Forecasting has become increasingly important in the BFSI segment, helping organizations in better process planning, says  SAS Global Services senior principal consultant Dinkar Sathe. Excerpts from an interview with Nanda Kasabe of CyberMedia News.

How can forecasting help banks?
Banks today are faced with a variety of issues that need to be addressed swiftly and simultaneously. As more banks enter the retail banking space, there are two issues that come to the fore: increased competition and an influx of large amounts of data. This data can be used to understand banking business better and forecast ways in which to counter competition.

Funding allocations, inventory planning and scheduling, are all based on predictions for the future. The more accurate the forecasts, the better the decisions, so forecasting is vital.

Lately, banks have been using forecasting for ATM management to check the optimal amount of cash in the machines to guard against theft. Forecasting is also being used in stock predictions. Even call centers are using these to predict attrition trends.

Do you see an increase in the use of forecasting in the global BFSI segment?
Definitely. Take SAS. Around 40% of SAS revenues come from BFSI segment. Forecasting is becoming increasingly important because this offers prediction of revenues and allows for better planning exercises.

Can you elaborate on Hi-Performance forecasting solution from SAS?
The new solution from SAS is the fastest and most analytically advanced large scale-forecasting program in the market. This helps transform transactional data into time-series formats, automatically selects the time-series models that best explain the historical data, optimizes all model parameters and generates large volumes of forecasts. It performs forecasting in a batch environment to produce millions of forecasts with speed and accuracy. It also helps prepare for changes and predict trends as normal part of business, without requiring companies to re-train or increase their staff to analyze and update huge volumes of data.

What are the major markets for these forecasting solutions?
These could be used in ATM management, stock predictions, buying and selling of mutual funds, predicting churn in the telecom industry and attrition in call centers. The US government uses forecasting for census, making budgets, predicting GDP and inflation rates.