Purchase Orders Over €20,000 Q2 2018

Spending records

Payment date^*	Supplier	Description	Kind	Amount
30 Jun 2018	Dublin 2 D02 Ireland www.finance.gov.ie @IRLDeptFinance	R	Purchase Order	€583.00
30 Jun 2018	Financial Services & Pensions Ombudsman Government Buildings Upper Merrion Street	Q4. 2018 Drawdown of Excheque	Purchase Order	€237,500.00
30 Jun 2018	Financial Services & Pensions Ombudsman	Q3. 2018 Drawdown of Excheque	Purchase Order	€237,500.00
30 Jun 2018	Financial Services & Pensions Ombudsman	Q2. 2018 Drawdown of Excheque	Purchase Order	€237,500.00
30 Jun 2018	Financial Services & Pensions Ombudsman	Q1 2018 Drawdown of Excheque	Purchase Order	€237,500.00
30 Jun 2018	Bruegel AISBL Centre Euro	Annual Subscription 201	Purchase Order	€66,406.00
30 Jun 2018	Dept. Of Foreign Affairs	Secondee Cost	Purchase Order	€27,737.00
30 Jun 2018	Arthur Cox	Legal Advi	Purchase Order	€21,829.00
30 Jun 2018	Arthur Cox	Legal Advi	Purchase Order	€43,113.00
30 Jun 2018	Arthur Cox	Legal Advi	Purchase Order	€54,421.00
30 Jun 2018	William Fry	Legal Advi	Purchase Order	€30,069.00
30 Jun 2018	William Fry	Legal Advi	Purchase Order	€80,279.00
30 Jun 2018	William Fry	Legal Advi	Purchase Order	€39,011.00
30 Jun 2018	William Fry	Legal Advi	Purchase Order	€109,859.00
30 Jun 2018	William Fry	Legal Advi	Purchase Order	€26,124.00

^* 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