Under FRS 102 para 18.8C, internally generated customer lists and items similar in substance are never capitalised — they're expensed as incurred. Separately acquired intangibles, by contrast, are recognised at cost. The result: the same data, built organically vs. bought, gets opposite treatment on the balance sheet.
Under FRS 102 para 18.8C(a), internally generated brands, logos, publishing titles, customer lists, and items similar in substance are never capitalised. A multi-source geospatial data compilation is not explicitly named in the standard; it is mapped to "items similar in substance" — a defensible interpretation, but a judgment call, not a settled rule. Separately acquired intangibles are recognised at cost (para 18.8). Intangibles acquired in a business combination are recognised at fair value (para 18.8, conditions (a)–(c)). The result: the same data, built organically vs. bought, gets opposite treatment on the balance sheet.
| Asset Origin | Accounting Treatment | Balance Sheet Impact |
|---|---|---|
| Organic / internally generatedData compilations, customer lists, brands | Never capitalised (FRS 102 para 18.8C(a)). Expensed as incurred. | Off-balance |
| Separately acquiredAsset purchase, license grant | Capitalised at cost (para 18.8). Amortised over useful life. | On-balance |
| Business combinationPPA at acquisition date | Recognised at fair value (para 18.8). Amortised over useful life. | On-balance |
| Development costsSoftware, models (para 18.8H criteria met) | Capitalisable if all six criteria satisfied. Rare in practice. | Conditional |
The organic dataset — 5+ years of accumulated, multi-sourced, ground-truth-validated foot-traffic intelligence — falls under the para 18.8C(a) prohibition as an item similar in substance to a customer list or data compilation. It is never on the balance sheet. The same data, had it arrived via the Tamoco asset purchase, would be. That gap is a structural feature of FRS 102, not an error.
| Input Category | Typical Structure | FRS 102 Treatment | Balance Sheet |
|---|---|---|---|
| Mobile-location panelsPanel partners | Term-based data license. Annual or multi-year. | License cost → expense over term. Data itself: no asset recognised. | COGS |
| In-store sensorsSensor networks / retailers | Term agreements with sensor networks / retailers. | License cost → expense. Validation data: no asset. | COGS |
| TransUnion CAMEOPsychographic segmentation partnership | Negotiated term license. | License cost → expense over term. | COGS |
| Sales dataRetailer POS / transaction feeds | Term-based data-sharing agreements. | License cost → expense. No asset recognised. | COGS |
| Predictive model (NeuralProphet extension)90-day foot-traffic forecast, Stanford collaboration | Internally developed on open-source base (Apache 2.0). Contributions returned upstream. | Development costs: capitalisable only if para 18.8H criteria met. In practice, likely expensed. | Conditional |
| Tamoco assets (acquired Oct 2023)Geospatial data, technology, operational assets | Asset purchase. | Recognised as separately acquired intangible under FRS 102 para 18.8. Capitalised at cost. Amortised over useful life. | On-balance |
| Organic data asset5+ years, multi-sourced, ground-truth-validated | Built organically since 2017 (Olvin era). Never went through a PPA or acquisition. | FRS 102 para 18.8C(a): never capitalised. Carried at zero. | Off-balance |
You acquired the Tamoco assets in October 2023. That purchase was recognised as a separately acquired intangible under FRS 102 para 18.8 — capitalised at cost, amortising over its useful life. It's on the balance sheet. Your investors can see it.
The key point: the Tamoco assets went through a formal recognition event. The 5+ year organic dataset did not. It sits at zero on the balance sheet while generating the revenue your 60+ retailers, Exabel, and Dewey pay for. This is the correct treatment under FRS 102. The zero is not an error — it is what the standard requires. The practical consequence is that the balance sheet does not reflect the economic value of the organic dataset, and that gap will need to be addressed in any financing conversation through a separate valuation narrative, not through a change in accounting treatment.
| Instrument | Fit | Why |
|---|---|---|
| Revenue-based financingRecurring license revenue | Strong | 60+ retailer subscriptions, Exabel alt-data feeds, Dewey research licenses. Predictable, contract-backed recurring revenue is the cleanest RBF collateral. The organic data asset is the revenue engine — even at zero carrying value, it's the cash-flow source. |
| Receivables / factoringExisting license receivables | Good | Named enterprise-retailer license receivables are factorable. Caveat: revenue base is small (~$1–5M), so facility size is limited. Best as a bridge, not a core structure. |
| IP-backed lendingStructured credit on data IP | Partial | Owns Tamoco assets (on-balance, amortising) + organic dataset (off-balance, zero). The on-balance IP is collateralisable but small. The organic dataset is the real value but needs a standalone valuation to serve as collateral. Nascent market for data-IP lending. |
| Trade finance / working capitalAs licensee (upstream data purchases) | Good | As a data licensee, pass_by pays for mobile panels, TransUnion CAMEO, sensor networks, sales data feeds. Payables financing / working-capital lines against those purchase commitments are straightforward. |
The Tamoco asset purchase was October 2023. The organic dataset has been generating revenue since 2017 (Olvin era). You're at a point where the next raise or credit conversation will force the question: what is the data asset actually worth, and why is it at zero on the books? Mapping the term/perpetual ratio across the 15+ inputs — and documenting the revenue it generates — is the answer. Do it before it's asked for.