As AI has become a more significant driver of economic activity, there has been increased interest from organizations to train all of the workforce with data driven skillsets. Organizations can enable digital transformation & create workforce of the future using OneNine AI to train all the employees about data driven decision making. It reduces entry barriers for individuals and businesses to start using AI and machine learning.
Workforce enabled with practical AI skillsets & data driven solutions to their problems
We are using AI to solve global issues like Carbon Emission, Space Weather Prediction & Pupil Distortion Detection. We also enable future workforce to build impactful projects using our Platform thought exclusive partnership with AVS Academy Flagship Student Projects & New Jersey Institute of Technology, a leading technological research university in the world.
Build Innovative organization while making positive impact in the world
Historical customer data is combined with machine learning algorithms to rank a customer’s likelihood to churn. Various algorithms are used in the model library to evaluates performance metrics using cross-validation. Understand the precise customer behaviors and attributes that can signal the risk and timing of customer churn. The accuracy of the technique used is obviously critical to the success of any retention efforts.
Identify customers with high churn probability & engage before they churn
Build machine learning algorithms to recommend the most relevant items to a particular customer. It provides analysts with association rules that can be used to predict the likelihood of products being purchased together & next best product. It captures the past behavior of a customer and recommends products/content which the users might be likely to buy/watch.
Identify best products your customer will likely buy
Over 90% of fraud detection use transaction rules to direct suspicious transactions through to human review. Automated AI models give analysts the ability to reduce the time spent on manual reviews and data analysis. With Machine Learning, you can enable your analysts’ team to work faster and with greater accuracy. Models can quickly identify if the user has drifted from their regular behavior.
Learn from historical fraud patterns and recognize them in future transactions
Analysts can create groups that reflect similarity among customers in order to maximize the value of each customer to the business. Customer segmentation has the potential to allow marketers to address each customer in the most effective way. Using the large amount of data available on customers (and potential customers), a customer segmentation analysis allows marketers to identify discrete groups of customers with a high degree of accuracy based on demographic, behavioral and other indicators.
Smart segmentation for better personalization
Credit risk plays a major role in the financial services industry. Many organizations have been facing an escalating credit default rate. Analysts can build AI models that helps to predict which customer is most likely to default and prevent the loss by providing the customer with alternative options (such as forbearance or debt consolidation)
Develop more reliable models in order to reduce the decision time
A high rate of attrition in an organization leads to increased recruitment, hiring and training costs. Not only it is costly, but qualified and competent replacements are hard to find. In most industries, the top 20% of people produce about 50% of the output. This use case takes HR data and uses machine learning models to predict what employees will be more likely to leave given some attributes.
Predict employee attrition at every level and define a strategy to reduce attrition