What Makes Us Different?
1) We democratise access to professional investment insights
Nowadays, large corporations and major financial firms like the investment banks, fund houses,
global media outlets and information providers have been using and developing large language
models (LLMs) to assist in the investment processes. On the other hand, the resources and
knowledge for independent investors remain relatively limited.
FinCatch aims to democratise access to investment analysis insights by making them affordable and accessible to independent investors. By leveraging generative AI, predictive machine learning models, and our proprietary semantic network, we are able to provide a platform that empowers individual investors with the same level of insights historically available only to large institutions.
Our basic features include:
- Research and Information Gathering: Our framework tirelessly retrieves historical data, financial events, and pertinent information about publicly traded companies. Dive into timelines, analyze news, and understand market sentiment effortlessly.
- Language Processing and Text Generation: Experience the power of natural language processing and advanced text generation capabilities with LLMs. Perfect for searching materials, summarizing content, and analyzing textual data, these tools elevate your data comprehension and decision-making processes.
- Efficiency and Productivity: Our tools empower finance participants to redirect their focus toward higher-value activities by automating repetitive tasks and delivering essential information. Maximize your impact while our technology streamlines the essentials.
2) We focus on event implications and possible outcomes
Our approach combines advanced AI techniques with a systematic fundamental framework. We utilise generative AI and machine learning models to generate investment implications based on extensive data analysis. By employing techniques like chain-of-thoughts and RAG (Retrieval Augmented Generation), we enhance the reasoning power of our AI system and minimise the occurrence of false or misleading information.
A significant challenge in investment analysis is dealing with unstructured data, including news articles, social media posts, and company reports. FinCatch addresses this challenge by leveraging the power of embedding techniques and vector databases. This enables us to extract readable signals from unstructured data, transforming them into valuable insights that investors can easily comprehend and act upon.
To provide a comprehensive understanding of the investment landscape, FinCatch develops a knowledge graph. This graph helps identify the root causes of events and uncovers the broader implications behind them. By connecting various data points and analysing relationships among them, we provide investors with a deeper understanding of the factors influencing the market and specific investment opportunities.
Our unique approach includes:
- Systematic Fundamental Framework: Integrating a systematic fundamental framework with our cutting-edge vector database, FinCatch leverages AI-generated investment implications.
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Enhanced Reasoning Power: We employ techniques including chain-of-thoughts and
RAG to enhance reasoning power and minimise hallucinations. -
Machine Learning and Unstructured Data: Combining the power of language model
with predictive machine learning models, we extract readable signals from unstructured
data. -
Building a Knowledge Graph: We develop a knowledge graph that searches for root
causes and uncovers the broader implications behind every single event happening every
day.