The OutRank API enables you to provide your customers with a holistic view of their financial situation by delivering actionable insights in an engaging and scalable way. Our technology delivers superior digital analytic that put consumers in control of their investments, loans and pension savings considered together. All this while improving the cost-efficiency of delivering financial guidance or advice by projecting wealth over time and empowering financial decision-making.
Whether you are looking to build generic guidance tools to support better point-of-sale decision-making or to develop a state-of-the-art robo-advice framework, OutRank has what it takes to turbo-charge your project! Moreover, it can equip your team of wealth managers with analytics to support optimal decision-making, creating an excellent choice for hybrid wealth strategies.
The OutRank API provides:
In this article series, we present a machine learning-based approach to solving a common problem in financial modelling where one is faced with the task of estimating the value of a function which requires a significant amount of computation to evaluate. More specifically, a function that corresponds to a so-called nested simulation aimed at, for example, estimating a capital requirement for a financial institution or the risk associated with a structured product for a retail investor.
In the third and the final part of our “Portfolio Construction” article series, the findings of the previous sections are applied to a broader and more realistic set of assets to evaluate the performance of the proposed methods against more conventional techniques.
The second part of the “Portfolio Construction”-series explores whether introducing parameter uncertainty to the model would improve the out-of-sample performance of the optimal portfolio. Additionally, the article proposes and tests two adjustments to regular utility optimisation.
There is a number of challenges associated with portfolio construction based on historical data. This three-part article series explores some of the most common issues attributed to the model-based portfolio optimization: the sensitivity to changes in data, large variations in portfolio weights and the bad out-of-sample performance.
Kidbrooke’s Economic Scenario Generator is an API that enables a spectrum of firms to model possible future states of the global economy and capital markets to drive a wide range of portfolio and risk management decisions.Learn more
Kidbrooke’s Balance Sheet Simulator is a critical element of OutRank API responsible for constructing future cash flow trajectories on the balance sheet level.Learn more
Kidbrooke’s financial decision support toolkit is a collection of APIs that support investment goal creation, risk profiling and investment product ranking.Learn more