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Category: Case Study

Case Study: Datamart Design and Build

The Client

Government Sponsored Enterprise (GSE)

The Problem

A GSE needed a centralized data solution for its forecasting process which involved cross-functional teams from different business lines (Single Family, Multi Family, Capital Markets).​

The client also needed a cloud-based data warehouse to host forecasting outputs for reporting purpose with a faster querying and processing speed.​

The input and output files and datasets came from different sources and/or in different formats. Analysis and transformation were required prior to designing, developing and loading tables. The client was also migrating data from legacy data sources to new datamarts. 

The Solution

RiskSpan was engaged to build and maintain a new centralized datamart (in both Oracle and Amazon Web Services) for the client’s revenue and loss forecasting processes. This included data modeling, historical data upload as well as the monthly recurring data process.

The Deliverables

  • Analyzed the end-to-end data flow and data elements​
  • Designed data models satisfying business requirements​
  • Processed and mapped forecasting input and output files​
  • Migrated data from legacy databases to the new sources ​
  • Built an Oracle datamart and a cloud-based data warehouse (Amazon Web Services) ​
  • Led development team to develop schemas, tables and views, process scripts to maintain data updates and table partitioning logic​
  • Resolved data issues with the source and assisted in reconciliation of results

Case Study: ETL Solutions

The Client

Government Sponsored Enterprise (GSE)

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 load into its Oracle and AWS datamarts for it’s revenue and loss forecasting processes. ​

The client’s forecasting process used very complex large-scale datasets in different formats which needed to be consumed and loaded in an automated and timely manner.

The Solution

RiskSpan was engaged to design, develop and implement ETL (Extract, Transform and Load) solutions for handling input and output data for the client’s revenue and loss forecasting processes. This included dealing with large volumes of data and multiple source systems, transforming and loading data to and from data marts and data ware houses.

The Deliverables

  • Analyzed data sources and developed ETL strategies for different data types and sources​
  • Performed source target mapping in support of report and warehouse technical designs​
  • Implemented business-driven requirements using Informatica ​
  • Collaborated with cross-functional business and development teams to document ETL requirements and turn them into ETL jobs ​
  • Optimized, developed, and maintained integration solutions as necessary to connect legacy data stores and the data warehouses

Case Study: Web Based Data Application Build

The Client

Government Sponsored Enterprise (GSE)

The Problem

The Structured Transactions group of a GSE needed to offer a simpler way for broker-dealers to  create new restructured securities (improved ease of use), that provided flexibility to do business at any hour and reduce the dependence on Structured Transactions team members’ availability. 

The Solution

RiskSpan led the development of a customer-facing web-based application for a GSE. Their structured transactions clients use the application to independently create pools of pools and re-combinable REMIC exchanges (RCRs) with existing pooling and pricing requirements.​

RiskSpan delivered the complete end-to-end technical implementation of the new portal.

The Deliverables

  • Development included self-service web portal that provides RCR, pool-of-pool exchange capabilities, reporting features ​
  • Managed data flows from various internal sources to the portal, providing real-time calculations​
  • Latest technology stack included Angular 2.0, Java for web services​
  • Development, testing, and config control methodology featured DevOps practices, CI/CD pipeline, 100% automated testing with Cucumber, Selenium​
  • GIT, JIRA, Gherkin, Jenkins, Fisheye/Crucible, SauceLabs, for config control, testing, deployment

Case Study: Web Based Data Application Build

The Client

GOVERNMENT SPONSORED ENTERPRISE (GSE)

The Problem

The Structured Transactions group of a GSE needed to offer a simpler way for broker-dealers to  create new restructured securities (improved ease of use), that provided flexibility to do business at any hour and reduce the dependence on Structured Transactions team members’ availability. 


The Solution

RiskSpan led the development of a customer-facing web-based application for a GSE. Their structured transactions clients use the application to independently create pools of pools and re-combinable REMIC exchanges (RCRs) with existing pooling and pricing requirements.​

RiskSpan delivered the complete end-to-end technical implementation of the new portal.


