Insig Portfolio 2.0 significantly enhances the data science tool kit available to asset managers.

Insig AI, the technology company that provides machine learning solutions for asset managers, is pleased to announce the second major release of its flagship software, Insig Portfolio.

Insig Portfolio is a user-friendly web application which provides portfolio managers of all sizes and strategies with additional data driven insights to aid their investment decisions. Insig Portfolio was developed to alleviate the frustration of asset managers currently working with error-prone spreadsheets, and to remove the time-consuming effort of building data science applications in-house.

To address these issues, Insig Portfolio has a framework-based architecture that is easily tailored to a portfolio manager’s investment thesis and preferred sources of data. At the same time, Insig Portfolio’s analytics are underpinned by a robust data management process, freeing analysts and portfolio managers from the need to do time consuming manual data updates.

Furthermore, Insig Portfolio includes functionality to explore financial data, ESG metrics, identify important financial features, construct portfolios with machine learning or screening tools, measure and optimise risk exposures, and attribute portfolio performance to regions, sectors and other idiosyncratic characteristics.

Exponential growth in computing processing power has widened the information gap between asset managers with traditional, inefficient data systems and those with easily accessible, efficient data management systems. Insig Portfolio leverages its cloud infrastructure to reduce the constraint of limited computing power with access to multiple cloud-based machines.

Jaco Venter, Head of Asset Management and Data Science, Insig AI, commented: “This second release of Insig Portfolio is a major push forward in both capability and usability, allowing investment analysts and portfolio managers to easily slice and dice financial data to enhance investment decision-making based on data exploration, visualisation and machine learning from targeted stock universes.”

Steve Cracknell, Chief Executive, Insig AI, added:

“In addition to financial metrics, we have also developed Insig Portfolio to leverage our ESG machine learning classifiers. This helps meet increasing client demand for more integrated ESG metrics to enable deeper analysis. The sophistication of our data platform makes the integration of multiple data sets easily accessible to our clients.

“We already have 4 potential clients currently trialling Insig Portfolio who have each agreed to upgrade to this new v2.0 and we are optimistic that further potential clients will wish to have meetings with us to understand the capabilities of Insig Portfolio 2.0 and benefits to their business.”

In the video below, CEO Steve Cracknell outlines the nature of the group’s business and its ongoing growth strategy