New Analytics Are The Future Of Banking—Are You Ready?

Andy Hirst

Not so long ago, people used to rely on their local bank manager to know their personal financial situation, provide personalized advice, and make targeted recommendations to help them achieve their goals. But times have changed. As banks have consolidated and the industry has evolved, high-touch services like this are no longer feasible for every customer. It simply doesn’t scale or meet modern customer demands—for example, for mobile access to their financial information.

Now, banks need to “know” their many customers by the massive volumes of data they collect on them. This data can be analyzed to reveal their habits, worries, major life events, preferences, priorities, and more—and when harnessed properly, to enable banks to provide better engagements and differentiating service.

But as noted in a recent IDC InfoBrief “New Analytics Techniques Fuel Data Transformation in Banking,” most banks aren’t prepared technologically to turn their data into powerful customer insights. Their systems were designed for the days of the local bank manager.

How can new tech help you know your customer?

But the fact is, new analytics such as predictive analytics, artificial intelligence (AI), and machine learning can empower employees at all levels to better understand clients’ needs and provide even more personalized services and solutions than bank managers of the past. Today’s exploding customer data records—which include valuable, unstructured data pools—can reveal everything from what car customers own, to the phone they have, the vacations and credit card purchases they make, their cash flows each month, the life events that impact them, and more. Analysis of this data also lets you segment customers by social spending type (for example, traveler, medical, or sports-oriented), so you can offer targeted promotions and partner on related, relevant services at the right time.

Harnessing data in these ways is imperative today. To simply keep existing customers, your bank is expected to use this data to understand the context of each customer across any channel, as well as to anticipate their needs, personalize services, and make targeted and relevant offers at just the right moment. And to compete with emerging, digitally native banking competitors (who really “get” Big Data), you need to aggregate all the data, analyze it in real time, and provide front-line employees or channels with information to make the right recommendations for clients at the time of engagement.

These new, nimble, digital players will raise the tide—and while compliance with complex banking regulations will continue to be a barrier to their entry into some service areas, make no mistake: If you rest on your laurels, they will either catch up or out-innovate your organization.

Read the infobrief “New Analytics Techniques Fuel Data Transformation in Banking” from IDC, which explores how modern analytics are being deployed to transform modern banking. The paper also discusses the five stages of information transformation, which you can use to assess the maturity of your business and what steps you need to take. And it showcases three common use cases to help you understand the potential business value of investments in Big Data analytics for financial institutions.

Andy Hirst

About Andy Hirst

Andy Hirst is vice president of Banking Solutions, SAP Banking Industry Business Unit, at SAP. He is responsible for driving the success of the SAP go-to-market strategy in Line of Business Cloud Applications and Analytics in Financial Services. Previously, Andy was responsible for Capital Markets solutions for banking. Andy is an expert in Big Data and analytics use cases in financial services and has been involved in many digital banking initiatives for banks.