AI Data Extraction

Our platform enables users to swiftly access credited services by allowing them to upload their previous transaction history. This data is then processed using AI to swiftly generate credit profiles.

Data Collection:

Transaction History: Users upload their previous transaction data, which includes details such as payment amounts, frequency, types of transactions, and associated vendors.

User Information: Alongside transaction history, relevant user data such as demographics, location, and any other provided personal information is gathered.

AI Processing:

Data Preprocessing: The AI cleans and organizes the uploaded transaction history and user information, identifying and rectifying any inconsistencies or missing data.

Feature Extraction: The AI algorithm extracts key features from the transaction data, such as spending patterns, regular payment recipients, frequency of transactions, and consistency in payments.

Profile Generation: Using machine learning algorithms, the system creates user profiles based on the analyzed transaction data. It identifies behavioral patterns, creditworthiness indicators, and risk factors.

Credit Scoring: The AI model generates an immediate credit score based on the derived profile, assessing the user’s reliability for accessing credited services.

Important Information for AI Profiling:

Transaction Details: Payment amounts, frequency, types of transactions (one-time, recurring), and categories (utilities, rent, subscriptions, etc.).

Consistency and Timeliness: Regularity and timeliness of payments as indicators of reliability.

Spending Patterns: Identification of consistent patterns in spending, understanding financial habits, and behavioral traits.

Geographical Data: Location-based spending and transaction patterns.

Privacy and Security Measures:

Data Encryption: All customer data, including transaction history and soulbound tokens, are encrypted to ensure privacy and security, especially during AI analysis for credit scoring.