Python modules to support AI/ML

R modules to support AI/ML

Economic Trend Modeling

Enhance economic forecasting accuracy beyond traditional statistical models to better predict economic events

PDF Optical Character Recognition (Text)

Automate extraction of structured column data from unstructured PDF reports to reduce manual processing time and errors

PDF Optical Character Recognition (Images)

PDF OCR (Images) – Extract textual information from images embedded within PDF documents for comprehensive document analysis

Stock Market Analysis

Quantify relationships between news media narratives and stock market volatility to improve market event understanding

Commercial Real Estate Index

Synthesize commercial real estate data points into a comprehensive market index for improved market monitoring

Variable Optimization

Determine optimal lag structures to enhance accuracy for forecasting call report metrics

Credit Fragment Analysis

Identify meaningful patterns in fragmented data to support more comprehensive research analysis

Proposals and Public Comments

Efficiently process large volumes of public regulatory comments while ensuring proper handling of sensitive information

Manufacturer Sentiment Analysis

Convert qualitative survey responses into quantitative insights on industrial production forecasts

Supply Chain Estimations

Identify and measure supply chain constraints that could impact broader economic performance

Body Worn Cameras Data Management System

Body Worn Cameras Data Management – Ensure proper handling of information in body camera footage while making content searchable

Market Fund Portfolio

Accurately identify security issuers in money market fund portfolios

Sentiment Analysis of Earnings Transcripts

Measure and classify sentiment in bank earnings calls to identify emerging trends

Anomaly Detection

Identifying irregular patterns in firm-submitted information based on historical submission patterns

Consumer Complaints Explorer

Categorize large volumes of consumer complaints into topics to facilitate appropriate analysis and response

Regulatory Data Analysis

Identify potential reporting anomalies by comparing current submitted values against expected ranges based on historical patterns

Decision Tree for Deposits Data

Detect outliers in current reporting data to enhance overall data quality and reliability

Novel Activities Call Report Classification

Identify emerging or non-traditional banking activities

Financial News Processing

Transform large volumes of unstructured financial news into structured, actionable insights

Bank Exam Quality Control – Model 1

Enhance quality control by incorporating external news data into performance assessment models

Document Summarization Statistics

Extract meaningful metrics and term frequencies from lengthy documents to identify trends and common issues

Writing Quality Analysis Model

Ensure consistent, high-quality writing across organizational documents through automated style and quality assessment