Why would our customers need amendment data instead of plain amortisation tables?

**Why would our customers need amendment data instead of plain amortisation tables?**

A plain table answers one question: what are the instalments if nothing changes. Most agent and automation work starts after something changes. A customer asks for a later due date, a payment fails, an employer pays early, or an approver declines a request.

Amendment data adds the parts a table cannot carry:

- the request and who made it - the policy that was applied and the limit that was checked - the approval or refusal, with the handover between roles - the before and after schedule, linked by identifiers - the follow-on effects, such as notices, arrears flags and reconciliation tasks

For a reseller, this lets you offer buyers a dataset that supports both training and evaluation of tool-using agents, not just numeric forecasting. It also gives you a clearer way to describe differences between releases in your catalogue.

**Is it real data?** No. MirrorFirm output is generated, informed by direct observation of how real businesses operate. Your customers should still inspect grounding and disclosure risk, and nothing about generation guarantees anonymity or compliance.