If the COVID-19 pandemic has taught banks anything, it is that technology can make or break revenue strategies. The banks who pursued the right digital transformation path have fared better than those who hesitated. The race to recover from the COVID-19 pandemic and conquer the current environment isn’t over and business shifts will continue.

Two of the primary trends making a significant impact in the commercial lending space right now are not newcomers but are expected to gather more attention and importance in coming years: cognitive computing and automation strategies.

Both trends are fully embedded in the modern concept of “digital transformation.” Digital transformation is about converting non-digital or manual processes to digital or technology-served processes and replacing or optimizing “legacy” hardware or software with newer technology. The objective of such changes is to improve business performance and competitiveness via efficiencies and business intelligence.

In 2021 and on, there will be increased emphasis on digital business lending as a way to boost new business. It will be expressed through innovative customer experience and staff efficiencies all along the loan cycle, including origination, underwriting and servicing.

Unlocking Your Data

We’ll start with data since no innovation will serve a financial institution well if it doesn’t have great data.

We all know that data is a critical asset, but various hurdles, such as disparate document formats and types, have made it difficult to uniformly unlock documents. Newer tools such as optical character recognition (OCR), have recently gotten much better about translating unstructured data such as images of invoices and purchase orders into a digitally readable format. By the same token, moving structured data directly between applications, such as from a bank system to a loan servicing system rather than via document uploads, is a faster and more accurate way of putting data to work.

A lender that can quickly ingest customer information regardless of its initial format will win. Period. Right now, it can take hours, if not days, for a staff to extract information from a customer’s financial statements, invoices, agings and bank statements for underwriting and loan servicing purposes. Lenders that do not fix this inexcusable technological data gap will not be competitive.

The potential for reducing the time it takes to get a credit decision is staggering. But like any journey, it begins with a first step. Start by identifying data within your company that, if unlocked, can be transformed into actionable insights. Once the data is unlocked and easily available, an entire world of opportunity awaits at each step of the loan process, as lenders can:

• Personalize marketing offers and streamline initial approvals to revive originations
• Make smarter credit decisions faster for better underwriting performance
• Improve analytical impact through predictive modeling and risk management trends to enhance loan servicing profit and production.

Experiment with Data

Artificial intelligence has become a business banking reality, as cloud computing power becomes equal to the massive pool of increasingly accessible data. New data-centric AI tools are now available to financial institution managers, helping them generate their own models rather than having a tech team build them from scratch. Consider the recent IPO of C3 AI, a company that is delivering an AI platform to accelerate digital transformation with “no-code AI.” There are many other AI tools helping different domains solve problems or provide actionable insights exponentially faster than before.

In the past, banking insights were mainly focused on historical data and predictive analysis based on rudimentary business rules. These insights could describe what happened and make a guess about what would happen if little about the data changed. But new data technology allows banks the opportunity to shift into more intelligent problem-solving with what data scientists called “prescriptive analytics.” Technology has finally caught up to the business need. Analytics that historically were available only to economists and data scientists are now within reach for lending subject matter experts. Using modern business intelligence tools, managers — people trained in the business of making money, not analyzing data — can make intelligent suggestions about how to do business better by assuming certain variables.

For example, rather than digging through files, a loan officer could use a chat bot on their phone or computer to query company data in milliseconds using simple questions like, “What is my debtor concentration level for Acme Manufacturing across my entire portfolio?” or “What will the dilution factor look like over the next 12 months?” The wherewithal for this intelligent insight is here. The tools to make it possible are also here. “Now” is a good time to start investigating this area of data intelligence and to begin experimenting with data. Not doing so raises the risk of falling behind the opportunity and value curve as well as the emerging competition that has every incentive to do it first.

The people who understand a business best can use modern business intelligence tools to prescribe outcomes for the bank or its loan customer. What a market advantage this will bring to the banks that adopt it!

Finding Automation Opportunities

Improving the speed and accuracy of processes and decisions will continue to be a competitive advantage for financial institutions. Fortunately, there continue to be huge technological advancements that make it easier to add intelligent automation in areas once considered too difficult to achieve.

It is now possible to integrate multiple systems for full automation. For example, you can pull cash balances directly from financial institutions, aging reports directly from accounting systems and payment information from e-commerce sites, all in real time. Such capability allows commercial lenders to have and hold a clear picture of customers’ credit qualification to make intelligent loan advance recommendations in a matter of minutes. Software platforms that offer connectivity via Web Services REST APIs typically enable this real-time data exchange for seamless data communication. Banks, like manufacturers, that find ways to automate elements of their financial acumen will dramatically improve revenue.

Most commercial lenders can immediately think of routines they would love to automate. Consider some common scenarios:

• Exchanging data automatically between a CRM and loan servicing software for instant snapshots of customers’ monthly availability
• Gathering borrower profile information from e-commerce sites like Shopify or raw material information from specialized inventory systems
• Pushing financial data directly from customers’ standard accounting systems into underwriting systems for credit analysis

Opportunities for automation are hiding in plain site as manual data entry or import routines. Closing these manual gaps will allow banks to fully embrace digital transformation and gain several steps on competitors.

Be in Front of Trends

The market almost always rewards lenders who exceed expectations. These days, that translates to more than access to money. It requires flexibility and speed in communication and decision-making.

The new generation of borrowers expect aspects of their loan process to be fast and friction-free. A bank with established data and automation capabilities will present a much more favorable experience to these customers. More than that, these banks will be proactive about managing risk and opportunity.

Banks have (at least) three big incentives to quickly adopt technology suited to their workflow:

• Defend and protect lending opportunity: The next generation of borrowers have grown up with mobile- and web-savvy applications (products) that are convenient and fast. These customers will expect the same level of experience with financial products. A bank without great data automation will fail to deliver at scale.
• Improve back-office and customer-facing efficiency: New technology, particularly with respect to data collection and process automation, is very well-suited to financial organizations and their portfolio management.
• Improve risk protection and reward manageability: A fantastic opportunity for strategic insight and market-beating tactics will come with the greater efficiency of data through collection, monitoring and analysis.

Obstacles to change are rarely technological, rather, they are human-made. It takes a person some time to get comfortable with using technology to automate a procedure historically dominated by humans. This is not a bad thing. Banking is people helping people, after all, which is why consumer lenders under greater pressure from customers may be further along in the digital transformation journey.

Commercial lender that find a way to put and keep people in front of people while having IT assets handle data-driven work will strike the right balance. They will exceed customer expectations and maximize market opportunity. By so doing, they will react to market conditions with greater effect. They will manage risk better. The commercial lenders that thrive will be those that find good ways to get more value out of data flows by automating them.

Nancy Lee is CEO of ABLSoft, an asset-based lending fintech company. Lee is a more than 20-year veteran in enterprise software and commercial lending technology. She can be reached at 866-632-7146 or [email protected].