RiskSpan Adds Whole Loan Analytics to Edge Platform ARLINGTON, VA, May 20, 2019 – Leading mortgage data and analytics provider RiskSpan announced the release of its Whole Loan Analytics Module on the RiskSpan Edge Platform. The module enables whole loan investors, portfolio managers, and risk managers to manage loan-level data flows and predictive models that forecast loan performance under a range of scenarios. The off-the-shelf SaaS version supports whole loan pricing and surveillance. It enables complex forecasting analytics including geographically granular House Price scenarios and historically significant economic event scenarios. Other features and custom configurations are also...
Attribution analysis of portfolios typically aims to discover the impact that a portfolio manager’s investment choices and strategies had on overall profitability. They can help determine whether success was the result of an educated choice or simply good luck. Usually a benchmark is chosen and the portfolio’s performance is assessed relative to it.
This post, however, considers the question of whether a non-referential assessment is possible. That is, can we deconstruct and assess a portfolio’s performance without employing a benchmark? Such an analysis would require access to historical return as well as the portfolio’s weights and perhaps the volatility of interest rates, if some of the components exhibit a dependence on them. This list of required variables is by no means exhaustive.
There is movement in the vendor market for Risk Analytics. Barclays is divesting its POINT risk analytics system and Capital IQ has exited the risk business. These changes have prompted the market to consider vendor alternatives and the timing for a fresh look at solutions couldn’t be better.
The regulatory environment persists. There is a constant stream of demand from investors and regulators for independent risk analysis and reporting. Further, the emergence of new data management tools and the declining cost of cloud-managed hardware presents the market with an opportunity to scale data processing and reduce costs.