Banks are used to dealing with data at scale. Increasingly, this includes a vast amount of third-party data, driven largely by regulation and compliance.
These data sources pose their own challenges, when it comes to storing, processing and sharing information. But third-party data is critical to banking operations, not least because of regulations including Anti Money Laundering (AML) Know Your Customer (KYC), risk, and even cybersecurity.
BNP Paribas operates banking and investment services across 64 countries, and employs some 180,000 staff. But it faced weak data quality, high costs – the bank estimates it spent up to €2 million ($2.3 million) a year on data copying, transformation, and reconciliation – and slow approval processes.
Adding a new data source could take a year, or more.
According to Bruno Micaelli, transformation leader and strategic program director, third-party data is a “strategic control point” for the bank.
Yet the Paris-headquartered bank found it hard to share third-party data internally, and lacked the infrastructure to provide a single, reliable and source of data for new projects, including AI. Its legacy central database was a mainframe application, supplemented with “a Java complementary layer”, Micaelli said.
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