Digital Banking Disruption

Banks can no longer simply provide transaction-based payments and cash management services.

With a continued squeeze on margins, banks will need to build strong relationships with their commercial customers, streamline processes with an emphasis on cost reduction and efficiency, and increase cross-sell opportunities.

Relationship managers, underwriters, and portfolio managers spend more than 40% of their time on “noncore” administrative, repetitive, and automatable tasks.

But there are challenges in getting from a transaction-based informational model to one that uses data to create digital experiences. 

THE CHALLENGES

1. The customer relationship management (CRM) systems banks use for their commercial franchise don’t provide the insights and intelligence that commercial bankers can use to offer proactive guidance and consultative advice.

2. Commercial banking relies heavily on manual processes that force employees to spend too much time on repetitive activities for complex tasks, such as Know Your Customer (KYC) and anti-money laundering (AML) compliance.

3. Most banks are hampered by highly siloed business units, such as treasury, trade, and lending, and the unintegrated fragmented systems that support those business modules. And the bank systems they offer customers emphasize these siloes.

4. Finally, legacy core systems that are 20 years old — or more — lack a modern front-end interface, and many core providers fail to invest adequately in their front-end user experience.

Intelligent engagement enables banks to deliver a unified customer experience to deepen their relationships with business customers and help them make smarter business decisions. Simply put, it enables banks to more intelligently engage with their business customers.

Forward-thinking banks are implementing intelligent engagement via digital engagement platforms. This offers several benefits: They’re intuitive and easy-to-use, with an interface that presents information to both customers and bankers in a compelling yet straightforward manner. And just as important, they facilitate collaboration and engagement between the banker and the customer.

For banks that partner with the right technology partner, intelligent engagement is easy to implement and supports rapid innovation.

Unlike a wholesale rip and replace of legacy systems, the right platform will integrate with existing core systems via application programming interfaces (APIs). These APIs allow banks to offer innovative solutions to commercial clients, whether the banks develop these solutions in-house or partner with fintech firms that offer niche products and a faster time to market. Banks can then bundle these products and services and position themselves for future innovation.

Intelligent automation relies on the cloud to provide quick provisioning, agility, scalability and lower total cost of ownership. Predictive and deep analytics tools use structured and unstructured data to anticipate customer behaviors, predict their next step, and recommend products and services that meet those needs.

Driven in part by the Payment Services Directive (PSD2) and General Data Protection Regulation (GDPR), banks are starting to embrace the power of open data. Long advantaged by having access to customer data, open banking can level the playing field for fintechs and non-traditional financial institutions by providing access to customer data to other players.

But open banking will also offer an opportunity as banks will now have access to data from those same fintechs and non-traditional financial institutions.

Banks can leverage that data to provide intelligence and a greater value proposition to business customers. For example, PSD2 is ushering in innovations, such as peer-to-peer commercial payments and aggregated accounts. In an open system — and employing intelligent engagement — a bank that processes a vendor payment would be able to review the original invoice and recognize that the payment was for 1,000 units. With access to the customer’s enterprise resource planning (ERP) system, the bank could now offer to help the business with monitoring and managing inventory. The more data and intelligence the bank collects, the more services, recommendations, and solutions it can offer to help the business.

Another driver for reimagining commercial banking is faster payments systems, such as the RTP® network from The Clearing House in the U.S., SEPA Instant Credit Transfer in the EU, and New Payments Platform (NPP) in Australia.

Retail banking continues to adopt real-time payments for consumers and commercial customers have the same expectations. For commercial customers, the benefits of faster payments include lower processing costs and increased transparency.

New approaches to digitizing supplier payments and automated payables solutions from fintech firms — many targeting small and mid-sized businesses — and an increase in the demand for cross-border payments are also driving an interest in reimagining commercial banking.

Cash management:

Intelligent engagement uses data for insights that deepen the customer relationship and help business customers feel smarter about their business and financial scenario. Customers understand their performance relative to their peer group and use that comparison to improve cash flow.

Streamline commercial lending:

Intelligent engagement leverages optical character recognition and robotic process automation to extract data from structured and unstructured loan documents that were previously entered manually into account opening and loan origination systems.

Managing false positives is typically a manual process. Using intelligent automation, banks can extract names, companies, and other entities in client documents and automate the entry of that data into sanction-screening systems to save time and improve accuracy.

Since it tends to be such a labor-intensive process, businesses only reconcile a small percentage of invoices and purchase orders. Intelligent automation can identify invoice and purchase order formats, extract data, and automatically enter that data into the accounting system.

Payments investigation and resolution:

Intelligent automation identifies common payment issues, automatically fixing missing or incorrect information and managing issues, such as payment recalls and exchange rate discrepancies.