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CASE STUDY - LoanPerformance Revitalizes Competitive Web-Based Analytics Service

Commentary by David Gussmann, Sr. VP Product Development & Operations, LoanPerformance

casestudy loanperformance
Executive Summary

LoanPerformance supplies risk management and financial analysis tools to industry giants like Fannie Mae, FreddieMac, Bank of America, JPMorgan Chase,Wells Fargo, and Washington Mutual. Loan Performance’s True Standings solution is a Web-based analytics solution that provides securities data to its customers.With Sybase IQ processing huge volumes of data, on-demand reports and queries are now delivered an average of 8 times—and up to 100 times—faster than before.

Customer Profile

Financial Services

Sybase Technology
Sybase IQ

Key Benefits

  • Increased analytics speed by an average of eight times
  • Queries taking more than 10 minutes reduced from 16 percent to less than 1 percent
  • Rapid implementation
  • Deployed on cost-effective Linux® platform
  • Scalable for users and data loads

LoanPerformance is a subsidiary of First American Corporation, a Fortune 500 company with more than 30,000 employees and revenues in excess of $6.5 billion. First American manages the largest property and ownership database in the U.S., covering 94 percent of the U.S. population and 97 percent of all mortgage transactions. A self-standing subsidiary, LoanPerformance provides state-of-theart technology predictive analytics and reporting capabilities to the world’s leading financial institutions that invest or trade in mortgage risk.

Business Challenge

An innovator in mortgage securities data, LoanPerformance was faced with growing their business and supplying solutions to increasingly demanding customer requirements while operating an efficient technology architecture. Two additional drivers were adding new Web-based capabilities and improving the existing functionality of analytic applications. As the central databases grew exponentially into the terabyte range, queries and reports were taking longer than anticipated,and customers grew weary of extended wait times for their information.One in 5 queries took longer than five minutes, and one in 20 queries would time out. In short, the IT team knew it was time to investigate alternatives beyond a traditional OLTP database on which to run their mission-critical analytics applications.

Selection Criteria

Knowing the future success of the company would ride on its ability to deliver fast, accurate, Web-based reporting, the IT team developed their standards forthe new solution. Simple queries must be delivered in under a minute, and complex queries in under 20 minutes.They also required enhanced attribute capabilities, faster load times, and scalability for thousands of concurrent users, as well as anticipated future data growth, both in fields and in record number.

Why Sybase?

During exhaustive head-to-head testing, Sybase IQ emerged as the leader inprice/performance. Even with increasing numbers of concurrent users, speed requirements were exceeded—at a lower cost than the competition. Other solutions, while meeting the baseline requirements, slowed dramatically when additional concurrent users were added. LoanPerformance selected Sybase IQ to allow the company to pursue their healthy growth plans while providing astounding performance on a low-cost Linux platform.


Installation of the new Sybase IQ system took only one week and delivered dramatic results immediately. Queries taking more than 10 minutes were reduced from 16 percent to less than 1 percent. LoanPerformance also saw an average speed increase of 8 times—and up to100 times—over the previous system, resulting in better customer service and better utilization of IT resources. Now LoanPerformance can continue to offer unparalleled Web-based analytics services and information from the industry’s largest, most comprehensive database at lightning-fast speeds. So now, when an investor asks, “How does my mortgage portfolio compare over time with themarket?” LoanPerformance can providethe answers. Online. Faster than they ever thought possible.

This article originally appeared in the issue of .

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