It is now well recognized that traditional active and hedge funds are increasingly valuing the combination of discretionary investment approach with data-based analytics.
Surveys have shown close to, or more than half of, funds/ managers are using data analytics to gauge portfolio risk, investment opportunities, model performance, manager performance, performance analysis, and so on. At the same time, data analytics inputs remain a supporting tool in an industry driven by accomplished managers’ experience and networks.
At our recent event in New York on Data Science and Analytics, specifically focused on challenges and applications in Finance, Shailesh Dhuri, Chief Executive officer DPA, and Gaurav Gupta, Managing Director, DPA spoke about the key trends in data science and their impact.
- Technology and improved connectivity have resulted in a manifold increase in sources of alternate data
- Advanced analytics and data science are the keys to examine and understand alternative data sets
- Finance companies are increasingly turning towards technology, especially AI and ML, to leverage this data
- In the future, quantum computing can potentially transform financial services.
With increasing competition, the new-age data science team requires collaboration with technology, people processes, and the right analytics partner. At Decimal Point Analytics, we serve data science teams through a confluence of various capabilities such as data ingestion, machine learning and algorithms, data infrastructure, and visualization/ business intelligence.
The speakers shared some interesting use cases, such as the extraction and ingestion of large volumes of unstructured data for an SEC-registered institutional asset manager and an ML model to analyse offerings from multiple US banks. The speakers also deep-dived into a use case where Decimal Point Analytics created an automated model for processing over 66,000 rent roll receipts, which helped reduce the scanning time for a rent roll by 75%.
The participants also had an opportunity to understand the working of SmartPipe, a 100% automated, machine learning-driven cloud-based platform developed by Decimal Point Analytics. SmartPipe serves as a one-stop shop for data ingestion, data cleaning, and data deduping. The no-code nature of SmartPipe, which enables its self-service usage without the need for technical know-how for implementation, proved to be a real discussion point among the participants.