Making financial insights accessible.
Risk assessment in finance is a tricky thing - for retail as well as institutional investors. While regulatory models do their fair share there is still a huge gap in early warning signals that could make risk assessment better. This is where AI-ML, mathematical modelling and statistics could play a part.
Enter Nullpointer's Financial Data and Insights platform - a combination of predictive Early Warning Signals, Insights and Data APIs that will cater to multiple domains of finance.
Data and Insights Suite.
Since establishing we have worked on multiple projects related to risk assessment in finance . We are now building a comprehensive product that will integrate these as easily consumable Open APIs.
Our deep learning models extract numerical and table information from text-based sources such as annual reports, earnings calls and financial research reports to provide insights such as document summarisation and sentiment analysis at the hit of an API.
Our trading engine uses machine-learning and leverages stochastic sampling, information theory and Kalman filters to generate the best possible trading signals. Deployed using Alpaca's paper trading API on DJIA securities, it has a one-year back-test return of 21%. The live solution's dashboard is available here.
Structural Credit Ratings.
We have applied the Merton Model, with reference to KMV Model used by Moody's Analytics for publicly listed companies. This was project was initially completed for Indian equities as a research assignment for ICRA Ltd. We applied the same model for S&P 1500 securities as well and the results are available here.
Estimated Credit Loss Computation.
Developed the analytics engine for an integrated credit loss calculation tool that will help banks increase the accuracy and efficiency of risk provisioning calculation. The analytics engine, which is served through APIs, does end-to-end tasks from cleaning to statistical modelling on the provided data
Predictive Credit Ratings.
Built a solution that augments the long-term credit rating methodology for corporate borrowers using a machine learning algorithm optimised for the Indian capital market. The solution significantly reduces the data and time required to arrive at a rating decision.
Clients and Testimonials.
"We interacted and worked with two bright explorers, Akshay and Bala, in the Nullpointer team on two intricate assignments. We were highly impressed by their strong technical acumen, their desire and diligence to solve complex problems, and a genuine intent to work in the best interests of customers. To any institution or professional grappling with statistical modelling, artificial intelligence or business-related mathematical problems, we would highly recommend partnering with Nullpointer."
"We worked with the team of Null Pointer (Bala & Akshay) as part of few analytical projects they did for our organization. The work done by them was professionally handled and the quality of output was also better than our expectations. The team at Null Pointer was prompt in resolving any issues that were brought to their notice.
Overall we were more than satisfied with the team and their quality of work and would recommend them to others too."
- JITIN MAKKAR, Vice President and Head - Credit Policy, ICRA Limited
- VIKAS TARACHANDANI, DGM and Head - Financial Services, ICRA Analytics Limited