Predictive Data Analytics

Predictive Analysis (PA) uses a wide range of techniques from statistics and data mining. PA filters through the historical data and forms trend patterns that can be used to support several decision and strategy making efforts.

Over the last two decades quantitative analysis has been taken the center stage with managerial decision making.

Common risks for an enterprise involves financial, credit, operational and hazard. Financial risks include risks arising from treasury operations such as capital structure, interest rate risk, hedging, pension contributions and cash management) as well as risks arising from global economic activity and procurement policies such as rising raw materials costs. Credit risks include risks of customer defaults as well as management of the firm’s accounts receivable and payable. Operational risks include things like IT failures, supply chain breakdowns, fraud and mechanical break-downs at plants. Hazard risks can include traditional insurable risks like catastrophe and product liability, as well as risks like stakeholder litigation.

These risks can be evaluated using quantitative methods, and their impact on firm profitability is understood when evaluated appropriately. Many of these risks are analyzed on a standalone basis that may not provide a comprehensive evaluation of the risk. This is where Synerjix Actuary Service teams up with IT to gather disperate information scattered throughout the enterprise and brought in for quantitive analysis leading to efficient decision-making.

  • Historical transaction data is analyzed to identify patterns and is used to predict risks and opportunities.

  • An optimum mix of products to carry as well as optimum pricing and promotions can be derived from store transactions data.

  • Building efficient supply chains