Reduce Loan Delinquencies and Defaults with Loan Pool Analysis

The Informatica solution for mortgage pool analysis automates data collection and exchange in B2B distribution channels to streamline loan pool evaluation processes. The solution enables timely and accurate mortgage data management, which, in turn, optimizes the use of all analysis modeling techniques.

  • Decrease loan pool analysis risk and better manage risk overall
  • Reduce core operational costs involved in portfolio evaluation
  • Increase operational efficiency by managing broad business channels and maintaining more control over business transactions
  • Facilitate regulatory compliance and corporate governance and transparency by providing reliable audit trails

Mortgage Pool Analysis Challenges

With the recent rise in mortgage delinquencies and defaults, your company is looking to sharpen its analysis of loan pools. Loan pool evaluation involves collecting data from a variety of service providers, mortgage originators, and database systems. This data comes in a wide variety of formats—predominantly in Excel spreadsheets, but also Word documents and PDFs. And you don’t know whether this data is complete, current, or accurate.

You need to normalize this data so that it can be included in your analysis models. This manual process is cumbersome and time consuming. Normalization can require expensive IT intervention, increase error rates, and decrease bidding effectiveness. And it forces your experts to spend their time on manual normalization of data instead of examining that data.

Mortgage Pool Analysis Solution Key Features

  • Access all data —regardless of its source or structure—from arcane mainframe systems, from relational databases and applications, and from Excel spreadsheets, Word documents, and PDFs
  • Convert structured and unstructured data to and from more broadly consumable data formats to support business-to-business and multiple-enterprise transactions
  • Profile data to deliver a complete and completely accurate picture of the content, quality, and structure of securities data so that data quality issues can be resolved
  • Conduct high-precision, high-performance searches on identity data to find matches accurately and quickly, regardless of language, structure, format, location, duplication, omissions, or errors
  • Analyze and cleanse all data —including securities data—and measure, monitor, track, and report on data quality at multiple points across your company
  • Integrate massive volumes of real-time transactional and analytical data —residing both inside and outside the enterprise