Purchase Orders Over €20,000 Q4 2021

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2021	King & Spalding LLP	Legal Deals	Purchase Order	€23,900.13
31 Dec 2021	PricewaterhouseCoopers	Consultancy Fees	Purchase Order	€48,013.00
31 Dec 2021	Arthur Cox	Legal Fees	Purchase Order	€38,632.50
31 Dec 2021	Arthur Cox	Legal Deals	Purchase Order	€35,000.00
31 Dec 2021	KPMG	Tax Fees	Purchase Order	€81,500.00
31 Dec 2021	Baker & McKenzie LLP	Legal Deals	Purchase Order	€245,967.92
31 Dec 2021	Lowenstein Sandler	Legal Deals	Purchase Order	€27,138.59
31 Dec 2021	Lowenstein Sandler	Legal Deals	Purchase Order	€223,963.93
31 Dec 2021	Bank of New York Mellon	Global Custodian Fees	Purchase Order	€49,727.10
31 Dec 2021	Bank of New York Mellon	Global Custodian Fees	Purchase Order	€48,589.70
31 Dec 2021	Bank of New York Mellon	Global Custodian Fees	Purchase Order	€118,349.40
31 Dec 2021	Bank of New York Mellon	Global Custodian Fees	Purchase Order	€49,201.90
31 Dec 2021	Bank of New York Mellon	Global Custodian Fees	Purchase Order	€64,796.81
31 Dec 2021	Irish Life Investment Managers	Investment Manager Fees	Purchase Order	€561,174.33
31 Dec 2021	Goldman Sachs Asset Management International	Investment Manager Fees	Purchase Order	€1,625,502.77

^* 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.

Here is a project that encountered similar issues