The statements are accepted because checking them is impractical
Volume and format variety make manual verification impossible, so income is reconciled at the total and never at the line.
IP and royalties
Royalty statements turned into revenue you can actually check
Statements from every payer ingested, normalised and matched to the underlying rights, so income is verified rather than accepted and forecasting has something to stand on.
Royalty income arrives as hundreds of statements in dozens of formats, on different periods, with different identifiers, and most rights holders accept the total because checking it by hand is not feasible. We build the ingestion and matching layer so statements are normalised against the catalogue, underpayment is detectable, and forecasts are built on the income history rather than on a payer summary.
Discuss your operationWhat we usually find
The problems that come up in almost every one of these businesses.
Identifiers do not match across payers
The same work carries different identifiers in different systems, and without a resolved catalogue the income cannot be attributed reliably.
Forecasting runs on a payer summary
Projections are built from headline totals rather than from the decay and seasonality visible in the underlying lines.
Where we start
What the first engagement usually covers.
Scope depends on the state of your systems. These are the pieces that recur in this sector.
Statement ingestion
Every payer format parsed into one structure, on consistent periods, with the failures surfaced rather than dropped.
Rights and catalogue matching
Identifiers resolved against the catalogue so income attaches to the right work, writer or asset share.
Underpayment detection
Expected against received, by work and payer, so a shortfall is a flagged exception rather than an unnoticed loss.
Income forecasting
Decay curves and seasonality built from the line-level history, which is also what a valuation or a securitisation will want.
What changes
What is different afterwards.
You own all of it: the code, the written definitions and documentation aimed at whoever maintains this after us.
- Every payer statement in one normalised structure
- Income attributed to the correct work and share
- Underpayment surfaced as an exception
- Forecasts built on line-level history
The builds behind it
Sector knowledge decides the order. The builds are the same four.
Single source of truth
Your finance, customer and operational records joined into one dataset, with each figure defined once and traceable back to the system it came from.
Analytics layer
Reporting built on top of the joined data, aimed at the few revenue and cost drivers that actually change the result.
Workflows
One defined task, automated inside a process that already exists, measured against whatever it replaced.
Financial modelling
Driver-based models built on the same definitions as your reporting, so the forecast and the actuals stop disagreeing.
Worth asking
Questions this tends to answer.
- Are we being paid what we are owed?
- Which works and payers actually drive the income?
- What does this catalogue earn over the next five years?
- Could we support a valuation or a financing with this data?