Are you using the data you have to understand and target your marketplace and each customer need? The truth is that most banks today generate more data than they are capable of exploiting.
But does the instant availability of data, combined with less expensive and faster computing capability, make big data a competitive silver bullet or is it just the next shiny object that will distract us from the real business at hand? Bottom line... is more data actually better?
Being saddled with legacy siloed technology platforms, lacking analytical expertise and structured only to support traditional approaches to data usage, many financial institutions are finding they’re woefully unprepared for the challenges of working with big data (usually defined as data inside and outside the organization that is both structured and unstructured).
A better starting place for most banks is to start small, using a building-block approach to data management. This would address the most immediate hurdles facing banks today including: 1) improving the integrity of current data, 2) integrating multiple data silos, 3) leveraging real-time data, 4) improving accessibility of data, and 5) better analyzing data sets.
Improving Data Integrity
Before we expand our data inputs, we must make sure our existing database is complete and accurate. While names and addresses may be up to date, the same can’t usually be said for phone numbers, email addresses and preferred communication channels. >In addition, important information such as mobile phone numbers and services held at other institutions is usually not collected.
To move forward in the world of big data, we should first build a plan to update and backfill outdated and incomplete data files. This process starts on the front line, in our call centers and through customer surveys.
Integrating Data Silos
Most banks still have individual data silos for the retail consumer, small businesses, commercial accounts, the mortgage portfolio and possibly other credit services such as credit cards. Without an integrated platform, a fully functioning 360-degree view of our customers is impossible.
A common scenario occurs when banks don’t recognize small business or commercial relationships of retail customers. Breaking down silos between product lines and integrating the data should be done before any overarching big data initiative is considered.
Leveraging Real-Time Data
As more customers are using online and mobile channels, there is a need to leverage real-time data from both the bank and customer perspective. Yesterday’s data, while important for trend analysis, is much less valuable for risk analysis and marketing optimization.
Today’s customer expects all transactions to be reflected immediately as they use their cards, transfer funds online, and increasingly use their mobile devices to transact. Other industries have also made them accustomed to relevant offers, communicated using the right channel at the optimal time. To accomplish this in banking, we need to collect (and act on) real-time data.
Expanding Data Accessibility
Integrating accurate and complete real-time data is powerful only if it can be easily accessed and effectively analyzed across the organization. This will require a new operating model and approach to data management.
Since many banks are already dealing with data overload, the odds are not in our favor that more data will automatically improve results. But until all areas are seeing the same view of the customer, and can make business decisions based on insight available, the potential of big data will be lost.
Remember, more data doesn’t fix bad analysis. Progressive banks in the future will be engaging with customers in ways that were unforeseen only a few years ago. Retail banking will be operating faster as described in a recent blog post written by Scott Bales from Movenbank entitled, “Finding Serendipity in Big Data.”
Competitive advantage is achievable through the better analysis and use of customer data and big data definitely deserves to be part of our planning and strategy process. But banks should start small as opposed to boiling an ocean. Some starting steps include:
- Use account level and transaction data to build life-stage trigger communication programs (new movers, retention, onboarding)
- Leverage transaction data to improve risk and fraud monitoring
- Review channel and transaction data to determine optimal branch reconfiguration (size, structure, support)
- Use funds movement data to determine price elasticity of products and customer segments
Now is the time to improve the accuracy of data already stored, build real-time capabilities, break down existing data solos and improve the accessibility and analysis of data to ensure that the concept of big data doesn’t move towards the trough of disillusionment and lost opportunities.