Press Release
FinSoftAi Debuts Trailblazing AI-Powered Equity Research Product Click here to view.
brand_awareness
FinSoftAi Invites Industry Professionals to Webinar Exploring Impact of Social Sentiment on Modern Investing Strategies Click here to view.
brand_awareness
FinSoftAi Unveils Disruptive AI Technology, Transforming Institutional Investing in 2024 Click here to view.
brand_awareness
SSi leverages FinSoftAi’s unique patent-pending technology.
Video Gallery
SSi Overview 1:38
SSi Use Cases 4:02
FAANG Sentiment Dashboard 1:34
Social Sentiment Insights (SSi)
Making timely and better business decisions using social sentiment
Problem: Rise of social trading and investing requires alternate data to make timely and better business decisions to maximize gains while managing social risk. Financial Institutions now need to monitor social buzz and social sentiment to avoid yet another meme stock (GME) saga!
Solution: Leverages Big data and ML to provide accurate Sentiment from multiple social media & news sources to help Investors & Traders maximize gains while managing social risk. Back-testing results show outsized (up to 40X) gains over Index!
Use Cases
Investment Research
- Create winning portfolios by picking stocks that have a strong correlation with sentiment
- Portfolio re-balancing using sentiment and sentiment based technical analysis
Impact Investing using ESG Sentiment score
- Limited disclosures and lack of standards for ESG Reporting
- ESG scores fails to capture public sentiment
- ESG input is qualitative and voluminous. Need for an automated big data, NLP ML solution
Managing Social Risk
- Social media goes viral, is volatile and impacts stock performance. Portfolio managers need to manage exposure to stocks that have a high volume of social buzz and high volatility w.r.t sentiment.
Trading
- Sentiment is a leading indicator while price is lagging Combining sentiment based technical analysis with price based technicals results in increased gains.
Features
FAANG Sentiment Dashboard – Features
- The AI-powered FAANG Sentiment dashboard offers key insights for investors and traders for Facebook/Meta, Amazon, Apple, Netflix, and Google/Alphabet stocks. With features like sentiment analysis, social buzz trends, customizable alerts, and trending Word Clouds, it empowers users with timely and valuable information before market opening to enhance Return on Investment.
SSi Research – Features
- Social media is all-pervasive, more so with Gen Z and millennials. With the democratization of investing & trading, institutions need to constantly monitor retail sentiment mirrored in social media and news. Machine Learning using GenAI & Transformers has revolutionized Natural Language Understanding. Accurate social sentiment is now a reality and superimposing this powerful alternate data on various charts enables investors & traders to maximize gains while managing risk.
Sentiment Analysis
A unique and multi-asset sentiment analysis framework that will:
- Plug and play across different information sources (news, social media, private data sources, google trends etc.). Research Analysts can refine this universe of information by creating a structured Natural Language Processing (NLP) NLP Query
- Sentiment indicators and alert signals across multiple financial asset classes
- Render Trading signals through multiple channels including an API interface to enable further processing by our customers using quantitative models.
- A Private blockchain architecture ensures collaboration within the trading desk, transparent calculation of commissions, and compliance with the firms trading objectives
Executive Summary
Making timely and better business decisions using social sentiment
Solution | A Platform that Collects, Aggregates, Analyzes, Organizes, & Visualizes data from multiple social media & news sources to create actionable insights |
Use Cases | Investment Research, Trading, Social Risk , ESG (Impact Investing) |
Customer Segments | Asset Managers, Hedge Funds, Investment Banks, Broker Dealers, Boutique Research, Financial Media, FinTechs’s |
User Profile | Research Analysts, Traders, Market Risk Analysts, Investment Managers/Advisors, Portfolio Managers, ESG Analysts |
Revenue Model | B2B and B2B2C, (SaaS using public/private cloud), AMC and Professional Services (specific to SSi), White Labeling |
Growth Strategy | Rapid growth powered by Win-Win Partnerships and Consortiums. |
Key Differentiators | ML Models outperform Industry benchmarks by 60%, Easy to support new data sources & ML models, Superimposing sentiment on Trading charts, Highly configurable architecture that supports multiple use cases, correlation analysis, API’s. |