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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

CONTACT US

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: 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​

Asset Manager: Cost-Efficient and Flexible Solution

An asset management company needed to replace an inflexible risk system provided by a Wall Street dealer.  The client’s portfolio was diverse, with a sizable concentration in structured securities and mortgage assets. The legacy analytics system was rigid with no flexibility to vary scenarios or critical investor and regulatory reporting.

Every portfolio manager requires reliable and accurate analytics to manage risk and improve investment decisions. They require understanding of investment positions and the impacts on risk metrics measures such as value at risk (VaR). The faster they can assess a portfolio’s total exposure and understand the key drivers, the better they can react and align activities with the overall firm risk appetite.

“The challenge was that our existing daily process for calculating, validating and reporting market and credit risk metrics required significant manual work. If we could get to the answers faster, we would be in a much better position to identify exposures and address potential problems.”                             

The Solution

As a fully-managed solution, RiskSpan’s Edge Platform provides the asset manager with a cost-efficient and flexible solution. The service bundles required data feeds, infrastructure management, and predictive models for mortgages and structured products. Edge manages and validates third-party data as well as client portfolio data, and produces scenario analytics in a secure hosted environment. With the combination of models, data management, and an end-to-end managed process, Edge provides the asset manager with unmatched value.

The Benefits

  • Portfolio risk measures on-demand
  • Structured product expertise
  • Outsourced data management
  • Predictive models for mortgages
  • Outsourced hardware management
  • Customized dashboards and reports

The asset manager used the Edge Platform to cut hours from daily risk-reporting processes and free several analysts to focus on their primary task: optimizing analytics and processes that support better investment decisions.

Deliverables

Analytics Software

The Edge Platform provides for the calculation of key market risk metrics for over 70 different instrument types. The service provides for a combination of on-demand or overnight batch processing. Users have online access to platform to run ad-hoc analyses, including additional scenarios or what-if analyses. The hosted platform makes the processing speed lightning fast.

Data Management Outsourced

The Edge market-risk analytics platform integrates data from six major data vendors.  Our data management services support integrated data for interest-rates, implied volatility, and terms & conditions for over 70 different instrument types. The platform includes loan-level data for Agency and non-Agency mortgage-backed products. The platform integrates seamlessly with Intex subroutines to support all structured products.  Further, Edge clients have access to a team of experts in mortgage and structured product – not just technical support.

Technology and Infrastructure Management

As a hosted solution, the asset manager is able to leave management of hardware to the Edge technology team. We secure and manage all required hardware, freeing up millions of dollars in hardware acquisition costs and labor costs required to manage the infrastructure.

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