Making customer data work for the customer
No doubt “big data” is one of the most popular terms in banking discussions and has even seeped into consumers’ frame of reference. Who hasn’t noticed when the ads on a website eerily mimic your recent Internet search history? While it’s talked about ad-nauseam, many banks still struggle with how to leverage the vast amounts of information at their fingertips for marketing purposes. It’s not exactly that they are doing it wrong, but more that they aren’t taking full advantage of the potential.
It doesn’t help that everyone has a different definition of big data. What does it encompass? To turn data into financial results, banks should include the wealth of transaction-level data that is available through transaction accounts, debit and credit card accounts and loan products in their definition. This can include geo-data, demographic data and the velocity of funds into and out of accounts. No matter what it’s made up of, transaction-level financial data is what banks need to be focused on.
However, in order for the data to keep flowing, bankers must make it clear to their customers – the creators of this treasure trove of information – that the data is being used for their benefit as well as the bank’s.
Some personal financial information can be mined from your existing relationship with account holders, such as debit card transactions, but you must dig deeper and gain insight into additional spending behaviors. Encouraging customers to utilize budgeting tools or a full personal financial management (PFM) suite opens doors to extensive spending data, as well as the information associated with accounts that aren’t held under your bank’s roof. If an account holder uses a credit card for a large amount at an auto repair shop, for example, it could be good timing to place a special offer for a car loan in front of them.
One area that financial institutions have not fully tapped into is social media data and other “lifestyle data,” such as Facebook check-ins and likes. Some person-to-person (P2P) lenders and Web banks, such as Upstart and Moven, have begun leveraging social media data in loan decisioning and underwriting. This rich data can also have a major impact on cross-sell and retention efforts in other ways. Let’s say an account holder’s child is graduating from high school and we learn from social data that they are planning to attend college. This information can be used to send out a promotion for student loans or deals for housing in that college town.
The power of lifestyle data is that the bank can learn details about the customer that wouldn’t be shared at the desk during a new account opening. If a bank leverages social data to work to effectively help people with life events, the account holder has more of a reason to stay loyal to that institution.
Yet, while consumers have become more accustomed to customized service and offers and are sharing more about their personal lives via social media than ever before, they are also simultaneously becoming more wary of how their information is used. Spending data is one thing, but lifestyle data can raise a personal barrier for many people. Banks must be very careful if they want to gain access to this information without being accused of “big brother” actions; customer buy-in is vital.
The first step is to give account holders comprehensive opt-in options for what they are willing to share. Banks must also provide tangible rewards for using services that feed the data machine. A loyalty system should be set up that benefits account holders when they leverage online banking, debit cards, PFM and other tools. This can be as simple as “points” associated with login or use or using a certain card frequently. In order to get account holders on board with these data initiatives, you must give them value as well as confidence in the bank.
Another bonus banks can offer is an alerts program. While these tools have been used by banks for years, transaction-level data could make them much more useful for account holders. Along with providing the traditional basic alerts, such as when an account balance is getting low or there is a suspicious charge, account holders can customize the alerts they receive based on spending. For example, a customer could choose to be alerted when a late charge is looming on a credit card account or a purchase will get them close to their credit limit. The ability to customize alerts is driven by the account holders’ spending data, which they would need to opt in to provide the bank while reaping significant benefits themselves.
Having customers proactively share this data can also enable banks to provide targeted personalized advice, such as how a purchase could affect a credit score or why using cash is better in certain situations. This is the marriage of financial data and social data. Investing in the consumer’s financial well-being goes a long way in showing them their data is being used for their benefit.
To start using big data and take full advantage of the opportunities, banks need to make sure that they break down their data silos. The auto lending platform, for example, might contain customer data that could assist with decisioning in the mortgage lending system. Banks must find a way to bring down the walls between various locations where data is housed. This can be done in two ways. Either these forms of data need a common structure or outside providers can provide you with the ability to feed data into a system or pull data out of a system.
The fallacy of big data is that in and of itself it will produce results. However, you need to have a plan for the type of information that would be useful to your institution and how you will use it. Know what you’re going to do with the results.