SCI wants to do the heavy lifting in building financial forecasts and methodologies that will enable the financial analysts/institutions, investors and auditors add credibility to the financial models that they use in decision-making by minimizing the potential for human errors and biases. We will do this by offering various solutions starting from the end-result DCF forecast, the intermediate financial assumptions and growth rates up to the core pieces of data. This will enable our customers to focus on building trust and relationship with their clients. And this is something that we can apply globally
SCI combines XBRL, Natural Language Processing (NLP) and other machine learning methodologies to come up with these future cashflows forecasts. XBRL enables us to capture and store financial reports in seconds while NLP and other deep learning methodologies make it possible to get insights from the news and other economic data so we can determine the impact of these indicators to various financial accounts. By doing so, we can create a robust and reliable DCF in a matter of minutes
XBRL will enable us to gather data across regions/countries with XBRL submission portals. We will use the attached XBRL language functionality and language translation technologies (for NLP) so that our engines can comprehend the economic, political, technological, and social aspects of a company. This makes our technology transferable and scalable across regions.
SCI believes in the value of making machine-readable data, such as XBRL, immutable. As such, SCI is also exploring and creating POC’s for the integration of blockchain into our product offerings. We want to add credibility and integrity to the data that we are gathering and sharing with our customers.
SCI is developing a series of AI algorithms, through detailed financial modeling, data processing & storage, and standardization measures that will combine to create an inclusive product we plan to offer as a white label solution for existing financial services providers to be able to offer to their end users to increase their access to high level intelligent output that is usually reserved for the select few on Wall Street.
To perform dependable data analysis and machine learning, Spartan Capital Intelligence (SCI) obtains its data from relieble sources like the US Government Database, US SEC and financial data marketplaces like Intrinio and Zacks. SCI is currently developing its own EU Financial Data Marketplace which will be debuted in 2021.
SCI has a diverse team with talent originating from five continents which is building an equally diverse and robust technological ecosystem with Ai and analytics at its core. We are proud to work with key partners: Intrinio, who provides our data to be ingested, and GOLS Inc, who we rely on for additional development power. Our systems are supported by AWS, and we are in the process of finalization intellectual property patents for our designs.