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RiskSpan Expands Private Credit Solution to Include Residential Transition ...
Arlington, VA – July 18, 2024 – RiskSpan, a leading technology provider of innovative risk management and data analytics for securities, loans and private credit,
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AI Prompt Structuring — Does it Even Matter?
At the mesh point of human ingenuity and artificial intelligence, the importance of appropriately structured prompts is frequently underestimated. Within this dynamic (and, at times,
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MSR Tape to Bid in 6 Easy Steps
Creating an MSR bid using RiskSpan's Edge Platform is designed to be easy. How easy? So easy that we challenged a user to create a
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Get Free Access to RiskSpan’s Non-Agency Performance Trends Dashboard
The latest addition to RiskSpan’s free RS Insights dashboard enables users to delve into insightful non-Agency delinquency trends. Slice and dice CoreLogic loan-level data by
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RiskSpan Launches MBS Loan Level Historical Data on Snowflake Marketplace
ARLINGTON, Va., June 18, 2024 – RiskSpan, a leading provider of data analytics and risk management solutions for the mortgage industry, announced today that it
![The newest, fastest and easiest way to access and analyze Agency MBS data](https://riskspan.com/wp-content/uploads/2024/05/Snowflake-Marketplace-blog-hero-1024x576.png)
The newest, fastest and easiest way to access and analyze Agency MBS data
TL;DR Summary of Benefits Data normalization and enhancement: RiskSpan’s MBS data on Snowflake normalizes Fannie, Freddie, and Ginnie loan-level data, consolidating everything into one set
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Transforming Loan Data Management Using Snowflake Secure Data Sharing
Presenters Paul Gross Senior Quantitative Analyst, Rithm Capital Michael Cowley Principal, Data Cloud Products, Snowflake Bernadette Kogler CEO, RiskSpan Suhrud Dagli CTO, RiskSpan Wednesday, May
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Snowflake and the Future of Data Sharing Across Financial Institutions
The digitization of the financial services industry has opened countless doors to streamlining operations, building customer bases, and more accurately modeling risk. Capitalizing on these
![Loans & MSRs: Managing model assumptions and tuners the easy way](https://riskspan.com/wp-content/uploads/2024/04/hidden-features-background-1024x576.png)
Loans & MSRs: Managing model assumptions and tuners the easy way
One of the things that makes modeling loan and MSR cash flows hard is appropriately applying assumptions to individual loans. Creating appropriate assumptions for each
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How an MSR Analytical Solution Can Boost Your Mortgage Banking Business
And why it's probably less expensive than you think Mortgage servicing rights (MSRs) are complex and volatile assets that require careful management and analysis. Inherent
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What Do 2024 Origination Trends Mean for MSRs?
While mortgage rates remain stubbornly high by recent historical standards, accurately forecasting MSR performance and valuations requires a thoughtful evaluation of loan characteristics that go
![GenAI Applications for Loans and Mapping Data](https://riskspan.com/wp-content/uploads/2024/03/Picture2-1024x576.png)
GenAI Applications for Loans and Mapping Data
RiskSpan is actively furthering the advancement of several GenAI applications aimed at transforming how mortgage loan and private credit investors work and maximizing their efficiency
Our Insights
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A Brief Introduction to Agile Philosophy
Reducing time to delivery by developing in smaller incremental chunks and incorporating an ability to pivot is the cornerstone of
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Hands-On Machine Learning–Predicting Loan Delinquency
The ability of machine learning models to predict loan performance makes them particularly interesting to lenders and fixed-income investors. This
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Back-Testing: Using RS Edge to Validate a Prepayment Model
Most asset-liability management (ALM) models contain an embedded prepayment model for residential mortgage loans. To gauge their accuracy, prepayment modelers
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Why Model Validation Does Not Eliminate Spreadsheet Risk
Model risk managers invest considerable time in determining which spreadsheets qualify as models, which are end-user computing (EUC) applications, and
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AML Models: Applying Model Validation Principles to Non-Models
Anti-money-laundering (AML) solutions have no business being classified as models. To be sure, AML “models” are sophisticated, complex, and vitally
![data governance](https://riskspan.com/wp-content/uploads/2020/06/model-validation-1.jpg)
Machine Learning Model Selection
Machine learning model selection is the second step of the machine learning process, following variable selection and data cleansing. Selecting
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End-User Computing Controls – Building an EUC Inventory
An accounting manager at a mid-sized bank recently wondered aloud to us how to approach implementing end-user computing controls (EUC).
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What is an “S-Curve” and Does it Matter if it Varies by Servicer?
Mortgage analysts refer to graphs plotting prepayment rates against the interest rate incentive for refinancing as “S-curves” because the resulting
![data governance](https://riskspan.com/wp-content/uploads/2020/06/model-validation-1.jpg)
Validating Interest Rate Models
Many model validations—particularly validations of market risk models, ALM models, and mortgage servicing rights valuation models—require validators to evaluate an
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AML Model Validation: Effective Process Verification Requires Thorough Documentation
Increasing regulatory scrutiny due to the catastrophic risk associated with anti-money-laundering (AML) non-compliance is prompting many banks to tighten up
![data governance](https://riskspan.com/wp-content/uploads/2020/06/model-validation-1.jpg)
Mitigating EUC Risk Using Model Validation Principles
The challenge associated with simply gauging the risk associated with “end user computing” applications (EUCs)— let alone managing it—is both
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Open Source Governance: Three Potential Risks
For many companies, the question is no longer whether to use open-source tools, but rather how to implement them with
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