Track 4 Title: How XBRL Facilitates the Electronic Collection of Financial Information for Credit Risk Rating, Name: Igno J. Dekker, Business Architect,

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Presentation transcript:

Track 4 Title: How XBRL Facilitates the Electronic Collection of Financial Information for Credit Risk Rating, Name: Igno J. Dekker, Business Architect, ABN AMRO Bank, The Netherlands. Date: Thursday, June – 12.30

 Flash back  Observations  Developments in banking sector  (Dis)Advantages Banking Taxonomy  Agreement Government and banks

Flash back  Goal SBR NL: reducing administrative burden - by semantic and technical standardization - and ensure the connection between the taxonomy and the law  In 2007 the Dutch taxonomy was available: mission completed! - number of data elements dropped from more than  in practice the taxonomy was used by professionals for interpreting law and regulations, and accounting practices - advantages of the Dutch taxonomy were and are beyond doubt - there was and is a growing interest in the concept - banks did not participate until October 2007 … but…

Observations  “What in it for me?“  Organisational problems  Is there a political and corporate need?  Ultimately, it comes down to moderating the chain

Developments in banking sector  Fulfil Basel II requirements 1. Program lending vs. Non-program lending 2. Automated creditscoring based on bankspecific models  Increase data quality: standardization and prevent data entry mistakes by electronically exchange of annual account information  Investigate the possibility of an online, realtime end-to-end credit process for program lending products  The need to get more credit specific information from the annual account data

Bank extension on Dutch Taxonomy  In close cooperation between two banks, two financial intermediaries and the SBR operational office, the data elements for the credit process of Program Lending products are specified and defined  Starting point was: the Dutch Taxonomy on tax basis, built in 2007  Bank extension means that the data required for the credit process are standardized for the credit lines until € 1 mln.

SBR: three interconnected layers

Examples of detail information  The Dutch Tax Administration is interested in the total amount of fixed assets. The banks are interested in the tax and market value of the individual objects  The tax administration needs the total amounts of debtors and creditors. The banks are interested in the next specification: Specify number/ amount Debtors & Creditors 0 – 30 days 30 – 60 days 60 – 90 days > 90 days

Advantages business entity  Data exchange to different parties (Tax Administration, Chamber of Commerce, Statistics Office) from one administration point  Taxonomy connected to accounting software. Data can be generated automatically.  Apply for credit can be answered online, real-time in the near future  Apply for credit via internet channel Disadvantage  Bank extension needs additional data on top of tax administration

Advantages financial intermediary  No difference between commercial and fiscal annual account  Paper output will be replaced by electronical output  Validation of in between information means additional work  More attention for benchmarking Disadvantage  Decreasing efforts of accountant by standardization

Advantages Bank  One valuation standard  One point of data generation  No manual data entry  Higher frequency of data exchange. Improvement credit control  Increasing quality of data and credit risk models Disadvantage  It becomes much easier to apply for more than one quotation

Agreement Government and Banks  Major problem: Dutch Taxonomy and bank extension are defined, but how can both parties mobilize/”bootstrap” the market  Solution: Joint efforts of Government and banks to stimulate the use of the Dutch taxonomy included the bank extension. Agreement signed on June.9 th 2009