Custom Machine Learning models to solve complex business problems
Machine Learning is opening a wide variety of new business opportunities and helping businesses adapt new processes. Leveraging machine learning, we can help organizations automate their activities and make their processes smarter.
We have deep domain expertise to help our clients leverage machine learning-powered models into their business. Our machine learning services will help our clients in increasing their productivity and faster decision-making capabilities along with-
Our highly skilled team leverages the latest data processing frameworks and develops advanced machine learning algorithms. Our solutions are capable of interpreting complicated data, detecting trends and identifying patterns to solve your business problems.
A McKinsey report reveals that machine learning models can reduce credit losses by up to 10 %, with more than 50% of risk managers expecting credit decision times to fall by 25 to 50%.
The credit risk industry can greatly gain by leveraging Machine Learning to build consumer Credit Risk Analysis models. At Soulpage IT Solutions, we help businesses build custom ML credit risk detection models perfectly suited to their needs. Our Credit Risk Detection models help in not only getting a fair assessment of the lending risks but will also help expedite the decision-making process to positively impact productivity.
Our Time Series Forecasting models will automate the development of sophisticated time series that predict the future values of a data series based on its past behavior and present trends. This helps our clients in improving their sales forecasts, product demand, financial applications, etc. We leverage machine learning to deliver highly accurate forecasts by integrating the best practices in time series modeling and achieve the highest possible accuracy.
We build forecasting models that are unique to clients’ data and hence the forecasts are custom fit to their businesses. Our time series forecasting models help our clients in
Machine Learning’s ability to instantly detect anomalies more efficiently is enabling enterprises to make a smooth transition from traditional ruled-based processes to intelligent solutions by using unstructured data sets.
We help our clients build custom anomaly detection and self-optimizing machine learning models to prevent, detect, and manage frauds.We develop our ML-driven fraud detection and prevention models based upon our clients’ risk profile and specific pain points. Our advanced fraud prevention models constantly learn and prevent traditional and trending tactics.
Be it reducing application fraud, retail and eCommerce fraud or open-account fraud-we will help build the best model for your business.
Our ML-driven model that analyzes passengers’ transit was built on 2 data sets from 2 different time periods. We took into account various factors like the routes, total number of passengers traveled, seasons, etc and gained insights on the busiest routes and stations, the busiest time of the day, the busiest day of the week, etc. With these inferences, we were able to forecast the average weekly ridership for a duration of 2 years with an error deviation of 4%.
We developed models to predict the demand and supply of electricity in households by considering the appliances used. By leveraging Machine Learning, our model achieved 62. 01% accuracy. Our model benefits in identifying future electricity patterns and faulty appliances, while optimally consuming the required amount of energy and thereby save resources.
Feel free to say hello for any queries and questions. We would be happy to answer your questions & setup a meeting with you.