The data used for prediction is analysed first like what happened, why it is happened? Then it is monitored for what is happening now? After that predictive analytics is applied to find out what will happen in future and then a respective action for the prediction is applied. This whole process takes place with respect to time. Predictive analytics allows the organization to become proactive, forward looking anticipating outcomes and behaviour based on data and not on assumptions.
Predictive Analytics Lifecycle
Data Collection, this phase collects the data from multiple sources; Data Analysis, this phase is process of transforming data into useful information to get a meaningful conclusion; Statistics, this phase helps to validate the assumptions made against the predictions; Modelling, which creates predictive model for future; Deployment, the predicted model is deployed in the everyday decision making process to get the output, reports etc., Monitoring, the predictive model is monitored to ensure whether it provides expected results.
Risk Management with Predictive Analytics
Predictive analytics scans thousands of data sets and past histories as well as social media data and finds out the behavioural pattern. From the identified patterns it helps to map the changes in the industry through which it helps in identifying the reason behind the problem. Risk Management with predictive analytics helps organizations in minimizing risks that can damage brand value or result in losses.
Our Predictive Analytics will address the sectors like Treasury, HR, Supply chain etc.,
Pain Points of Addressed Sectors
• Corporate accounts often are in multiple currencies and across several geographies, these require complex interactions to be able to view and monitor all the account and transaction information
• New regulations allow treasurers to view and monitor all of their bank accounts on a single platform
• HR Analytics help organizations remain competitive in several aspects beginning with acquiring top talent and retaining them.
• IT helps us provide evidence-based advice on how to drive the business from a people perspective
• It also enables the HR initiatives to be pursued by line-of-business leaders to help them reach business targets
• Search on unstructured data (local files & folders)
• Identification of Suppliers
• Integrated view of supplier performance
• Lack of indexation of supply chain and transaction dataSupply chain risk prediction
EXTENDED USE CASE- PREDICTIVE ANALYTICS
PREDICT OTHER RISKS
q Market Risk
q Regulatory Risk
q Forex Risk
q Supply Chain Risk
q Supplier Scores
q Supplier Tiers
NON FINANCIAL ANALYSIS
q Stream the social data with respect to the bank
q Do sentiment analysis on the data that enables better decision making
q Supply Chain Disruptions-Natural Factors