Big Data for Banking by SAP

By Michel Borst,VP, Financial Services Industry, SAP

1. What are you going to offer in BIG DATA in 2013? What are the product and services roadmap that you have prepared for this theme?

Big Data was one of the top priorities of CIOs in the past few years. In 2013, Big Data makes its move into the list of the CEO. With the innovative technology to handle Big Data becoming mainstream and more affordable, companies have put the necessary infrastructure in place. The race is now on to make best use of the data to deliver value.

Michel Borst,VP, Financial Services Industry, SAP

The Big Data topic has always been dominated by data generated by social media sites. However, it is the analysis of other sources of data which already exist in the organization that will drive transparency, operation efficiency, cost reduction and changes to business processes. The technology required to create value out of the large volumes of internal data from disparate sources were out of reach of most companies previously. Data needs to be collated, processed, analyzed and made available to users who require it to make better decisions in a timely manner. The advances in the technology to enable this:
  • In memory technology which processes millions of rows of data in seconds.
  • Analytics software which not only delivers highly visual results in business user friendly format, but is also easier to use, making it accessible to more people instead of a handful of data analysts.
  • Mobile technology which allows information to be instantly available on mobile devices like smartphones, tablets anytime, anywhere.

It is no longer sufficient to have information the next working day, the next week or the end of the month. Your customers, shareholders, suppliers, competitors have information in their fingertips and you are expected to have it too.

2. What are the industry developments that you think will occur in BIG DATA? The big data revolution is expected to continue to disrupt established industries and current business models.

For instance in the banking industry which has been operating in a tough economic environment, under increased regulatory pressure and managing changing customer behavior, Big Data is both a challenge as well as an opportunity. Optimal use of technology will be the differentiator. Two examples of Big Data use which SAP will be launching in 2013 are:
  • Liquidity Risk Management – Greater than 250 million cash flows can be processed in a second. This enables the bank to manage their liquidity risk in real time. Decisions can be made based on facts at any time; there is no longer a need to wait for hours or days for data.
  • Fraud Management – Fraud can be detected as it happens in real time so that appropriate actions are taken immediately.

In addition to meeting regulatory requirements, banks are also under pressure to meet the changing expectations of customers. Customers expect their bank to know what to sell to them at the right time. With information available readily via smartphones and tablets, customers compare prices, products, services and know their options. Banks have to continuously look to their Big Data for answers to retain and gain profitable customers.

3. How do you see customer demands shaping up in BIG DATA? 

Deploying Big Data Technology and the ability of handling massive amount of data in both structured and unstructured form is not what Big Data is about. The value of Big Data lies in the use of it by people in different levels of the organization to make the right decision at the right time. Now that we have the technology to handle Big Data, the push in 2013 is finding the value hidden within it.

4. And how would your offerings impact on your customers? 

(A scenario describing the impact of your product/service on one customer's technology and business/user environment We see banks doing sophisticated customer segmentation and campaign monitoring to get maximum value out of their marketing dollars. With the technology to process Big Data now accessible, here is an example of how one bank had taken this to the most granular level in real time.

A customer walks into a branch and deposits a large cheque (over 2 standard deviations larger than any other deposit in the last 1 year). As the deposit is recorded and processed, real time analytics triggers an alert that this deposit represents an opportunity to make a product offer. An alert is sent to a call center or a relationship manager to call the customer to make the offer within2 hours. The customer accepts the saving bond offer, retains the money in the bank and gets a greater wallet share of the customer.

The bank in the example has found a use of Big Data they never considered before. The banks who can find good use cases first will have the advantage of capturing the customers. Finding good use cases cannot be left to an Analytics Team or to Data Analysts. More people in the organization need to have access to Big Data and the tools for analysis:
  • Granular risk information in market, credit and liquidity risk
  • Granular information on customer, products, transactions
  • Easy to use analytical tools, enabling business users to do analysis, simple predictive, hence freeing up the data analysts/scientists to focus on complex modeling
  • Highly visual ways of viewing and interpreting data using visualization and geographical mapping tools
  • Information available on the go on mobile devices