In a recent announcement, Accern Corporation, a leading no-code, and artificial intelligence (AI) company announced the acquisition of Morningstar’s global equity research. Morningstar provides independent investment research, maintaining a team of more than 120 equity analysts covering over 1,500 companies. The addition of Morningstar will allow wealth management firms to identify better investments for client portfolios and communicate recommendations that are more tailored.
Kumesh Aroomoogan, Co-Founder and CEO of Accern, stated, “With the rapid rise of unstructured content, Accern is committed to helping our customers more easily extract the insights they’re searching for, using AI models trained specifically for finance. The commitment of financial firms like Morningstar to fundamental research empowers financial professionals to make more-informed investment decisions, evaluate investment ideas, and monitor their performance.”
Companies like Amazon and Oracle use Accern’s platform to analyze millions of structured and unstructured data points in real-time and in real-time. Data points that could have a strong influence on investment decisions are made available to asset managers, insurers, hedge funds, and other financial services professionals through the platform. In addition to adding Morningstar Global Equity Research, the company has expanded its data sources and applications available to customers.
Marc DeMoss, head of research products for Morningstar, said, “Morningstar stands unique in our commitment to providing research that delivers an objective view on investments from the investor’s perspective. We’re looking forward to bringing these independent insights to more wealth managers through Accern’s platform, ultimately empowering success for their end clients.”
Integrating Morningstar Global Equity Research enables financial services teams to:
- Gain better insight into investment decisions with buy and sell signals.
- Analyze global equities for clients and present research clearly.
- Integrate independent research with existing services.
Furthermore, financial data teams will be able to use the research to build AI use cases and analyze unstructured data with natural language processing (NLP), which can increase workflow efficiency and decrease time to insight. By using this service, investors, analysts, wealth, and portfolio managers are able to identify and monitor market risks and opportunities in real-time.
