwer published another revealing number: 42% of financial institutions continue to use manual processes, most often spreadsheets, for regulatory compliance.
The question is no longer whether Excel should be replaced, but rather how the industry can claim to have “digitised” itself when its day-to-day mechanics remain powered by a tool designed for personal computers four decades ago.
Excel as the Industry’s Unspoken Infrastructure
To understand this paradox, one must recognise that Excel is not merely a productivity tool inside financial institutions; it is a cultural artefact. It is the first language learned by junior analysts, the standard dialect of portfolio managers, the safety net of risk teams, and the experimental lab of middle-office specialists. It is universal, easily shared, rarely policed, and infinitely malleable. It enables rapid prototyping, immediate responses to client requests, and countless undocumented fixes to system shortcomings.
While modern platforms offer structured data models, Excel provides something arguably more valuable in the short term: immediate control. A system may take months to reconfigure; a spreadsheet takes minutes. When a regulator adjusts a template or a client requests a new breakdown of exposures, the default reaction is instinctive: open Excel, extract data, and build the solution manually. This responsiveness explains why, despite billions invested in IT transformation, spreadsheets remain the connective tissue between systems that otherwise do not talk to one another.
Excel’s ubiquity is therefore not technological inertia alone; it is organisational self-defence. Finance has embraced digitalisation rhetorically, but has clung to Excel operationally because it guarantees autonomy in institutions where dependency on central IT systems is often seen as a burden.
A System Built on Fragility
The financial sector’s reliance on spreadsheets comes with well-documented risks. Unlike enterprise systems, spreadsheets offer no inherent audit trail, no controlled versioning, no rigorous data lineage, and no consistent validation framework. They remain vulnerable to manual errors—incorrect formulas, overwritten cells, hidden rows, corrupted files—that can spread silently across complex workflows.
In 2012, the JPMorgan “London Whale” scandal etched this vulnerability into financial history. A flawed spreadsheet underpinning a Value-at-Risk model contributed to one of the bank’s largest-ever trading losses. The episode is no anomaly; it is simply the most visible illustration of a broader pattern. Financial reporting errors, incorrect asset valuations, and inconsistent regulatory submissions all trace back, with disarming regularity, to spreadsheets that were never designed to support the weight placed upon them.
Risk management experts point out that spreadsheets do not scale with the complexity of alternative assets and private markets. Capital calls, waterfall calculations, valuation inputs, ESG metrics, and multi-jurisdictional tax data produce datasets that multiply exponentially. Yet many firms continue to manage these flows through files passed from inbox to inbox, each copy containing small divergences that erode integrity over time.
The irony is striking. Finance is an industry obsessed with precision, but which routinely entrusts essential operations to tools that offer none of the guarantees demanded of regulated systems.
The Paradox of Digitalisation
If technology budgets have soared and modern platforms proliferate, why do spreadsheets remain so entrenched?
The explanation lies in a structural contradiction. Digitalisation initiatives are generally conceived at the top of the organisation: transformation offices, IT architects, or strategic programmes. They produce roadmaps, select vendors, and deploy platforms. These systems almost always aim for standardisation, robustness, and controlled processes.
But the reality of financial operations does not follow standard patterns. Products differ by client, asset class, geography, or regulatory jurisdiction. Reporting templates shift constantly. Operating models involve multiple external providers—fund administrators, custodians, AIFMs, depositaries—each with their own systems and data definitions. The resulting complexity outpaces the ability of enterprise tools to adapt rapidly.
Front-line teams therefore rebuild flexibility where official systems cannot provide it. Excel becomes the bridge, the adapter, the temporary fix that becomes permanent, the unofficial layer allowing systems to cope with the unstructured reality of financial data.
Digitalisation therefore does not remove Excel; it often multiplies it. Each new system creates interfaces, exceptions, and transformation requirements that are easier to handle manually than through formal change requests. Transformation teams rarely measure this shadow dependency, but operations teams live within it daily.
Shadow IT — The Silent Counterculture
Nowhere is this disconnect more visible than in the phenomenon known as shadow IT. The term evokes unauthorised cloud storage or rogue SaaS subscriptions, but in finance it refers primarily to user-built workflows that operate beyond IT’s radar: macro-laden spreadsheets, personal reconciliation scripts, unregistered data pipelines, private databases, or even proprietary models maintained by individual teams.
Analysts automate NAV controls using VBA scripts inherited from colleagues long gone. Middle-office teams maintain internal datasets parallel to official golden sources because upstream systems are too slow or too rigid. Transfer agents create custom investor-level extracts that bypass data governance. Portfolio managers adjust risk models informally while waiting for IT to validate changes.
These unofficial architectures are neither anomalies nor occasional shortcuts. They are profoundly embedded within institutions. Gartner’s estimate—that 30% to 40% of technology spend occurs outside official IT governance—likely underestimates the scale in financial firms, where user ingenuity compensates for the slow pace of technological change.
