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UniCredit Develops Data Esperanto to Map End User Data Sets Across Group

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Italian banking group UniCredit is currently focused on extending the coverage of its data warehouse, which was rolled out in 2004, beyond accounting and regulatory reporting related data items to other reference data items, says Alberto Ricciotti, head of group pricing at the bank. A key success factor in this process has been in the data management team’s ability to engage internal and external end users of this data and the development of “Esperanto” between data sets, he explains.

“The main goal over the last two years and going forward is to improve the matching of data sources, develop common business understandings of data items and improve drill down capabilities,” says Ricciotti.

UniCredit began the process of rationalisation by evaluating end user requirements in terms of all players in the data management chain, including regulatory requirements and internal business users. This highlighted the need for greater regional data consistency, the ability to better track data along the credit process by matching local interpretation of data with central data processes and the requirement for greater drill down capabilities for end user analytical purposes.

“Data stewardship was a key method in engaging end users and these individuals are responsible for acting as a reference point for these users and are accountable for the data sets under their remit,” he explains. “The main challenge for UniCredit has been in dealing with the impact of the high level of M&A in which we have been engaged in over the last 10 years.”

The bank has a fairly siloed structure due to the bank’s recent history of acquisitions and this has caused data governance challenges, as well as the challenge of rationalising systems. The structure of the data sets varied across all these various systems and a lack of standardisation meant definitions of these data items had to be mapped carefully.

To this end, last year UniCredit kicked off a regime change to develop a data mapping layer between end user data dialects and centrally held data sets, which Ricciotti calls Esperanto. “The mapping process involved various stages including end user dialects, national official languages and Esperanto, which were all linked and mapped to enable us to build common definitions of clients and products across the group,” he elaborates.

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