Risk Framework
We have a deep experience in designing and subsequently building out all policies, procedures and process flows required for banking businesses as well as buy and investment houses. This includes all aspects from risk methodology, production and monitoring of risk control reporting through to new product procedure and pricing model validation. We have developed and implemented the organization and governance requirements coupled with the policy requirements necessary for both sell side and buy side businesses.
A tier one, blue chip US buy-side house required a full overhaul of the risk management & control policies and procedures to support its multi-billion USD Fund-of-fund business. This effort was to include the governance framework. The requirements were driven internally by a shift in internal control requirements and, externally, by the need to comply with regulation including UCITS.
- A turn-key solution was proposed and included all aspects of risk control including scoping, development and production of:
- A bespoke VaR and scenario risk engine
- Risk reporting protocols and report content
- Risk information hierarchies – dependent on business line and control function
- Risk Committee and associated terms of reference and MI requirements
- New Product Committee and associated processes
All aspects of the proposal were delivered for implementation and handover to ‘business - as - usual’ including assistance in successful recruitment of a new Head of Risk Management & Control.
Market Risk
A client from the reinsurance sector required a review of the market risk calculation approaches employed across its multi-asset management business. This business comprises of all asset types – equity, fixed income, commodities and real estate. The business is also exposed to the full range of product types across cash and derivatives – with the latter having long dated term structures.
The review highlighted an inconsistency across the risk measurement approached and inherent weaknesses in collating and aggregating high level risk numbers.
The Risk Committee moved to adopt recommendations we made across changes to risk measurement methods which included the need to have a single, consistent approach to calculating VaR, the application of appropriate (macro) scenarios and portfolio stress testing. These changes were implemented as part of a wider risk system overhaul.
Business Intelligence & Control
The client was a large, European bank which had a broad requirement to overhaul the risk and P/L reporting framework bank wide. The requirements for risk and P/L information clearly differed from trading desk to trading desk and management to board level.
Different screen based default dash boards were developed as was the ability to develop a customized suite of MI reports – governed only by the screen real estate.
The principal challenge was data sourcing and management. In general, risk methodologies were consistent but risk consolidation techniques required extensive review and change.
Product & Systems
A previous project saw the firm working alongside client senior management to develop a firm wide risk management solution across calculation and reporting of traded risk. The challenge was increased with the requirement to absorb back into ‘Group’ of a Financial Products subsidiary which had traded multi-currency, multi-asset long dated products.
We led the risk architecture efforts capturing and developing all functional requirements, translating functional to technical specification and leading the programme and data management offices.
Portfolio & Transaction Analytics
CPMoksha analysts were brought in to review a portfolio of vintage long dated trades comprising equity and credit derivative structures (or legs of structured trades) which we subsequently assessed with a view to developing the best case portfolio management solution going forward.
The analysis led to an understanding of where P/L was attributable – original risk premium, delta and second order effect. Scenario analysis allowed hedging profiles to be developed – including an understanding of how the risk parameters may change over time. Ultimately, the decision was taken by management to sell the portfolio into the secondary market.
Big Data Analytics for a Hedge fund
A market leading hedge fund was struggling to monitor real time investment activities. Missing comprehensive information while making investment decisions could cost the company dearly hence analysts had to manually troll through multiple websites.
Our Big data Analytics experts automated the manual process by crawling various information sources - company, regulatory websites and storing the data in an unstructured format while allowing it to be configured to any desired frequency. The data was curate and stored in searchable databases which was accessible through a web interface. This automation allowed researchers to efficiently use time and concentrate their efforts more on investment analysis.
The solution also provided the Hedge Fund with single interface with comparative information from various data sources - Bloomberg, BondHub, Markit. We customized the system to send email alerts as often as desired by the analysts. The benefits to the firm was immense in terms of an easy to use web based interface linked to an aggregated data source saving the analysts considerable time and effort and increased confidence in making informed decisions.
Cloud Deployment & Computing
A fast-growing Technology firm that sells Social Ad Campaign management software wanted its in-house Engineering team to focus on its core product and outsource its non-core technology needs. The non-core portion technology stack required cutting edge computing skills and entailed creating a Big Data Analytics infrastructure.
CPMoksha team designed and implemented a scalable Crawler to aggregate social data to meet challenging latency requirements while reducing cost of designing and maintaining Hadoop based infrastructure. We designed a robust analytics and predictive modeling backend to meet evolving business initiatives and continued to enhance and upgrade the system to the latest stable version of the Hadoop distribution to leverage ongoing upgrades.
The solution provided numerous benefits to the client in terms of scope and quality of deliverables by leveraging our expertise in Big Data infrastructure and Social content aggregation. Economically increased Data mining and Predictive modeling capabilities resulted in newer revenue streams while massive savings were achieved through reduction in resources in terms of staff and overhead costs.