aishwaryapaininde / equityedge

EquityEdge : FinTech - Financial Technolofy for all (NetApp)

OVERVIEW:

The Financial Technology challenge aims to advice individuals' financial handlings through user-friendly platforms offering interactive learning modules, gamification elements, and personalized recommendations. By integrating real-world examples and ensuring data security, the goal is to empower users of all ages and backgrounds to make informed financial decisions.

PROBLEM STATEMENT:

Technical Problem Statement: Financial technology, or FinTech, represents the vanguard of technological innovation in the financial services industry. It fundamentally disrupts established models by introducing streamlined and efficient solutions across the entire financial spectrum. This encompasses mobile banking and digital payments, as well as automated wealth management platforms and applications leveraging blockchain technology. In essence, FinTech is revolutionizing the way financial services are delivered, accessed, and managed.

PROPOSED SOLUTION:

This solution introduces an AI-driven financial technology platform, utilizing Machine Learning models to offer personalized recommendations and feedback. It adopts a modular, microlearning-based approach integrated with real-world case studies and gamification elements to enhance knowledge retention, aiding individuals in effectively navigating personal finance complexities.

Personalization: Behavioral Analysis and HR System (HRS): Utilizing ML models, the platform employs collaborative and content-based filtering to deliver tailored recommendations and feedback based on user behavior and profile assessment.

Literacy: Microlearning & Scenario-based Learning: Complex financial concepts are broken down into digestible modules for easier comprehension. Interactive scenarios simulate real-world financial situations, enhancing learning engagement.

Case Study Library: A collection of real-life case studies illustrates various successful financial scenarios, providing users with practical learning experiences.

Effectiveness:

Leaderboards & Community: Encouraging friendly competition through leaderboards and rewarded points fosters community engagement, while gamification elements enhance user motivation and participation.

Data Security:

Decentralized Data Storage: Utilizing a private blockchain network ensures secure storage of user preferences and data, while blockchain-based verification guarantees privacy and integrity.

Access Control | Consensus: Enforcing access control mechanisms and employing consortium architecture safeguards sensitive information, preventing unauthorized access and data breaches.

WORKFLOW:

USER END APPLICATION OVERVIEW:

ML Workflow:

1.User Assessment: Users complete an SRIT test, providing insights into risk tolerance and financial behavior. 2.Data Collection: Test results and user data are gathered as inputs for the ML model. 3.Hybrid Recommendation System (HRS): Combining collaborative and content-based filtering, HRS generates personalized recommendations based on user behavior and preferences. 4.Fine-Tuned LLMs: Further refining recommendations using Fine-Tuned Language Models, ensuring accuracy and personalization. 5.Feedback Loop: Continuous improvement through user feedback, enhancing recommendation effectiveness over time.

Blockchain Workflow:

Overview: This project focuses on the deployment of a Polygon Edge Chain on Amazon Web Services (AWS). The Polygon Edge Chain provides high-performance, low-latency infrastructure for blockchain applications. By successfully running a Polygon Edge Chain, this project aims to facilitate the development of efficient and scalable decentralized applications

Consortium blockchain architecture: Node Each node stores a copy of the blockchain and participates in the consensus process to validate transactions and add new blocks to the chain. There are two nodes running on the polygon blockchain

Ledger The ledger is the decentralized database that stores all of the transactions that occur on the blockchain

Smart Contracts Smart contracts are self-executing contracts. These are used in blockchain consortium architecture to automate the process of executing transactions on the blockchain. The smart Contract Management component simplifies Ethereum transaction submission and application development by providing clean RESTful interfaces for interaction with your smart contract methods. Governance Consortium blockchain governance is member-defined and adaptable, comprising rules and decision-making mechanisms tailored to specific use cases and goals. Access to a private blockchain network is restricted to authorized parties only, and the network is not open to the public. Private blockchains are preferred in enterprise use cases, such as supply chain management, to maintain greater network control.