We are working for more than two and a half decades for making government digital.
Get a QuoteThis is a specific practise or activity that may be used as a collection of technologies supporting a wide range of sourcing options. These include buying from online web stores, conducting tenders and sales through e-auctions or e-marketplaces. This can be taken a step further by using decision support systems and analytics. Evaluation can be performed to some extent without human intervention. This will link the transactions back into their core financial applications for estimates.
Every portfolio has a set of delinquent customers who do not make their payments on time. The financial institution has to undertake collection activities on these customers to recover the amounts due. A lot of collection resources are wasted on customers who are difficult or impossible to recover. Predictive analytics can help optimize the allocation of collection resources by identifying the most effective collection agencies, contact strategies, legal actions and other strategies to each customer, thus significantly increasing recovery at the same time reducing collection costs.
Fraud is a big problem and is of various types. Inaccurate credit applications, fraudulent transactions, identity thefts and false claims are some examples of this problem. Suppliers and even services providers i.e. basically any supply-chain network in the government system.
Often the focus of analysis is not the consumer but the product, portfolio, firm, industry or even the economy. For example a retailer might be interested in predicting store level demand for inventory management purposes. Or the Government might be interested in predicting the unemployment rate for the next year. These types of problems can be addressed by predictive analytics using Time Series techniques or more effectively by analytics.
Use of predictive analytics in government agencies can generate ROI as well as increased agility and reduce ongoing costs while providing better service to citizens. Analytics can help them use scarce resources more effectively.Use of analytics in transportation leads to more accurate traffic forecasting as also improved transportation planning. Analyzing and predicting traffic flows and growth is a complex process in populated countries like India, but can lead to significant benefits, including decongestion of roads and motorways. For the purpose, data has initially to be obtained from existing databases or records
This data, obtained from a detailed transport survey, has to undergo complete extensive pre-processing before it is amenable to data mining. Analysts can then select a representative variable for each group of fields, and ensure that the groups are independent of their effect on transport mode. This process, involving analytics in the form of neural networks, leads to the prediction of a three-way variable whether someone would walk, drive, or take public transportation for a specific journey.
An equally important application of analytics is its use to support public safety and security efforts. Public safety agencies not only can access data from multiple databases, they can also integrate textual data such as field reports, phone records and transcripts, web page content, and e-mails in multiple languages into their predictive analysis. This enables analysts to detect patterns that suggest likely security threats or criminal activity, and relay this information to the field, so that staff can be deployed appropriately.