%201.svg)
CogniFinX
Problem Statement
Uncertain Forecasting
As per USChamber reports, an estimate of 82% of businesses often struggle in accurately analyzing and predicting cash flow due to variable revenue streams and expenses.
Time-Consuming
Traditional, manual forecasting methods consume up to 50% of financial analysts' time and are prone to errors.
Inadequate Real-Time Insights
Companies often lack access to real-time financial insights, leading to delayed responses to financial issues.
Lack of Predictive Analytics
60% of banks lack the advanced analytics capabilities needed to predict future financial trends.
Our Approach
Feature Engineering
Extract key features such as time of day, day of week, seasonality, economic and market conditions, holiday, transactions to enhance the forecasting power of the model.
Data Collection
Collect historical cash flow data and Weather, Location, Festivals & Holiday calendar etc.
Model Selection
Our product utilizes time series and sequential regression models, or ensemble methods based on the nature of the data and the forecasting requirements with MLOps.
Continuous Integration
Integrating real-time data for retraining the AI models with feedback.
Training Techniques
Our models use temporal cross validation to evaluate the model on future periods and also weighted feature analysis to improve accuracy of predictions.
.avif)
Our Solution
.avif)
- Leverage AI algorithms to extract key features and provide accurate cash flow predictions, enhancing proactive decision making capabilities.
- Intra-day, day- ahead and week ahead, 14-day, 1 month and other forecasting models to streamlines business operations and minimize issues by using historical data from various data sources.
- Offer real-time cash flow analysis, enabling timely adjustments and optimizing cash management strategies.
Impact
.avif)
- Improve the logistical efficiency by 35%, helping businesses better anticipate financial needs and avoid cash shortfalls
- ML forecasting models provide operational improvements and potentially save the banking sector up to $60 billion annually.
- Real-time analysis enables businesses to react swiftly to financial changes, reducing response time. Also, cash forecasts can be generated 3,000 times faster than manually using ML models with 95% accurate predictions using ForeCashT.
Enquire more about this product
Explore other products
Get in touch
Reach out today for personalized assistance and tailored solutions. Contact us now for answers and a customized quote. Let's bring your vision to life efficiently and effectively!