XBRL Formula in use: Improving the quality of data Mark Montoya (FDIC) Víctor Morilla (Central Bank of Spain)

XBRL and the Bank of Spain Involved in the XBRL community since 2002 Founding member of XBRL Spain Working in the development of CEBS taxonomies Working in the deployment of systems and local taxonomies –New Basel’s Accord Solvency Information (COREP) –Reserved Statements of Financial Entities (FINREP) –Central Balance Sheet Data Office

Complexity of our filing process Some functions of the Bank of Spain imply the collection of data: –Promotion of the stability of the financial system –Preparation and publication of statistics –Gathering data for the European Central Bank Some numbers (credit institutions) –About statements per year –About different concepts managed –More than checks applied per year –More than data received per year –Data stored since 1985

Moving towards XBRL based solutions –2003: Pilot project to receive information from appraisal companies –2004: Project for leading and planning the deployment of XBRL at the Bank of Spain2004: Infrastructure for development and deployment of XBRL systems –2005: System for the submission of public statements Under development: –New Basel’s Accord Solvency Information –Central Balance Sheet Data Office questionnaires –Reserved Statements of Financial Entities

Why XBRL formula ? Some requirements not covered by current spec –Arithmetic comparisons –Conditional expressions –Operations between different contexts –Aggregation of dimension members –Checking for the presence of concepts if some rules apply –Mandatory comments XBRL Formula features –A formal language –To express business rules –Standard –Allowing validation at the origin –Benefits from other institutions’ experience

Sender Receiver Developing business rules (classic reporting system) IT developer System requirements Business rules IT developer Business user Business user IT analyst System requirements C Code C IT analyst

Sender Receiver Developing business rules (using XBRL Formula) Business user IT analyst Business rules XBRL Taxonomy Business user

Sender Receiver Data filing process timeline (classic reporting system) Data extraction & transformation Errors detected Analysis and corrections Data extraction & transformation Validation OK Analysis Notification

Sender Receiver Data filing process timeline (using XBRL Formula) Data extraction & local validation Analysis And corrections Analysis Validation OK

Receiver Sender More than 400 credit institutions

Conclusions XBRL Formula will help regulators: –Improving the quality of data –Increasing the efficiency of the reporting process –Reducing time and costs to develop new reporting solutions

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