Often, enterprise's most valuable and dangerous asset is one that has been overlooked by traditional businesses. Companies like Amazon and Facebook have put customer analytical data at the center of their business model. For banks, however, leveraging, mining and exploiting customer data has often been an afterthought.
Many of the major banks today are the product of consolidation strategies. The result can be an incoherent view of the customer. This inhibits business opportunity and creates friction when regulators press for customer-related information.
What can banks learn from Amazon with respect to data management?
First, Amazon knows each of its customers and maintains a single customer record as the basis for developing a relationship with them. Second, Amazon wants to learn as much as possible about its customers. From the very start, Amazons curiosity about customers tastes and buying habits has set it apart from other retailers. The company is able to learn about its customers' tastes and habits and analyze that data in many ways that are useful to these customers. Such data analytics help drive improved customer experience and revenue.
Interestingly, Amazon doesn't need to buy other retailers to drive revenue. Instead, much of its revenue is driven by partners rather than by acquired companies.
Third, Amazon has built a true partnership model with its customers. In this partnership, the use of customer information for marketing and business development purposes is quite transparent and almost taken for granted by the customer. Their consent is given because, as in any contractual relationship, they are giving up information in exchange for a tangible benefit. Recommendations and targeted discounts provide an enhanced experience.
Other "crowd-learning" applications like Waze, a traffic navigator, utilize a similarly symbiotic business model. The customer becomes the center of a community mediated by the company.
How can banks move to a more Amazon-like model?
First, they have to rise above several challenges. There is such distance between banks and their customers that legislation was required to force banks to get to know them better. Many banks have been fined by regulators for failures in this area, proving that "Know Your Customer" has been an issue.
Why is this? Certainly, banks are not aided by customers who deliberately hide behind anonymity. However, there are other issues in trying to build a single customer view. Many banks have different businesses, including retail, wealth management, corporate loans and other divisions. Some of these businesses may have been acquired, which means that they may have different systems and customer record requirements. As an example, "Colin Bell" in one system may be listed as "Bell Colin" in another. This makes it harder to marry and reconcile systems that allow the bank to recognize that the two "Colins" are one and the same.
A further difficulty is caused by bank confidentiality laws that in some cases inhibit the ability to share customer relationship information across business units and geographies.
However, despite these issues, banks can still learn from Amazon's example. In many ways, it is simply a question of replicating traditional, community-based, face-to-face relationships between banks and their clients. But banks have to adapt to today's realities, which dictate winning trust through more intimate online relationships and social media.
Building a partnership relationship with customers is a new frontier for banks. Banks need to be more transparent about what they want to do with customer information. However, they also shouldnt expect customers to agree to cough up their data if there isnt something in it for them. Banks should instead approach obtaining data as a quid pro quo. For instance, some banks now offer customers additional fraud protection and an enhanced level of credit information services. In this way, customer trust can be earned by making the issue of consent a non-issue.
Banks should also start to think about data in the way they think about other assets, first by addressing the issue of asset accountability. Forward-looking banks have been appointing chief data officers and establishing an office with capabilities in strategy, data modeling, risk and companywide influence to focus resources on the effort.
Industry leaders are also putting in place business processes and metrics to ensure incentives and efforts are aligned. Metrics would include tracking data quality issues, while incentives might include linking bonus compensation to revenue growth related to data analytics or to reduced information security breaches.
Forward-thinkers are building out their data governance frameworks to ensure that consistent business process and tools are adopted. Given regulatory requirements, banks have to look for ways to comply that will also bring business benefits to their customers. Despite the impediments to leveraging social media and data analytics within the financial sector, banks can boldly go to the new data frontier.
Andrew Waxman writes on risk and compliance issues in capital markets. He is a consultant in IBM's Global Business Services' financial markets risk and compliance practice and can be reached at firstname.lastname@example.org or on Twitter @abwaxman. The views expressed here are his own.