Amid bullish bank stock prices, actual C&I loan portfolio growth has been an elusive goal for many mid-size banks in recent years. Is automation a missing link to a more productive and profitable commercial lending department?
The 2015 Cornerstone Performance Report found significant reductions among mid-size banks in both monthly loans originated and outstandings per commercial lending full-time equivalent employee. According to the report, this challenged growth is forcing many banks to reassess their commercial origination, fulfillment and servicing processes. The plain fact is that the crisis of 2008 made the credit process swing too far into paper-based bureaucracy. It’s time to crack a better commercial lending code using digital technology.
A McKinsey study found that as much as 45% of activities performed by individuals in the workplace can be automated using “digital automation” technologies—translating to about $2 trillion in annual wages in the United States alone. Traditional commercial lenders may not believe that digital automation (DA) can be applied to their world because of the “art” they undertake when it comes to detailed underwriting analysis and loan structuring. These traditional bankers are becoming more wrong each year.
Digital automation, sometimes called robotic process automation or digitalization, is becoming more powerful in helping banks automate manual, repetitive processes that have traditionally been performed by credit analysts, loan assistants, appraisers and loan operations staff. So far, bankers’ attempts to automate commercial lending processes have focused on improving loan origination/servicing workflows and implementing customer portals. However, workflow tools only provide marginal efficiency gains because lending staff still perform numerous manual tasks and many commercial borrowers have abandoned usage of portals because they can’t easily navigate to view their loan status, perform flexible self-service and expedite their loan closing.
Commercial lending processes, by nature highly manual and labor intensive, present a host of automation opportunities beyond traditional loan origination workflow rules. The benefits of commercial lending DA are numerous and include:
DA opportunities can broadly be classified into three primary categories:
1. Basic automation, where routine, repetitive functions can be automated via workflow tools and decision engines (macro-based applets, optical character reader [OCR] data collection, workflow automation, self-executing process mapping, etc.)
2. Enhanced automation, where built-in knowledge repositories, learning capabilities and other methods are leveraged to further automate distinct functions/processes beyond that capable in basic automation (built-in knowledge repositories, learning capabilities, use of unstructured data, pattern recognition, etc.)
3. Cognitive automation, where the use of artificial intelligence (AI) and self-learning capabilities are leveraged to create the highest level of automation possible (AI, use of super data sets, natural language recognition, predictive analytics, evidenced-based learning, etc.)
There are many commercial lending tasks that innovative Gonzobankers are beginning to implement that will change the game in commercial lending productivity. For example:
Marketing analytics aimed at identifying potential commercial credit request needs.
Public information on geography, NAICS, revenues and collateral filings can be leveraged to greatly focus marketing efforts. Existing customer data (DDA balances, business credit card and other revolving/term debt availability and utilization, and trade finance and treasury product usage) can be supplemented with purchased data to feed basic algorithms that can identify and prioritize prospective and existing client credit needs.
Financial “spreading” of borrower financial statements.
Most institutions still spread financial statements via manual data entry into a financial spreading software—this despite OCR and document ingestion capabilities that allow scanned financial statements to be imported into spreading platforms. Some loan origination system (LOS) vendors provide for OCR and document ingestion automation, while others provide for the import of data from accounting platforms such as QuickBooks. Rules-based logic can classify this data into a desired format, with the resulting file imported into a spreading system, with only a cursory review required for validation.
Validation of required and received credit due diligence items and vendor order execution.
An LOS often permits the creation of user configurable rule logic that can generate the specific pre-decision and/or pre-closing due diligence items required to be satisfied before a credit request can be evaluated or loan documents prepared. However, many require manual effort to trigger the ordering of flood, property and UCC searches, good standing certs, appraisals/equipment valuations, etc., in addition to user evaluation to confirm when such items have been received and evaluated. The use of knowledge repositories, pattern recognition and unstructured data processing to automate vendor ordering, status assessment and evaluation are all achievable DA tasks.
Generate credit underwriting recommendation/decision.
Most LOS provide for configurable rule logic permitting automated credit recommendations and/or decision rendering. Although automated decision rendering is still predominantly used in consumer lending, larger FIs have been using automated decisioning in small business lending for years. Cognitive automation can expand the power of automated decisioning, notably on annual renewals/reviews, using AI, super data sets, predictive analytics and evidence-based learning.
Early problem loan identification.
DA automation, using super data sets, analytics and AI, among other methods, can connect borrower behaviors and economic variables to identify red flags for potential loans. Examples are increased overdraft frequency/amounts/patterns, new/increased credit utilization, past due financial reporting, and significant score changes, among numerous others. Most FIs have barely scratched the surface of using predictive, proactive processes for early problem detection.
Although largely still in its infancy, digital automation is gaining industry momentum and already generating tremendous benefits for financial service firms. Make no mistake, the “art” form that commercial lenders practice will be further automated each year and the best credit officers will thrive in a more productive environment. Banks that enact material and fundamental change to the commercial lending processes can realize significant gains in both efficiency and, more importantly, portfolio growth.
In the past, commercial lenders viewed digital technology as the realm of the mortgage or consumer lender, or maybe the tiniest small business loans. Those days are over, and banks that ignore DA’s transformational opportunities will begin to lag the origination and portfolio benchmarks of the Gonzobankers that forged a new commercial banking path. Isn’t it time to embrace the possible?