Real-time banking is here, and adoption is a matter of survival. Here is how real-time banking is transforming common transactions, plus five keys to understanding how to compete and win in this changing environment.
In October 2004, Check 21 came into effect, enabling banks to exchange check images instead of physically moving checks through the banking system. While it took nearly a decade for the industry to transition fully, one unexpected byproduct of image exchange quickly upended business banking: remote deposit capture. With the earliest deployments, banks soon realized that RDC could collapse distance. A bank on the west coast could accept deposits on the east coast—and anywhere in between. An arms race broke out among banks of all sizes to retain existing business customers while taking them away from banks that moved too slowly.
Today, a new arms race has broken out in banking, but instead of collapsing distance, emerging technology is collapsing time itself. Real-time banking began by providing immediate access to account information and transaction history through online and mobile banking. But today it is transforming transactions, including high-risk ones such as person-to-person payments, new account openings, and both consumer and business lending.
There is a common thread to this shift: Even the simplest banking transactions are conducted without certainty, but with acceptable levels of conviction. For example, is the currency being deposited counterfeit? Is the mobile-deposited check legitimate? Is this truly the ID of the person opening the account? Whether in the branch or on a mobile app, banks ultimately rely on well-defined levels of conviction to complete transactions. While several emerging technologies are being leveraged to achieve conviction in real-time, chief among them is data science.
In simple terms, data science takes advantage of the explosion of information available about people and businesses, and combines it with ever-more sophisticated decisioning to close the gap between uncertainty and conviction. To get to real-time, much of the data collection and decisioning happens well in advance of a transaction. It only “feels” real-time to the customer since the bulk of the work happened before the customer even contemplated a transaction.
Consider Zelle, where most P2P transactions are funded in minutes. Critical to its functioning is the risk mitigation based on bank customer data coming from its parent company, Early Warning Systems, and partner banks. Combined with other information, Zelle is constantly sifting and scoring tens-of-millions of accounts. This does not eliminate all bad transactions, but when a customer attempts a payment, the system immediately has enough conviction to authorize the transaction—or not.
Real-time lending also requires sophisticated data science. While transactions such as payments and account openings are binary and require a simple “yes” or “no” to complete, lending is multi-dimensional; in addition to a yes/no, the decision includes how much to lend and at what interest rate. Also, like Zelle, data is collected and decisioned—essentially underwriting loans—in anticipation of an application. If and when the consumer or business applies for a loan, much of the work has already been done; customers need only answer a handful of questions—and often receive a decision in seconds.
When contemplating how your bank will compete and win in a real-time world, consider these keys to understanding and evaluating potential solutions:
(1) Know that these systems work the way banks have always worked—by mitigating risk to a reasonable level of conviction. (2) Keep in mind that the critical enabler of real-time banking is more information and the ability to process it—at a much greater level than can be accomplished in manually. (3) In addition to having more information and more speed, these systems apply rules and make decisions more consistently than bank staff. (4) Because of this, managers ultimately have greater control over policy and risk management. (5) Remember that the bulk of data analysis and decisioning happens prior to customer contact—often before the customer even contemplates a transaction; while it “feels” real-time to the customer, it is the upfront work that reduces fraud and other transaction risks.
Some believe that we are in the early stages of real-time banking. These banks have adopted a wait-and-see attitude. But as real-time banking is applied to ever-more complex financial transactions, can any bank truly afford to wait?
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