Maximize efficiency: How loan automation can improve your loan origination process

Automation has become the latest industry buzzword, but what does it really mean? How can automation streamline your commercial loan origination process, increase the productivity of your lending officers and make your customers happier?

Introduction

In the current commercial lending market, there are many software applications that serve the loan origination and credit assessment requirements of traditional and non-traditional lenders. Financial institutions are increasingly mindful of improving their practices in these areas to increase efficiency, decision speed, and productivity, all with the goal of enhancing their customer experience.  

Here, we outline the challenges of traditional lending practices and examine each stage of the credit process to see how loan origination automation can improve and standardize underwriting procedures.
 

Understanding the need for loan automation

Commercial lending is about generating economic benefit through enterprise funding while ensuring the lender can make a profit, create shareholder value, and manage risk. However, assessing the creditworthiness of any business can be a challenging task. A financial institution’s tools can impact underwriting standards, timely approval, cost, and the scale of any unpredicted losses. 

Through loan automation (such as an automated loan approval system), financial institutions seek to overcome these challenges, increase the quality of the loan portfolio, and deliver customer satisfaction.
 

Identifying obstacles in the manual loan orgination process

When lenders use manual and paper-based loan approval procedures, they have slower decision times than what many customers want. This also leads to an internal data management problem that creates more work for bankers and causes opacity for both management and external examiners.

It’s true that automation and transformation can seem risky, particularly in a digital world consistently complicated by questions like compliance and data security. However, the reality is that manual work is just as precarious (if not more so), albeit in different ways.

Using a spreadsheet to underwrite credit in any form can be cumbersome. Data entry can be time-consuming and might lose uniformity over time — and, worse, it’s sometimes reentered directly into a lender’s other core systems, doubling effort and creating duplicate records of the same data. From a storage, lineage, retrieval, and portfolio insight perspective, this method has serious flaws.

Figure 1 illustrates a typical commercial lending process. Every banker reading this article can likely recognize the stages and visualize each step in their own organization. Think about each major step in terms of the number of personnel involved, where process bottlenecks appear, which steps are the most challenging, and how long it typically takes for a loan application to move between stages.
 

Simplifying customer management

The first step in any loan decision or new relationship is collecting the necessary information from the prospect or customer. This task can be labor-intensive and difficult to complete. It’s often dominated by form filling, electronic or printed documents, and a physical customer file. The more often the information in these electronic and paper documents is entered and rekeyed into the lender’s systems, the greater the possibility of inaccurate data being recorded.

Automation can mitigate the inconsistency and delays of manually collecting financial data and other mandatory customer information. Customer-facing web-based portals and application program interfaces (APIs) can facilitate the digital onboarding of new prospects and existing customer data straight to the lender’s loan origination platform. After data is received, lender-defined business rules can automate the next step in the process, differentiating between loan applications that are ready for decision and loan applications that require more documentation.

More advanced automated loan origination platforms are also capable of receiving data feeds that pre-populate customer information fields within the origination platform. One of the more useful applications is the import of customer ownership hierarchies. Users can upload organization diagrams, visually depicting the key entities within a group and the inter-relationship between parties, to create the customer ownership hierarchy automatically. For complex borrowers, importing such information can relieve a huge administrative burden.

How many times do bankers rekey information from the CRM system into the credit application after changes to a borrower’s details or ownership structure? Would it be simpler and less error-prone for the CRM system to integrate seamlessly with the loan application system and for data in one system to flow natively into the other? The best loan origination platforms enable this integration with a lender’s CRM.

If a financial institution’s front office and risk department maintain separate records for the same customer, inefficiencies can occur. The latter might restrict access to certain information for compliance reasons, but this duplication often leads to unnecessary inefficiency and inaccuracies. An automated credit origination platform enables multiple teams across departments or locations to access the same customer documents electronically, according to their need and purpose, creating a single source of truth. The application of user identity and access protocols within the system can be effective, maintaining the integrity of the customer information and ensuring only those individuals with the correct privileges gain access information. From an audit and control perspective, this satisfies examination considerably more than open-access file directories.
 

Streamlining credit analysis

One of the most important stages of the commercial risk assessment process is spreading the financial data you have received from your prospect or customer, typically another manual and repetitive task. 

How can automation play a role in helping the credit analyst create accurate financial spreads on which to base risk assessment and lending appetite.

Today’s loan origination software has technology that, with appropriate permissions, allows the lender to interact via a web portal with its commercial customer’s systems. For example, it can extract the relevant financial data required for a credit risk assessment from accounting software, tax returns, and other documents.

The process can occur almost instantaneously and even allow the lender to pre-screen, score the borrower, and provide an in-principle credit decision in a matter of minutes. Similar solutions include Know Your Customer or KYC pre-screening, giving banks a better understanding of each borrower’s risk profile, cash flow position, repayment capacity, and covenants.

Electronic data collection and automated financial spreading give more time back to the analyst to perform risk assessment work. This may include data interpretation, ratio analysis, and forecasting models to gauge the financial risk of the borrower and its capacity to repay the loan. Credit analysis can also include automated risk rating based on probability of default (PD) and loss-given default (LGD) models, tools that instantaneously deliver essential risk metrics for loan assessment.

Moreover, when automated customer management and credit analysis tools are combined in the same origination platform, the benefits compound. One example in the commercial lending environment is the case of borrower groups, where each entity in the group traditionally has to have its own financial statements assessed individually to have a risk rating assigned. Where the lender’s policy allows, an automated loan origination platform can save considerable time in the rating process by applying instantaneous group ratings based on the consolidated financial strength of the lead borrower and the application of cascaded or distributed ratings from the parent entity.
 

