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5 Common lending challenges and how lending software can help

Abrigo
April 22, 2026
0 min read

Leveraging AI-powered software to gain efficiency

Banks and credit unions that leverage an integrated lending and credit platform reap the benefits of a consistent, efficient, and defensible lending program. Today, many institutions are also exploring how artificial intelligence (AI) can enhance these efforts by improving insights, reducing manual work, and supporting more informed decision-making.

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An integrated, AI-enhanced lending and credit system can help overcome many roadblocks to a streamlined lending program. Below is a short list of the most important features you should look for in researching lending and credit software.

1. Improving transparency into business development.

Lenders track outstanding opportunities and sales activities in spreadsheets, calendars, and notebooks at most institutions. However, it’s challenging for management to measure progress or build predictable forecasts without a centralized system.

An integrated solution provides lenders with a contact database using customer information from the core. It also creates a central location for logging conversations. The increased transparency of an integrated relationship system allows the institution to serve customers better. Management can also hold lenders accountable for achieving their activity goals.

Modern lending and credit software features can also incorporate AI to analyze activity trends, helping identify high-potential opportunities and providing additional visibility into pipeline health.

2. Optimizing the loan origination process.

For many financial institutions, the process of taking a loan from application to closing can take months. It involves numerous bank employees, including business development officers, analysts, credit committee members, loan administrators and outside closing agents. As the prospective loan advances from stage to stage, bottlenecks are common:

  • Back and forth with the borrower for required financial documents
  • Unbalanced credit analyst workload
  • Unresponsive third parties
  • Unclear loan-decisioning rules that require added discussion
  • Delay as the credit file is passed between parties
  • Hunting down the credit file when the bank must report to the borrower on progress

Without a systematic and comprehensive method, consistency and speed are impossible. Loan application software can speed up the process by creating a digital experience that makes document management and processing easier. Coupled with enhanced workflows and automation on the back end, institutions can turn around applications more quickly.

Some lending and credit software features now use AI to extract data from financial documents, highlight missing information, and support more consistent credit analysis. These capabilities help reduce manual effort while supporting lenders’ expertise. By removing the burden of managing daily activities, the management team can focus more on strategic decisions.

3. Tracking outstanding post-closing documents.

This stage of loan management starts immediately after loan closure and includes trailing critical documents. Absent a systematic, proactive process for identifying and tracking outstanding documents, the potential for documents “falling through the cracks” dramatically increases. This can lead to higher institutional risk concerning proper lien perfection, inadequately insured collateral, and regulatory scrutiny.

On the surface, documentation exceptions for loan tracking may seem minor or less critical than underwriting policy exceptions; however, that may not always be the case. The OCC Comptroller’s Handbook on Loan Portfolio Management indicates that this situation can worsen problem loans. It can also greatly hinder efforts to resolve these issues. An automated, centralized system that creates ticklers and exception reports is invaluable. This workflow helps identify patterns that may indicate a weak closing agent or a branch that needs better documentation compliance. Enhanced lending and credit software features can also use AI to identify trends in documentation exceptions and flag higher-risk gaps earlier, helping institutions address issues before they escalate.

4. Collecting current financial information for annual reviews.

According to the Federal Reserve Bank of Atlanta, an effective loan review system should, at a minimum, promptly identify loans with potential credit weaknesses, identify trends affecting the collectability of the portfolio and assign risk grades based on quantitative data.

To conduct a periodic review of commercial borrowing relationships, the institution must have current business and personal financial information. The collection process can be improved with software that defines responsibilities, tracks activities, and logs receipt dates.

A borrower’s failure to provide updated financial information may suggest they are facing financial issues. Quickly identifying borrowers with overdue documents can act as an early warning sign. Some lending and credit software features now incorporate AI-driven insights that help analyze financial trends and surface potential risk indicators earlier in the review process, supporting more proactive portfolio management.

5. Transfer of watch-list credits to special servicing.

Upon certain specified events, primarily a default or breach of covenant, the administration of a loan should be transferred from the banker to special servicing. For example, suppose the loan or relationship has been classified at or above a specific, defined risk level. In that case, the loan file, including collateral and credit documents, will be passed on to the special assets group. This process raises a few procedural questions:

  • Will the banker meet with the Special Assets Department to communicate the customer’s financial situation?
  • Should Loan Administration consider updating ticklers for financial data to quarterly or monthly instead of annually? Will new covenants be agreed upon and monitored?
  • Is a new appraisal being ordered?
  • Has the loan been evaluated for impairment?
  • Has Special Servicing developed its loss mitigation strategy?

An end-to-end solution can tackle these important questions by following a series of clear steps and approvals. It includes role-based routing and related transfers. AI capabilities within lending and credit software features can further support this process by monitoring portfolio data for risk triggers and helping institutions identify when a loan may require additional attention. In other words, the advantages of an automated process extend beyond underwriting and servicing.

About the Author

Abrigo

Abrigo enables U.S. financial institutions to support their communities through technology that fights financial crime, grows loans and deposits, and optimizes risk. Abrigo’s platform centralizes the institution’s data, creates a digital user experience, ensures compliance, and delivers efficiency for scale and profitable growth. Make Big Things Happen.

Full Bio

About Abrigo

Abrigo enables U.S. financial institutions to support their communities through technology that fights financial crime, grows loans and deposits, and optimizes risk. Abrigo's platform centralizes the institution's data, creates a digital user experience, ensures compliance, and delivers efficiency for scale and profitable growth.

Make Big Things Happen.