The Deliverables

  • Development included self-service web portal that provides RCR, pool-of-pool exchange capabilities, reporting features ​
  • Managed data flows from various internal sources to the portal, providing real-time calculations​
  • Latest technology stack included Angular 2.0, Java for web services​
  • Development, testing, and config control methodology featured DevOps practices, CI/CD pipeline, 100% automated testing with Cucumber, Selenium​
  • GIT, JIRA, Gherkin, Jenkins, Fisheye/Crucible, SauceLabs, for config control, testing, deployment

Case Study: RiskSpan Edge Platform Agency MBS Module

The Client

Multiple Agency Traders and the Research & Strategy Division of a Major Investment Bank

The Problem

RiskSpan leverages its extensive expertise to help clients rapidly access the drivers of prepayment risk and prepayment trends. Our analytical platform provides ultimate flexibility and speed to perform quickly turn securities level data into information to based decisions.

The Solution

The RiskSpan Edge Platform is used by the Agency Trading desk to slice and dice data and look for patterns among various bonds using the graphical interface. The RiskSpan Edge Platform offers users access to current and historical data on Ginnie Mae, Fannie Mae, and Freddie Mac (“Agencies”) pass-throughs as well as other data sets.

The tool provides a flexible user interface that supports analysis of prepayment data and actionable reporting. The database includes all monthly pool level data published by the Agencies dating back to 1995.  This data includes pool factors, geographic concentrations and supplemental pool level collateral information. The Prepayment Analytics tool provides a flexible user interface that supports intuitive analysis of the prepayment data and actionable reporting delivered quickly to decision‐makers. The database includes all monthly data published by the Agencies for all months back to 1995, including factors, geographic breakdowns and supplemental disclosure information.

The Deliverables

RiskSpan provides the tools for comprehensive Agency MBS analysis.

  • Visualizing data with integrated graphing and charting
  • Researching new prepayment trends
  • Creating user-defined data tables
  • Exporting customized charts and graphs for marketing purposes

Case Study: Risk-as-a-Service

The Client

Portfolio and Risk Management Software Vendor

The Problem

Our client is a Portfolio and Risk Management software vendor and leading provider of on-demand derivative trading analytics, portfolio and risk management solutions for the global financial industry. Its flagship product provides thousands of users worldwide with advanced real-time portfolio and risk management solutions.  The product delivers risk analysis and transparency to funds of funds, institutional investors, asset managers and others that invest across multiple funds and asset classes. By independently sourcing, verifying, aggregating and normalizing the fund level data that is typically not accessible by investors, then applying common sets of risk exposures and risk scenarios, the product provides the framework for comprehensive risk analysis. 

The Solution

This client did not have the capabilities to provide risk services for residential mortgage securities and structured products and could not independently provide risk services to clients that had RMBS investments. The turnaround time on large portfolios of securities was also critical. 

RiskSpan provided a customized solution to support the recipient’s clients with risk analytics. RiskSpan supports clients through a batch risk service that is run overnight on a cloud computing solution leveraging RiskSpan’s Edge platform.  The RiskSpan service is offered to clients as either daily or monthly to meet client needs. This client uses the risk service in their product, a risk aggregator service.  

The Deliverables

RiskSpan provides the risk analysis for structured products. This risk services solution includes: 

  • OAS simulation processing for agency and non-agency securities​
  • Reporting of OAS, OA-Duration, Convexity, Vega, and eight Key Rate Durations​
  • Additional analytics and scenarios that RiskSpan currently supports and will support in the future as part of the Edge Platform can be provided on request via the batch service

Case Study: Loan-Level Capital Reporting Environment​

The Client

Government Sponsored Enterprise (GSE)

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 in report development.

The Solution

The client engaged RiskSpan Consulting Services to develop a reporting environment backed by an ETL Engine to automate data acquisition from multiple sources. 

