RiskTech Forum

European DataWarehouse: European Loan Level Data: Smart Usage Beyond Asset-Backed Securities

Posted: 1 November 2016  |  Source: European DataWarehouse


Following the European Central Bank ABS loan-level initiative, which became operational in early 2013, European DataWarehouse as the centralised data repository has collected loan-level data for more than 50 million loans across Europe. While the primary purpose is to enhance transparency for ABS market participants, there are also important insights into loan markets more generally given the high granularity of data across issuers, asset classes, jurisdictions and time series. Moreover, the experience gathered so far can provide interesting lessons on data quality management.

European DataWarehouse (ED) is the first central data repository in Europe for collecting, validating and disseminating detailed, standardised and asset class specific loan level data (LLD) for Asset-Backed Securities (ABS). Developed, owned and operated by the market, ED facilitates risk assessment and improves transparency standards for European ABS deals.

More specifically, ED collects ABS deal, bond and loan level data according to the ECB ABS reporting templates. Simultaneously, ED also acts as a distributor of loan level data and documentation to subscribing entities such as investors, rating agencies, data vendors and analytic firms, investment and commercial banks, accounting firms, trustees and consultants.

A substantial amount of time and effort is constantly spent on improving the quality of the submitted data, along with its accessibility and usability.

Recently ED launched the ED Cloud Pro, a business intelligence solution that enables easy access to the entire universe of ED loan and bond level data.

This paper looks at three typical questions in relation to data projects:

1. What data is available and what are typical use cases - within and beyond the ABS market?
2. How to overcome the challenge of non-standardised data and other data quality issues?
3. How to make large quantities of data usable and easy to analyse?

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