Winning the Race to Provide Enhanced and Connected Banking

Facing unyielding competition from new players, tighter margins and changing customer expectations, banks are on a quest to optimize customer profitability. And the key to achieving this goal is right in their laps – customer data.

Financial service providers are sitting on a treasure trove of valuable customer data that they must start using smarter and more efficiently before others beat them to the punch. Doing so will put them into the future of financial technology – where newfound customer value and increased profitability await.

Three Ways to Leverage Data Smarter

While 57% of bank executives believe it is very important to develop advanced analytics capabilities as a way to create actionable insights, only 17% believe they are very well prepared to do so, according to a PWC study. For most, this roadblock is a result of having many different types of data spread across many disparate systems. This leads to an inability to gain a single, comprehensive view of the customer. Even when banks are able to integrate customer data, it is often challenging to marry the data in a way that makes it readily usable and transactable.

However, banks can improve data quality and quantity by creating a unified data model that can accommodate structured and unstructured data from all critical sources, including customer relationship management, risk and enterprise performance-management systems and even outside data from places such as social media channels. This provides banks with a more accurate view of the customer and ensures that everyone across the enterprise is “speaking the same language” when assessing customers’ profitability. While firms can build this model from the ground-up, banks can also leverage commercially available data models that have been built for the industry for a more cost-effective and customer-centric approach.

With a unified data model, firms are better positioned to create an enhanced and connected customer experience. Here are three areas in particular that banks can leverage data to win customers and maintain and potentially expand their market share.

• Smarter Lending. Customers today expect lending to be easily accessible at any point in time, the application process to be quick and seamless, and timed to key life events such as buying a home or expanding a small business. To remain competitive against challengers like Lending Club, SoFi and Kabbage, traditional banks must do a much better job of meeting customers’ expectations. An Oracle survey found that one in three consumers are looking for alternative loan providers because of an unsatisfactory experience with traditional banks. Oftentimes, customers are more concerned about the speed at which they can access cash than the loan rate, particularly in areas such as small business lending where time truly does equal money. Fintechs have been able to address this market need faster than traditional banks. As a result, banks run the risk of losing the key small business market to non-bank financial institutions like some have with mortgage lending.
  
  By leveraging data analytics and machine learning, banks can target and capitalize on customers’ key life moments. For example, if a consumer is looking at a house on a property website, a bank can see that data, and invite the customer to talk with the bank or easily apply for a loan on the bank website. While customers who applied for a loan ten years ago often had to fill out a ream of paperwork and produce the same information multiple times throughout the review process, banks today are able to integrate data sources, eliminating the need to provide duplicate information. Improved data access and integration integrated data sources ultimately helps banks significantly shorten review and loan approval times.
  
  
• Seamless data sharing. Financial data has traditionally lived in silos, but open banking is changing that with APIs. Using APIs, banks make it easier for customers to pull data into the loan application process. For example, APIs can be used to allow small businesses to drop in data from widely used business accounting platforms, such as QuickBooks, into their loan application. This eases the “process burden” on customers and reduces the replication of paperwork and forms traditionally needed to move the loan process forward. Banks can then more quickly verify and approve loan applications and speed up approval and funding times. All of this is critical for banks to win back the lucrative small business market.
  
  APIs can also be used to allow consumers to authorize payments directly from their bank account, instead of relying on a credit card or manual bank transfer. In the B2B space, where many payments still rely on paper checks and take days to process, an API integrated with an ERP or payroll platform allow businesses to issue real-time payments as well as track and confirm the receipt of issued payments. This enables corporate customers to more accurately manage their money and make decisions that are more informed.
  
  
• Cross selling to profitable customers. In retail, customers have come to expect personalized product recommendations and offers in their in-boxes or at the point of sale. Today, consumers have increasingly come to expect this same level of personalization and convenience from their banks. By using machine learning and artificial intelligence to scan a customer’s banks accounts, banks can offer customers relevant products and services. For example, if a bank sees a customer has $100K in savings, they can reach out and offer a few different ways customers can manage that money to help it grow.
  
  For instance, the bank could suggest a meeting with the bank’s investment team, or if they know a customer has children, the bank can suggest moving that money to a 529-education savings account. Similarly, if a bank sees the customer has updated their income, they can reach out congratulating them and offer a higher line of credit on their credit card. These types of suggestions show customers that the bank understands their needs and creates a personalized and customer-centric experience that can set a bank apart from other challengers.

When banks anticipate or respond faster and more accurately to new customer demands, they give consumers fewer reasons to explore new alternatives. By making better use of the wealth of data on hand, banks can better serve customers, fend off competition and increase their profitability.

By Aubrey Hawes, Senior Director of Solutions Consulting Banking, Americas, Oracle Financial Services