Plenty of top banks are embracing OFSDW, Ramikrishnan said, but he declined to name names because banks won't talk about such sensitive competitive and regulatory-related matters, he said.
Oracle has offered analytical applications for financial services for some time, but with OFSDW, they're engineered and packaged to work together with an Exadata-based data warehouse. The target market is large, diversified bank holding companies that have multiple lines of business and, therefore, a need to bring together analyses of retail and commercial banking, brokerage, trading desks, and related market-risk analysis.
Regulators are demanding unified reporting across all these activities, said Ramikrishnan, so it's a key differentiator for OFSDW. He contrasts the approach with best-of-breed financial applications that might address one or two needs but that can't be blended because they run on disparate data models.
"The competitors that do the applications don't do the database and infrastructure and the guys that do the database and data warehousing don't do the apps," he said. That puts SAS, Teradata, and IBM at a disadvantage, he said, because "they don't have the assets."
That may be overstating the case, as all three of these competitors as well as SAP offer broad capabilities cutting across many of the same demands addressed by OFSDW. There also are partnerships whereby SAS analytics, for example, can be run with in-database processing performance on the Teradata data warehousing platform.
What's more, large financial institutions invariably have many applications already in place, so the opportunities to start with a clean slate with OFSDW will be rare.
Acknowledging incumbencies as well as the fact that not every institution will require every app, Ramikrishnan said the OFSDW applications are offered a-la-carte, so enterprises can add what they need to the platform as required.
It's easy to question whether hardware and databases need to be part of a comprehensive financial services applications package, but there's no doubt that OFSDW's unified data model and ability to synthesize results from across otherwise disparate operations will be attractive.
"Companies tend to spend a lot of money trying to source data into siloed applications, and then they spend a lot more money reconciling the data," Ramikrishnan said.
By eliminating disparate data models, redundant data-integration steps, and related controls and quality checks, Oracle is lowering the cost and complexity financial services will face to cope with an increasingly demanding business and regulatory environment.
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