Background Investment and risk managers need to capture and analyze data across front, middle, and back offices to stay ahead of the competition. However, traditional risk systems are outdated and struggle to meet these demands, resulting in sub-optimal computational performance and lengthy computation times for portfolio investment risk analytics. To overcome these challenges, a solution is needed that can provide timely and accurate data, allowing investment and risk managers to make informed decisions efficiently. Major challenges that investment firms face:

• Operational risks related to launching new products, monitoring allocations, setting up exotic asset classes due to manual processes

• Access to quality data and ensuring an accurate custodian view as well as a detailed IBOR

• Ability to integrate data from disparate feeder in FO/MO/BO areas to establish “one version of truth”

A comprehensive solution is offered to investment firms by Digital Alpha's decision support platform, consolidating data and analytics for improved risk management and better decision-making. With the ability to support new products, computations, and reports, the platform provides flexible and adaptive technology for firms to optimize their portfolios and generate alpha in a fast-evolving risk landscape.

Features

• Understand portfolio exposure to fundamental risk factors such as growth, value, momentum, currency, yield, and spread to track risk.

• Analyze expected tail risk (VAR) using historical simulation, Monte Carlo, and parametric methodologies.

• Stress market variables to assess potential impacts on the portfolio's future performance.

• Utilize scenario analysis to evaluate the impact of market events on the portfolio and make informed decisions.

Benefits

• Investigate risk by decomposing it at a specific date or tracking changes over time.

• Review business-relevant risk measures, such as Volatility, Tracking Error, Value at Risk (VaR), and Expected Tail Loss.

• Compare portfolios to identify outliers and determine where risk is concentrated across funds.

• Utilize third-party or custom risk models that integrate with Digital Alpha's DSP.

• Identify risk hot spots in the portfolio or strategy using Monte Carlo or historical simulation.

Common Use Cases

• Portfolio analytics: Calculation of a defined set of analytics or exposures that might include notional, duration equivalents, delta, counterparty, sector, and country, while sensitivities include DV01, Greeks, Key Rate Durations, YTM, OAS

• Liquidity analytics: Calculation of analytics from market data, security master maintenance with client holdings from third-party systems

• ESG analytics: Provide clients with the breadth, depth, and flexibility to align with their reporting goals by aggregating multiple E, S, and G data sets

Deliverables -

• Design: Work with the client to create a tailored solution that meets their unique needs and can be deployed on AWS using a CI/CD approach.

• Solution Development: Develop and integrate the solution, perform testing and quality assurance to ensure it meets all requirements.

• Analytics: Provide various risk calculations and analytics, such as volatility, tracking error, and VaR, and the ability to integrate with third-party and custom models.

• Cloud Deployment: Deploy the platform on AWS using a cloudformation stack that can be easily updated and redeployed with AWS CodePipeline and CodeDeploy.

• Dashboard: Present data analysis in an easy-to-understand format through a dashboard with various charts and graphs.