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Rethinking the Loan Notice process: The need for AI-powered Loan Notice management

Written by Gil Cross | Jan 28, 2025

As banks’ share of the corporate loan market scales back in response to regulatory pressure and market conditions, alternative forms of lending are rising in popularity. In 2022, the U.S. syndicated loan market reached $5.1 trillion, and in 2024 private credit funding made up 85% of leveraged buyouts, up from 60% in 2019.

 

Alternative forms of lending offer flexibility and efficiency for borrowers, but they exacerbate the burden on loan operations teams. For example, syndicated deals can have as many as 100 to 300 lenders, significantly increasing the complexity of loan notice processing.

To keep up, firms often resort to increasing headcount — but that’s no longer the only solution. Thanks to advances in AI and automation, loan notice management is poised to increase efficiency for operations teams.

Below, we’ll explore how the growth of the private credit market has increased pressure on loan operations teams and how loan notice management can alleviate these challenges.

Loan operations teams face growing challenges — and risks

Historically, loan notice processes have been highly manual. As loan volumes grow, longstanding challenges for operations teams are becoming more acute:

 

High volumes of unstructured data

Agents provide lenders with notices in inconsistent and outdated formats, such as faxes, emails, and PDFs. Notices contain vast amounts of unstructured data, which is much harder to process and utilize than structured data.

 

Variability of loan notice formats

Each agent has its own notice format, which often contains numerous transactions. As a result, general automation and Intelligent Document Processing tools typically struggle to process these notices.

 

Quick turnaround times

Teams must quickly and accurately capture transactions and respond to time-sensitive notices. Delays expose firms to increased risk and potential financial damages.

 

Inaccuracies

Costly errors and inefficiencies often arise due to the heavy manual workload and operational inefficiencies involved. Industry observations indicate a notable portion of loan notices are delivered incorrectly to agent banks, requiring receiving firms to reconcile against their own records, further increasing processing times.

 

Volume spikes

Periodic increases in notice volumes at the end of the month or quarter strain operations teams and can cause backlogs and delays.

 

Many organizations have approached the problem by increasing headcount: McKinsey finds that 65% of financial institutions have turned to offshoring to support loan operations and 38% use third-party service providers. But relying on headcount growth is unsustainable, increasing both costs and complicates managing the process end to end at scale.

And the consequences don’t stop at costs. Manual processing leads to high rates of errors, which in turn leads to cash discrepancies that impact P&L. Slow processing times also impact the front office’s ability to have an accurate and timely view of current P&L and positions.

This highly manual market is ready for change — and industry participants are hungry for solutions. In 2023, Deutsche Bank, Morgan Stanley, U.S. Bancorp, and Wells Fargo invested in Versana, a data platform that aims to centralize corporate loan data from agents. And thanks to advances in AI and data automation, organizations now have scalable alternatives to increasing headcount.

How loan notice management is impacting the industry

Historically, loan operations teams have had few options for digitizing the loan notice process from end to end. Partial automation efforts are expensive and rarely worth the costs as they don’t offer full control over the process. Using generic tools not designed for financial services, such as Microsoft Power Automate, can take years due to complex data and orchestration requirements.

Fortunately, new AI and automation technologies tailored to financial services are making it possible to overcome barriers at each stage of the loan notice process:

Accurate data processing and extraction

Agents share complex transaction details (e.g., borrows, rate adjustments, paydowns interest payments, commitment fees, letters of credit) in emails and PDFs. Typically, employees must manually monitor incoming communications, identify relevant activity, and extract transactions. Accuracy is critical. 

AI makes it possible to efficiently process loan notices, identify anomalies, and extract relevant transaction information — even from complex unstructured documents containing multiple transactions. Purpose-built solutions provide financial services organizations with the control required to ensure accuracy and compliance. Further, with the use of confidence thresholds, a human in the loop review can be added to provide an additional layer of validation when necessary.

Code-free post-processing

Typically, the most challenging part of the loan notice process to automate, the post-processing phase entails referencing the security master to apply accounting rules and prepare system posts, then implement downstream into the end system.

Low-code automation technology makes it possible for operations teams to apply accounting and transformation rules in a non-technical interface. Exception management capabilities can add a human-in-the-loop validation layer to meet relevant regulatory, client, and firm criteria.

Seamless integration with accounting systems

To ensure front offices have an accurate view of P&L, it’s critical for loan notice processing to integrate with accounting systems. But the diversity of accounting engines — with different accounting rules and API interactions — makes it difficult to avoid manual touchpoints between systems.

Advanced automation capabilities enable fast and flexible integration within various systems, eliminating manual touchpoints to provide straight-through processing, while avoiding lengthy and costly IT-driven integration projects.

 

Transforming the loan lifecycle with Xceptor 

The Xceptor platform combines AI and automation, empowering loan operations teams to manage the entire loan lifecycle from end to end. Built to serve the unique needs of the financial services industry, Xceptor provides the flexibility and control required to drive efficiency, accuracy, and compliance.

 

Xceptor enables operations teams to manage the entire loan lifecycle from end to end,
maintaining a comprehensive audit trail throughout.
 

 

With Xceptor, you can:

  • Leverage AI-powered data extraction to automatically and accurately capture and validate transaction details from diverse notice formats, substantially reducing manual processing.
  • Fully automate notice processing from email to accounting system. Xceptor combines powerful data automation and orchestration capabilities with a business and accounting rules engine.
  • Process more notices without additional headcount. Xceptor’s intelligent workflow automation routes exceptions, tracks SLAs, and maintains comprehensive audit trails.
  • Adapt to your specific book of record with flexible system integration that cuts implementation time while maintaining data accuracy.

Experience the power of loan notice management

In the past, the only solution for handling growing loan volumes was headcount. Now, AI and automation offer a scalable solution that can help your organization thrive within the growing alternative lending market.

To learn how Xceptor can transform loan notice processing for your operations teams, reach out today to schedule a demo.