Risk Data Analysis Project

Key Challenges

A Pension Plan, with assets under management exceeding $160 billion, wanted to identify gaps in Terms and Conditions that were being captured for Risk Management Reporting. There was loss of confidence in the data and calculations being reported for overall firm-wide exposure to credit, interest rate and other risks that impacted Risk Management decisions. The security universe in scope was complex in nature and included many OTC and non-OTC derivatives.

InvestTech Solution

The project objective was to identify the risk data capture requirements for all derivative and cash securities necessary to support the following downstream Risk Management functions:

The key deliverable was to develop recommendations to resolve existing risk data gaps and improve firm-wide risk data quality reporting.

InvestTech deploys a Structured Data Analysis Methodology to define and document all data and metadata requirements. The InvestTech team interviewed all key business users to identify requirements in the risk management data process. The client utilized multiple products including DSTi Askari, OpenLink Findur, SimCorp Dimension and other internally developed cash and derivative systems. Integration with industry standard utilities included data requirements to support International Swaps and Derivatives Association- ISDA, FpML, DTCC DerivServ, Markit Partners and T-Zero.

The final deliverable included full data documentation and workflow processing from source to destination systems including data gaps, data validation, quality control and final recommendations on the steps to resolve data gaps to improve the risk data management process. InvestTech’s involvement and responsibilities covered all aspects of the project including Project Management, Business Analysis, and Data Architecture.

Results

The project tasks and deliverables covered multiple key areas:

1. Risk data quality accuracy and completeness gaps were identified across 150+ individual security types. A metadata matrix and heat-map was created to map the overall data model, show the severity of the data issues and to identify significant gaps in the risk data for all Fixed-Income and OTC Derivatives.

2. Gaps in data required for exposure monitoring, terms and conditions, counterparty and issuer/entity exposures were identified including security underlyers and basket requirements. Recommendations were provided to resolve these data gaps.

3. Data synchronization recommendations were provided to resolve data flows across multiple investment applications (trading, accounting, risk, etc…) to eliminate redundant manual data updates and data quality gaps.

4. Systems limitations to support outlying security types were identified, including gaps in theoretical pricing and valuation of complex derivative types.

5. Documentation of the data model needed to support the complete risk management process focused on the stated project objectives (e.g.: Risk Modeling, Valuation…etc.)

Why InvestTech?

InvestTech’s breadth of industry knowledge in risk data management and derivatives processing was brought to bear on this project. The first phase of the project relied on InvestTech’s extensive experience in analyzing the workflows and investment business processes while providing input on the industry best practices. Our ability to communicate effectively between front and back office, IT personnel as well as senior management helped to forge a consensus on how to proceed.

InvestTech’s knowledge of Risk management, OMS and investment accounting systems also provided valuable input into the optimized data capture and enrichment process. Our teams have successfully implemented and evaluated many of the leading OMS, investment accounting and risk reporting systems which helped ensure the optimal use of each systems throughout the front-to-back office risk data workflow, plus an on-time, on-budget project.