Big Data for bankingYour customers provide it. Your sales and customer service reps need it. Federal, state, and municipal governments require you to report on it. And your bank’s future depends on it.

Do you know what it is?

It’s data – and it’s everywhere.

However, to manage today’s highly volatile and heavily regulated financial environment and react quickly to changing conditions, simply collecting data is not enough. Banks must be able to access the right information at the right time and know how to glean actionable, accurate insight from it.

For many banks worldwide, in-memory computing is opening up new possibilities for rapid aggregation and processing of mountains of data from disparate sources. Banking decision makers are making well-informed decisions quickly, preventing losses, capturing more profits, and handling regulatory reporting more effectively.

If your bank has not yet entered the world of in-memory computing, don’t worry. If you follow this three-step approach for incorporating in-memory computing capabilities into your data infrastructure, your entire organization will soon be able to complete complex banking analyses and transactions in real time for faster, more effective business decisions.

Step 1: Use in-memory computing in an existing system for a quick win

By storing data for financial analysis and risk and regulatory analysis on an in-memory database, banks no longer need to aggregate data. Instead, banks can obtain detailed view of subledger accounting and access accounting results at the transaction level immediately after daily and periodic processing.

As a result, decision makers have a single source of the truth when it comes to analyzing financial and compliance data for different risk and regulatory views and creating real-time simulations and stress testing on that data.

Step 2: Integrate analytical data with in-memory computing

Integrating every piece of analytical data enables banks to manage financial positions and generate postings in near-real time. High-capacity, overnight batch processing increases valuation frequency, allows daily accruals of performance calculations, facilitates additional processing for risk and regulatory evaluation, and delivers earlier results for reporting purposes.

This step also makes it easier to handle even the most complex regulatory evaluation, as required by government and industry authorities. Banks can perform evaluations ad hoc or in parallel with each other. Plus, integrating additional scenarios and business simulations extends this analysis from actual results to future results.

Step 3: Apply in-memory computing to all data

In this final step, customer-centric and transactional banking is shared across the same database – without any replication. By processing customer-centric and transactional banking data with existing analytical banking applications in real time, decision makers can react immediately to changing business and regulatory conditions by accessing reports that give a full view of the entire banking operation.

To read more about how in-memory computing can help you bring operational, analytical, and business processes together, download the free SAP thought leadership paper “In-Memory Computing for Analytical Banking” (registration required).