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National Asset Management Agency

617 spending records on file.

Transparency Score

1.3/5

26% transparent

Machine readable 0.0/1

Descriptions 0.9/1

Uniqueness 0.1/1

Supplier number 0.0/1

Supplier name 0.3/1

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Payment date^*	Description	Kind	Publication	Amount
30 Jun 2016	Portfolio Management	Purchase Order	Q2 2016	€827,516.36
30 Jun 2016	Borrower Recoverable	Purchase Order	Q2 2016	€1,368,843.88
30 Jun 2016	Loan Sales	Purchase Order	Q2 2016	€1,767,395.06
30 Jun 2016	Primary Servicer	Purchase Order	Q2 2016	€6,653,405.68
30 Jun 2016	NTMA Recharge	Purchase Order	Q2 2016	€12,466,425.76
31 Mar 2016	Tax Advisory	Purchase Order	Q1 2016	€33,025.50
31 Mar 2016	Research & Publications	Purchase Order	Q1 2016	€33,333.79
31 Mar 2016	Occupancy Costs	Purchase Order	Q1 2016	€95,050.79
31 Mar 2016	IT Costs	Purchase Order	Q1 2016	€182,607.15
31 Mar 2016	Accounting & Audit	Purchase Order	Q1 2016	€250,513.72
31 Mar 2016	Master Servicer	Purchase Order	Q1 2016	€387,191.83
31 Mar 2016	Legal Fees	Purchase Order	Q1 2016	€543,202.95
31 Mar 2016	Portfolio Management	Purchase Order	Q1 2016	€637,296.89
31 Mar 2016	Borrower Recoverable	Purchase Order	Q1 2016	€1,515,467.97
31 Mar 2016	Loan Sales	Purchase Order	Q1 2016	€4,769,339.48
31 Mar 2016	Primary Servicer	Purchase Order	Q1 2016	€8,673,599.55
31 Mar 2016	NTMA Recharge	Purchase Order	Q1 2016	€13,408,024.69

^* Payment date may be the end of the reporting quarter when the entity does not publish an exact date.

How to read these figures

These are reported values from published purchase order and payment records — not verified cash paid, and not total spending by this organisation. A row may be a purchase order, a payment, or another reported transaction; the source files often do not say which.

Coverage and quality vary. Some fields are blank, supplier names are free text (the same firm can appear under many labels), and descriptions are inconsistent rather than a controlled taxonomy. An amount alone says nothing about value for money and it may or may not include VAT.

Records are retrieved from each organisation’s published files such as spreadsheets, PDFs, and other formats of uneven quality. Extraction techniques (including automated parsing) can introduce gaps, misreads, or incomplete rows when source layout or quality is poor. Treat the data as a starting point for investigation, not a definitive ledger.

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National Asset Management Agency

Transparency Score

Spending per quarter