Case Study: ETL Solutions

The Client Government Sponsored Enterprise (GSE) Talk ScopeGet a Demo The Problem The client needed ETL solutions for handling data of any complexity or size in a variety of formats and/or from different upstream sources.​ The client’s data management team extracted and processed data from different sources and different types of databases (e.g. Oracle, Netezza, Excel files, SAS datasets, etc.), and needed to...ShareTweetShare

riskspan case study

SOFR, So Good? The Main Anxieties Around the LIBOR Transition

SOFR Replacing LIBOR The London Interbank Offered Rate (LIBOR) is going away, and the international financial community is working hard to plan for and mitigate risks to make a smooth transition. In the United States, the Federal Reserve’s Alternative Reference Rates Committee (ARRC) has recommended the Secured Overnight Financing Rate (SOFR) as the preferred replacement rate. The New York Fed began publishing SOFR regularly on April 3,...ShareTweetShare

sofr replacing libor

Case Study: Loan-Level Capital Reporting Environment​

The Client Government Sponsored Enterprise (GSE) Talk ScopeGet a Demo The Problem A GSE and large mortgage securitizer maintained data from multiple work streams in several disparate systems, provided at different frequencies. Quarterly and ad-hoc data aggregation, consolidation, reporting and analytics required a significant amount of time and personnel hours. ​ The client desired configurable integration with source systems, automated acquisition of over 375 million records and performance improvements...ShareTweetShare

riskspan case study

Case Study: Securitization Disclosure File Creation Process

The Client Private Label Mortgage-Backed Security Issuer  Talk Scope The Problem The client issues private label MBS with sources from multiple origination channels. In accordance with industry requirements, the client needed to create and make available to securitization counterparties a loan-level data file (the “ASF File”) which has been defined and endorsed by the Structured Finance Industry Group. ​ The process of extraction and aggregation was...ShareTweetShare

riskspan case study

What is LIBOR and why is it Going Away?

What is LIBOR The London Interbank Offered Rate (LIBOR) is a reference rate, and over time since the 1980s has become the dominant rate for most adjustable-rate financial products. A group of banks (panel banks) voluntarily report the estimated transaction cost for unsecured bank-to-bank borrowing terms ranging from overnight to one year for various currencies....ShareTweetShare

A Primer on HECM Loans

In September, RiskSpan announced the addition of Ginnie Mae’s loan-level Home Equity Conversion Mortgage (“HECM”) dataset to the Edge platform. The dataset contains over 330,000 HECM loans with origination dates from 2000 to 2018 and reporting periods from August 2013 to October 2018.   This post is a primer on HECM loans, the HMBS securities they collateralize, and the structure of the new dataset.  What is a HECM?  HECMs are FHA-insured reverse mortgages that provide people 62 and older with cash payments or a line of credit… ShareTweetShare

Big Companies; Big Data Issues

Data issues plague organizations of all sorts and sizes. But generally, the bigger the dataset, and the more transformations the data goes through, the greater the likelihood of problems. Organizations take in data from many different sources, including social media, third-party vendors and other structured and unstructured origins, resulting in massive and complex data storage… ShareTweetShare

MDM to the Rescue for Financial Institutions

Data becomes an asset only when it is efficiently harnessed and managed. Because firms tend to evolve into silos, their data often gets organized that way as well, resulting in multiple references and unnecessary duplication of data that dilute its value. Master Data Management (MDM) architecture helps to avoid these and other pitfalls by applying… ShareTweetShare

Join Us: Webinar – Using Machine Learning in Whole Loan Data Prep

Register for our webinar on June 26th at 11:30 am, where we cover Using Machine Learning in Whole Loan Data Prep. One of the biggest obstacles to managing whole loan data is curating and normalizing multiple, disparate data sets. A field such as ‘interest rate’ may be formatted seven different ways from seven different sources, and… ShareTweetShare