In the wake of the financial crisis, big banks need to go beyond siloed reporting to support rapid risk analysis and stress testing.

Doug Henschen, Executive Editor, Enterprise Apps

August 1, 2011

5 Min Read

8 Big Data Deployments In Detail

8 Big Data Deployments In Detail


(click image for larger view)
Slideshow: 8 Big DataDeployments In Detail

Let's say the debt deal collapses and the U.S. credit rating drops. Perhaps Greece finally goes into default or the next Lehman Brothers-scale institution fails. What will that mean to world's largest banks in terms of credit risk, compliance status, customer mix, and profitability?

Financial institutions can no longer take months to figure these things out. Enter the Oracle Financial Services Data Warehouse (OFSDW), an integrated platform designed for rapid insight and what-if analysis across portfolios, product lines, compliance demands, and internal performance objectives.

OFSDW incorporates everything from hardware, databases, and middleware to myriad financial applications. It's the most comprehensive and coordinated platform available for financial institutions, says Oracle, and the vendor insists it can't be matched by competitors.

Data warehousing demands are ramping up across many industries, but nowhere more dramatically than in the financial services industry. It's no longer a question of simply gathering monthly, weekly, or even daily data for periodic departmental reporting.

"Stress testing and enterprise-liquidity testing are among a whole new class of requirements that are compressing response times and what-if analysis need," said S. Ramikrishnan, group vice president and general manager for Oracle Financial Services Analytical Applications, in an interview. Ramikrishnan visited New York last week to promote OFSDW in the world's financial services capital.

U.S. and European regulators, for example, have been demanding periodic stress tests at large financial institutions since the financial meltdown of 2008. Regulations such as Basel III will make such tests a routine requirement. So what has required hundreds of employees and as long as six months of analysis at some banks will have to be achievable within as little as two weeks, Ramikrishnan said. On the liquidity front, large banks with 20 or 30 million customers will have to track hundreds of millions of cash flows and apply complex computations to gain insight within minutes of market changes, he said.

Oracle says OFSDW cuts the time and cost of sophisticated, cross-enterprise analyses with a unified application portfolio that runs on a common architecture, data model, analysis methodology, and reporting environment. This alone is unprecedented, as it unites disparate applications typically supplied by as many as half a dozen vendors, according to Ramikrishnan. What's more, OFSDW puts these apps on the common hardware and infrastructure of Oracle Exadata, so the apps can exploit the platform's in-database and parallel-processing analysis capabilities.

The results are "stunning," Ramikrishnan claimed. "We've fundamentally shrunk the latency between data loading, execution, and delivery of results," he said.

10 Tenets Of Enterprise Data Management

10 Tenets Of Enterprise Data Management


(click image for larger view)
Slideshow: 10 Tenets Of Enterprise Data Management

In one example, Oracle was able to load data on 200 million cash flows from the portfolio of a large bank onto the platform, perform what-if liquidity analyses, and deliver results for management action within half an hour, he said.

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.

ERP is old news, but enhancing legacy software with mobile, analytics, and social apps can deliver substantial new value. Also in the new, all-digital issue of InformationWeek: SaaS can create new data silos unless companies follow best practices to make those apps work with on-premises systems and data sources. Download the issue now. (Free registration required.)

About the Author(s)

Doug Henschen

Executive Editor, Enterprise Apps

Doug Henschen is Executive Editor of InformationWeek, where he covers the intersection of enterprise applications with information management, business intelligence, big data and analytics. He previously served as editor in chief of Intelligent Enterprise, editor in chief of Transform Magazine, and Executive Editor at DM News. He has covered IT and data-driven marketing for more than 15 years.

Never Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.

You May Also Like


More Insights