Improving credit presentation & decisioning in underwriting

An automated loan approval system is about mining the appropriate data and information and presenting it clearly to make a commercial credit decision. Automating your lending process from start to finish captures the benefits of accuracy, near real-time data, increased efficiency, and reduced decision times.

After gathering information on your customer or prospect, spreading the financial statements, running the ratio analysis, performing some projected scenarios, and undertaking a risk rating, most bankers have a good idea of what their lending appetite looks like. Assuming it’s positive, the next step is to prepare a credit presentation, or application, for decisioning by the risk department.

For many lenders, the credit application represents another manual exercise in preparing and collating several separate, yet related, pieces of paper, often in a highly prescribed fashion. This adds to the processing time for approval, especially for a new relationship.

An automated credit application solution combines the previously discussed elements of the customer management module, financial analysis, and risk assessment with some form of loan structuring tool, collateral management system, and electronic credit memorandum. An automated credit application doesn’t need to be as complex as it sounds. Best-in-class origination platforms also integrate with existing systems or applications the lender already has in place for these functions.

In today’s banking software landscape, there are applications that package all the stages together for credit approval. However, by using the data and information already stored in the origination platform, the system can automatically produce pre-configured document templates mirroring a lender’s paper-based credit forms.

The final step, the decision to approve or decline the loan, has also been reimagined by software vendors. In the world of commercial lending, two loans are never the same. At the high-volume/low-loan value end of the spectrum, it’s possible to see auto-decisioning based on the particular policies and business rules of the lender. In the retail credit environment, automatic decision-making is already commonplace.

Automation plays a significant role in pre-screening applications and assisting loan officers in assessing risk and preparing proposals for decision-makers. Mobile enablement, in particular, is increasingly used in the decision-making step. Lenders of all sizes are arming their executives with laptops, smartphones, and tablet devices fully loaded with applications enabling them to make lending decisions while on the move, once again driving down the time to approval.
 

Strengthening covenants/monitoring

After the loan origination process, the asset itself still has to be managed, and the risk monitored annually, quarterly, or even monthly. One of the major challenges banks face is to identify a standardized process for collecting financial data to satisfy ticklers, covenants, and policy exceptions. Tracking can be inefficient, not to mention risky, with poorly defined manual processes. Moody’s has seen mid-tier lenders still using spreadsheets to track portfolios containing several thousand loan covenants. Examiners distrust such methods and often demand that a more robust solution be implemented.

Automated covenant solutions can exist outside of an origination system, but for data accuracy, efficiency, and effectiveness, they are better as part of the overall solution. Recording the required covenants as part of the loan application process saves rekeying and anchors the details of the covenant to the approval record for audit purposes.

An automated covenant/tickler feature provides peace of mind that the correct information can be collected in a timely manner through an in-built calendar alert. Automated notifications go out if the appropriate documentation isn’t collected or if various covenants aren’t met. Automated testing can also be applied so an immediate or impending breach is red-flagged via dashboard alerts when the data enters the system.
 

Enhancing portfolio risk management

With traditional manual, paper-based loan underwriting methods, lenders often struggle to see what exposures are in the portfolio and how these exposures change over time. All lenders have stated risk appetite tolerances and most set appropriate risk-based portfolio limits to guide their loan officers. However, formulating these rules is an academic exercise, unless the lender has an accurate portfolio reporting tool at hand.

A powerful rationale for loan origination automation rests with the improved data integrity, data lineage, and overall governance that come with a best-in-class origination platform. We’ve already discussed how data integrity is compromised when several systems are used to store the same data. The amount of keying and rekeying is multiplied, and data is stored in sub-optimal systems. When conditions such as this exist, lenders spend considerable time and resources reconciling their portfolio data before they can usefully analyze it. Several weeks can elapse before an accurate picture emerges, by which time it might be too late and costly to address a particular issue or problem.

The cost benefits attributable to the accurate measurement of a loan portfolio in terms of capital usage must not be underestimated. Overstating risk-weighted assets on your balance sheet has a substantial direct cost. We are aware of at least one large European bank that gained capital savings of several hundred million dollars after undertaking a major portfolio data cleansing project. However, the real lesson is not to allow things to get to that stage.

Automating key stages of the loan origination process helps ensure that risk data is subject to robust governance and control. Further automating, to deliver key business insights through a powerful business reporting tool can add significant value as well.
 

Conclusion

Automation has increased the efficiency of numerous industries worldwide. Banking was, in many ways, an innovation pioneer; however, the business of originating small business and commercial loans can always progress as technology does.

The landscape for commercial lending is now changing. Spurred on by the emergence of more technology-enabled competitors, many traditional lenders are adopting automation methods in their loan origination processes —but competition is far from the only impetus. Lenders that recognize a need to be more efficient, productive, and responsive to their customers, with higher levels of service, also look to implement technological solutions. Cost savings and requirements also drive these lenders to meet more stringent regulatory exam standards. Others are motivated by the ability to take back control of their data and gain sharper, more accurate business insights.

We find few, if any, lenders are prompted to apply automation as a way to reduce human intelligence in the commercial lending arena. Rather, most see it as an enabler to retain talent and engage bankers’ time on things that matter, such as risk analysis and customer relationship management, instead of administration.

Finally, while automating loan underwriting procedures can present some challenges, doing so can enhance the brand of the institution as an innovator and market leader among peers.