Ermas Consulting Inc. : Exceeding Expectations

Our Approach to Integration Consulting

Ermas Model Manager

  1. Overview
  2. Benefits
  3. Features
  4. Screenshots
  5. System Requirements


Ermas Model Manager helps the user to easily build a holistic risk model from a series of individual models, and to manage model versions for different model types. Ermas Model manager enables the user to continuously improve risk management by expediting the deployment of new, more accurate risk models.

Ermas Model Manager features project breakup allowing breaking project run into multiple parts to enable the user for example to validate any intermediate model output, to adjust any intermediate model output, and to distribute processing across multiple CPU cores for fastest processing and maximum scalability.

Ermas Model Manager features Intelligent Processing being an automatic check prior to project execution to validate completeness of model input parameters for each individual model to be executed.

Ermas Model Manager uses the following concepts:

Master Model
  • Master Model is a holistic risk model that combines of a series of individual models
  • For example different Master models can be built to analyze Fixed Rate Mortgages, Adjustable Rate Mortgages or Credit Card portfolios
  • Master models can, for example, refer to portfolio level models to monitor performance of certain portfolio segments such as mortgages, credit cards or consumer loans. A Master model can also relate to a complete Economic Capital model for the total portfolio.
Model Ordinator
  • For each individual model within the master model the user can choose a Model Ordinator
  • The Model Ordinator determines the logical order/sequence in which the individual models are processed within the Master Model
  • For each Master Model the user can define a specific Model Order
Model Version
  • For each individual model the user can choose the Model Version
  • For example, the Model Version determines whether to use:
    • Lab Version
    • Garage Version
    • Current Approved/Factory
    • Next Generation
    • Previous Period
Financial Product
  • The Product-ID identifies the Financial Product associated to the model


Cost efficient
  • Ermas Software deployment is based on basic SAS Modules referring to SAS BASE, STAT, ETS, IML, Graph, Integration Technology and SAS Share. This is a very cost effective way of deploying Risk Analytics.
  • Ermas Software also supports R language, C and C++ code. This enables the user for example to build Risk Analytics based on R open source language, in order to reduce commercial Software Fees.
Integrated with SAS
  • Proprietary SAS Model code can be fully applied within Ermas software.
  • Ermas Software is fully integrated with the SAS language and enables the user to develop proprietary SAS models and to expedite the deployment of new production SAS models.
  • Ermas Software can leverage a multi-core computing infrastructure and can be grid-enabled for fastest processing and scalability.
  • For example, Ermas Software can use SAS Connect (MP/Connect) to distribute processing load across multiple CPU cores fastest processing and maximum scalability.
  • No limitation in data volume processed.
  • Open integration with proprietary or third party models allows to apply 'best-in-class' models for each financial product type ensuring unlimited financial product coverage and leveraging full pricing.
  • Each individual model (such as cash flow model, pricing model, PD-, LGD- and prepayment model, term structure model, credit-Value-at-Risk model, Economic Capital model, or other model) can be chosen by the user allowing leveraging proprietary knowledge and propriety models to perform most accurate risk management.
  • The Ermas Risk Framework allows banks to develop, validate, deploy, and track risk models faster, cheaper, and more flexibly than outsourced alternatives or desktop solutions.
  • Ermas Risk Framework provides a risk management framework that is consistent with best practice of risk modeling in the financial services industry.
  • Consistent, accurate and reliable data is required in order to achieve best practice in risk management. Based on Ermas Risk Framework you can efficiently manage vast quantities of data from across the enterprise - this includes data from loan capture systems, trading systems, and risk factor agencies, loan performance data, among other data.
  • Ermas Risk Framework ensures to apply risk models and model parameters consistently across all portfolio and exposure types.


Model Management Build Holistic Risk Models, manage Models, manage Model Versions
Project Breakup Breaking Project run into multiple parts, allowing to:
  • validate intermediate model output
  • adjust intermediate model output,
  • and to distribute processing across multiple CPU cores
Portfolio Management The user can apply simple or advanced portfolio filters in order to define specific (sub-) portfolios. The creation of user defined sub-portfolios helps to quickly and effectively pre-sort the portfolio into tranches that may affect future performance. The user can apply holistic master models including Economic Capital Models, Stress- and Scenario models to user defined (sub-) portfolios, and run risk reports for the user defined (sub-) portfolios.
Stress Testing and Scenario Analysis With Ermas Model Manager the user can easily manage Stress Testing Models and Scenario Models
Economic Capital With Ermas Model Manager you can build and manage Holistic Economic Capital Models from individual models; Economic Capital models can include Monte-Carlo Simulations, Historical Simulations, Parametric Models or Proprietary Models.


System Requirements

SAS Software Requirements - SAS 9.1.3 or 9.2
  • SAS 9.1.3 or 9.2
  • SAS Connect
  • SAS Integration Technology
  • SAS Share
Java Requirements
  • Java 1.6
Web Portal Requirements
  • LifeRay 6.0