A commercial bank required an independent validation of its CECL models. The models are embedded into three platforms (Trepp, Impairment Studio and Evolv) and included the following:

The Solution

Because the CECL models are embedded into three platforms, RiskSpan conducted an independent, comprehensive validation of all three platforms.

Our validation included components typical of a full-scope model validation, focusing on a conceptual soundness review, process verification and outcomes analysis.

Deliverables 

RiskSpan was given access to the models’ platforms, and workpapers, along with the models’ development documentation, and weekly Q&A sessions with the model owners.

Our review evaluated:

i. the business requirements and purpose of the model, and the metrics that used by the developer to select the best model and evaluate its success in meeting these requirements will be judged.

ii. the identification and justification for

  (a) any theoretical basis for the model structure;

  (b) the use of specific developmental data;

  (c) the use of any statistical or econometric technique to estimate the model; and

  (d) the criteria used to identify and select the best model among alternatives.

iii. the reasonableness of model-development decisions, documented assumptions, data adjustments, and model-performance criteria as measured at the time of development.

iv. Process verification to determine the accuracy of data transcription, adjustment, transformation and model code.

RiskSpan produced a written validation report detailing its validation assessments, tests, and findings, and providing a summary assessment of the suitability of the models for their intended uses as an input to the bank’s CECL process, based upon the Conceptual Soundness Review and Process Verification.

A large regional bank required a qualified, independent third party to perform risk-based procedures designed to provide reasonable assurance that its FCRM anti-money laundering system’s transaction monitoring, customer risk rating, and watch list filtering applications were functioning as designed and intended.

The Solution

RiskSpan reviewed existing materials, past audits and results, testing protocols and all documentation related to the bank’s model risk management standards, model setup and execution. We inventoried all model data sources, scoring processes and outputs related to the AML system.

The solution consisted of testing each of the five model segments: Design and Development; Input Processing; Implementation; Output and Use; and Performance.

The solution also quantified risk and exposure of identified gaps and limitations and presented sound industry practices and resolutions. 

Deliverables

An inflexible, locally installed risk management system with dated technology required a large IT staff to support it and was incurring high internal maintenance costs.

Absent a single solution, the use of multiple vendors for pricing and risk analytics, prepay/credit models and data storage created inefficiencies in workflow and an administrative burden to maintain.

Inconsistent data and QC across the various sources was also creating a number of data integrity issues.

The Solution

An end-to-end data and risk management solution. The REIT implemented RiskSpan’s Edge Platform, which provides value, cost and operational efficiencies.

Deliverables 

Consolidating from five vendors down to a single platform enabled the REIT to streamline workflows and automate processes, resulting in a 32% annual cost savings and 46% fewer resources required for maintenance.

A $100+ billion government-sponsored enterprise with more than $3 trillion in assets sought to develop an end-to-end earnings forecast framework to project and stress-test the future performance of its loan portfolio. The comprehensive framework needed to draw data from a combination of unintegrated systems to compute earnings, capital management requirements and other ad hoc reporting under a variety of internal and regulatory (i.e., DFAST) stress scenarios. 

Computing the required metrics required cross-functional team coordination, proper data governance, and a reliable audit trail, all of which were posing a challenge.  

The Solution

RiskSpan addressed these needs via three interdependent workstreams: 

Data Preparation

RiskSpan consolidated multiple data sources required by the earnings forecast framework. These included: 

Model Simulation

Because the portfolio in question consisted principally of mortgage assets, RiskSpan incorporated more than 20 models into the framework, including (among others): 

Business Calculations and Reporting

Using the data and models above, RiskSpan incorporated the following outputs into the earnings forecast framework: 

Client Benefits

The earnings forecast framework RiskSpan developed represented a significant improvement over the client’s previous system of disconnected data, unintegrated models, and error-prone workarounds. Benefits of the new system included:  

An asset manager sought to replace an inflexible risk system provided by a Wall Street dealer. ​The 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.​

The Solution

RiskSpan’s Edge Platform delivered a cost-efficient and flexible solution by bundling required data feeds, predictive models for mortgage and structured products, and infrastructure management. ​

The Platform manages and validates the asset manager’s third-party and portfolio data and produces scenario analytics in a secure hosted environment. ​

Models + Data management = End-to-end Managed Process​

The Edge We Provided​

”Our existing daily process for calculating, validating, and reporting on key market and credit risk metrics required significant manual work… [Edge] gets us to the answers faster, putting us in a better position to identify exposures and address potential problems.” ​

                        — Managing Director, Securitized Products  

The Problem

A government-sponsored enterprise needed a centralized data solution for its forecasting process, which involved cross-functional teams from different business lines.​

The firm also sought a cloud-based data warehouse to host forecasting outputs for reporting purposes with faster querying and processing speeds.​

The firm also needed assistance migrating data from legacy data sources to new datamarts. The input and output files and datasets had different sources and were often in different formats. Analysis and transformation were required prior to designing, developing and loading tables.  

The Solution

RiskSpan built and now maintains a new centralized datamart (in both Oracle and Amazon Web Services) for the client’s revenue and loss forecasting processes. This includes data modeling, historical data upload, and the monthly recurring data process.

The Deliverables

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

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

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

CONTACT US

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.