Complicated Data? Smonik Goes Far Beyond Typical Data Extraction
The ability to extract data from structured and unstructured documents, specifically as it relates to alternative investment data, has become a hot topic in the institutional investor and data aggregation community. Technology for data processing has improved, and a few firms are out there selling software and/or services to accomplish the task of turning unstructured data, usually delivered in a PDF document format, into usable data available to be integrated with downstream systems. Although they are adept at extracting data from simpler document formats, such as capital statements, capital calls and distribution notices, what about more complex documents? Could they extract the financial highlights sections from a 300-page financial statement, or Schedule of Investments data so that it lines up properly in a spreadsheet output format? This is where you need a data extraction methodology with far more complex functionality.
Private capital investors rely on accurate information and must be able to produce it efficiently. Endowments, foundations, pension plans, and family offices digest large volumes of complicated material. Manually extracting relevant data costs a significant amount of time and runs the risk of human error, especially when the files are difficult to interpret. Investors must employ an intelligent, automated system able to process a wide range of complex documents or they may inadvertently exclude valuable data.