The Deliverables

  • Reviewed system architecture, security protocol, user requirements and data dictionaries to determine feasibility and approach.​
  • Developed a user-configurable ETL Engine, developed in Python, to load data from different sources into a PostgreSQL data repository hosted on Linux server. The engine provides real-time status updates and error tracking.​
  • Developed the reporting module of the ETL Engine in Python to automatically generate client-defined Excel reports, reducing report development time from days to minutes​
  • Made raw and aggregated data available for internal users to connect virtually any reporting tool, including Python, R, Tableau and Excel​
  • Developed a user interface, leveraging the API exposed by the ETL Engine, allowing users to create and schedule jobs as well as stand up user-controlled reporting environments​

Case Study: RS Edge – Analytics and Risk

The Client

Large Life Insurance Company – Investment Group

The Problem

The Client was shopping around for an analytics and risk platform to be used by both the trading desk and risk managers.

RiskSpan Edge Platform enabled highly scalable analytics and risk modeling providing visibility and control to address investment analysis, risk surveillance, stress testing and compliance requirements.

The Solution

Initially, the solution was intended for both the trading desk (as pre-trade analysis) as well as risk management (running scenarios on the existing portfolio).  Ultimately, the system was used exclusively by risk management and used heavily by mid-level risk management. 

Cloud Native Risk Service

We have transformed portfolio risk analytics through distributed cloud computing. Our optimized infrastructure powers risk and scenario analytics at speed and cost never before possible in the industry.

Perform advanced portfolio analysis to achieve risk oversight and regulatory compliance with confidence. Access reliable results with cloud-native interactive dashboards that satisfy investors, regulators, and clients.

Two Flexible Options
Fund Subscriber Service + Managed Service

Each deployment option includes on-demand analytics, standard batch and over-night processing or a hybrid model to suit your specific business needs. Our team will work with customers to customize deployment and delivery formats, including investor-specific reporting requirements.

Easy Integration + Delivery
Access Your Risk

Accessing the results of your risk run is easy via several different supported delivery channels. We can accommodate your specific needs – whether you’re a new hedge fund, fund-of-funds, bank or other Enterprise-scale customer.

“We feel the integration of RiskSpan into our toolkit will enhance portfolio management’s trading capabilities as well as increase the efficiency and scalability of the downstream RMBS analysis processes.  We found RiskSpan’s offering to be user-friendly, providing a strong integration of market / vendor data backed by a knowledgeable and responsive support team.”

The Deliverables

  • Enabled running various HPI scenarios and tweaked the credit model knobs to change the default curve, running a portfolio of a couple hundred non-agency RMBS
  • Scaling the processing power up/down via the cloud, and they would iterate through runs, changing conditions until they got the risk numbers they needed
  • Simplified integration into their risk reporting system, external to RiskSpan

Case Study: Securitization Disclosure File Creation Process

The Client

Private Label Mortgage-Backed Security Issuer 

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 inefficient and inconsistent with data from various originators, due diligence vendors and service providers.

RiskSpan consulting services streamlined extraction and aggregation, and reconciling the data used in this process.

The Solution

RiskSpan automated and improved the client’s processes to aggregate loan level data and perform data quality business rules. RiskSpan also designed, built, tested, and delivered an automated process to perform quality control business rules and produce the ASF File, while producing a reconciled file meeting ASF File standards and specifications.

Data Lineage

RiskSpan has experience working with various financial institutions on data lineage and its best practices. RiskSpan has also partnered with industry-leading data lineage solution providers to harness technical solutions for data lineage.

Data Quality

It’s increasingly important to reduce inefficiency in the data process and one of the key criteria to achieve the same is to ensure Data is of highest quality for downstream or any other analytical application usage. Riskspan experience in data quality stems from working with raw loan and transactional data from some of the world’s largest financial institutions.

The Deliverables

  • Created and documented data dictionary, data mapping, business procedures and business flows​
  • Gathered criteria and knowledge, from various client departments, to assess the reasonableness of data used in the securitization process ​
  • Documented client-specific business logic and business rules to reduce resource dependency and increase organizational transparency​
  • Enforced business rules through an automated mechanism, reducing manual effort and data scrub process time​
  • Delivered exception reporting which enabled the client to track, measure and report inaccuracies in data from due diligence firm​
  • Eliminated maintenance and dependency on ad hoc data sources and manual work-arounds​

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