Predictive Analytics with INTELLIBOT
Predictive analytics is leveraged to create predictions about unknown future actions. It uses numerous techniques, such as statistical algorithms, data mining, statistics, modelling, machine learning and AI, to evaluate current data and make forecasts about the future. It aims to identify the possibility of future results based on the available historical data. The goal is therefore to go past what has occurred to provide the finest assessment of what will occur.
In business, predictive models engages patterns found in past and transactional data to recognize risks and opportunities. Variables capture relationships among many factors to allow valuation of risk or potentials related with a set of conditions.
The primary objective in an analytics project is to quickly demonstrate the analysed data’s effectiveness. By elevating their data quality, organizations could complete their projects and achieve their first data results. These data results could then be used to mature and develop more features and continuously improve results and model outputs.
Who Uses it ?
Growing organisations use Predictive Awareness to identify concealed opportunities and uncover hidden risks buried within the organizations past data. By leveraging Predictive Analytics and exposing the capabilities to everyone within their organization empowerment to make the right calls at the right moment and
transform their future into a greater success is eminent.
Does your organisation also leverage the power of Predictive Analytics?
Industry Specific Use Cases:
Banking & Financial Services
The financial industry, with an enormous amount of data and money at stake, has long implemented predictive analytics to detect and reduce fraud, measure credit risk, make the most of cross-sell/up-sell prospects and retain valuable customers.
Retail
Retailers everywhere are using predictive
analytics to determine how much stock
needs to maintained based on future
demand predictions and the impact of
sales and also provide relevant customer
offers
Health Insurance
The health insurance industry is taking steps to identify patients at high risk of chronic diseases and recommend optimal interventions for best results. Health Insurance also leverages
Predictive Analysis to detect claim frauds.
Governments & the Public Sector
Governments have been important participants in the progression of technologies. Governments now use predictive analytics to enhance service and performance, detect and prevent fraud, and better understand customer behaviour.
Manufacturing
It is extremely important for manufacturers to identify aspects directing to decreased quality and production failures, as well as to
optimize parts, service resources and
distribution.
Oil, Gas & Utilities
Predicting machine failures and upcoming
resource needs, safety and risks, or refining
overall performance, the energy industry has
incorporated predictive analytics as a game
changer.
INTELLIBOT Predictive Analytics Platform
Intellibot is very excited to introduce Intellibot Predictive Analytics & Intellibot Recommendation Engine as a very significant addition to its current machine learning offerings.
These functionalities are an integral part of the Intellibot platform and do not require connectivity to external cloud environments.
Intellibot Predictive Analytics capability to consume PMML Models created using multiple frameworks such as R, IBM SPSS, TensorFlow, AWS SageMaker and more, enabling organizations to bring together process, people, technology and information into a value network and provide extensive selection of data and decision-making capability.
How simple is it?
Just configure the PMML file path and Intellibot Predictive Analytics in sync with the Intellibot Recommendation Engine will dynamically create simple Data Input and Output Ports for the dependant and independent variables distinctly.
Machine Learning algorithms currently supported by Intellibot :
• Associative Rule
• Clustering
• Cox Regression
• GBM
• General Regression
• Multinomial Regression
• Naive Bayes
• Neural Networks
• Random Forest
• Regression
• Support Vector Machine
• Tree Model