Shadow IT allows institutions to function despite their own complexity, yet increases risk in ways seldom acknowledged. A single corrupted spreadsheet can freeze a valuation cycle. A single macro failure can delay regulatory filings. A single undocumented dataset can distort analytics feeding investment committees. When the “super user” maintaining these workarounds leaves the company, entire workflows may collapse.
This informal ecosystem is the industry’s open secret. It supports operations while undermining the credibility of digitalisation strategies. It persists because no platform, however sophisticated, can keep pace with the relentless evolution of regulatory and client demands.
A Global Pattern, with Regional Variations
The spreadsheet paradox is not a European anomaly—although the European Union’s regulatory regime amplifies the phenomenon. It is global.
In the United States, hedge funds and private equity firms often operate at the technological frontier, yet continue to rely heavily on spreadsheets for portfolio analytics, deal modelling, and risk overlays. The industry’s culture of autonomy reinforces this dependency.
In Asia, fragmented systems and heterogeneous regulatory frameworks push firms to rely on Excel as an integration layer. Rapid industry growth often outpaces the development of robust, centralised platforms.
Europe sits between the two extremes. Regulatory intensity drives the proliferation of spreadsheets, as firms scramble to comply with SFDR, AIFMD Annex IV, EMIR, PRIIPs, MiFID II, and a long list of national filings. Each reporting change introduces fresh layers of manual work, temporary models, and dataset recombinations.
Across all regions, the pattern is clear: spreadsheets thrive wherever systems, regulation, and organisational structures diverge. They absorb the inconsistencies of a globalised financial industry.
Luxembourg’s Silent Dependency
Luxembourg offers a particularly revealing microcosm. As the world’s leading cross-border fund centre, it handles a unique combination of complexity, volume, and regulatory oversight. The proliferation of RAIFs, SCSp structures, private equity and private debt vehicles, and multi-provider operating models generates operational flows that few systems manage natively.
The country’s fund administrators, transfer agents, and ManCos often operate across multiple jurisdictions and asset classes, each with their own templates, data definitions, and oversight expectations. Talent shortages in fund accounting, TA operations, and regulatory reporting compound these pressures. As a result, spreadsheets frequently serve as the glue binding together processes that no single system can fully accommodate.
Although no official statistics quantify Luxembourg’s spreadsheet dependency, industry practitioners consistently acknowledge it. Critical Excel files exist within most institutions, often maintained by a few key individuals whose departure would expose systemic fragility.
In a market built on operational reliability, this hidden dependency introduces a risk seldom addressed explicitly in governance discussions.
What Real Modernisation Requires
True digitalisation is not a question of replacing Excel with a single platform. It requires a deeper shift in mindset and governance. Data must be treated as an asset with lineage, ownership, and quality controls. Systems must be interconnected through APIs rather than fragmented exports. Regulatory reporting must be industrialised rather than stitched together manually. Middle- and back-office teams must be trained not only in new tools but in new ways of thinking about data flows. Change management must become a core discipline.
Transformation also demands a period of reinforced execution capacity. As institutions redesign operating models or migrate away from manual workflows, they must temporarily rely on additional expertise—data specialists, operational consultants, regulatory experts—capable of supporting transition without compromising day-to-day controls. Platforms such as We Put You in Touch facilitate precisely this type of flexible, vetted expertise without the frictions of traditional intermediaries.
The ultimate objective is not to eradicate Excel, but to restore it to its natural place: a powerful analytical tool, not the backbone of a regulated industry.
Conclusion — An Era Ending Slowly
Excel is a remarkable invention. Its flexibility has empowered generations of financial professionals. But an entire sector’s operational stability cannot continue to rest on tools that lack governance, scalability, and resilience.
As private markets expand, as regulatory scrutiny intensifies, and as investors demand near real-time transparency, the mismatch between the industry’s ambitions and its operational reality becomes increasingly untenable. The real challenge for financial institutions is not acquiring new technologies, but confronting the unspoken architecture of spreadsheets that underpins their daily operations.
Digitalisation will become credible only when the industry acknowledges this hidden infrastructure—and replaces it not with promises, but with durable, governed, and truly integrated systems.
References
- CFOTech — 2025 study highlighting that approximately 70% of CFOs continue to rely heavily on Excel for reporting, planning and forecasting.
- FundsTech — industry survey showing that around 73% of hedge funds remain over-reliant on spreadsheets for portfolio analytics and risk workflows.
- Wolters Kluwer — 2025 compliance survey revealing that 42% of financial institutions still use manual, spreadsheet-based processes for regulatory obligations.
- BakerHill — analysis outlining why spreadsheets are ill-suited for modern financial risk management and data governance.
- TerrapinTech — report on the operational and strategic risks faced by wealth and asset managers relying on spreadsheet-based architectures.
- Henricodolfing.com — detailed case study of the JPMorgan “London Whale” incident, including analysis of spreadsheet errors contributing to the loss.
- Cardo AI — research describing the risks of managing structured finance and private markets portfolios using Excel rather than purpose-built systems.
- ArXiv — academic paper examining spreadsheet dependency within financial departments and the organisational risks associated with uncontrolled spreadsheet usage.