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Billtrust Launches Agentic Credit Lines to Help Finance Teams Proactively Defend Against Credit Risk

AI-powered credit insights improve risk management and help teams unlock capital sooner.
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HAMILTON TOWNSHIP, NJ – March 3, 2026 – Billtrust, the leader in B2B accounts receivable (AR) workflow and payment software, today announced the availability of Agentic Credit Lines, a new AI‑powered capability that helps finance teams proactively identify payment risk and make faster, more confident credit decisions.

Agentic Credit Lines, embedded in the Billtrust Credit Review workflow, analyzes payment history, utilization patterns, and external credit data using Billtrust’s proprietary network of 13 million buyers and 25 years of B2B payment intelligence. It delivers prioritized account reviews and clear, audit‑ready credit limit recommendations with transparent rationale, giving finance teams greater visibility, stronger portfolio control, and earlier detection of emerging risks.

Credit management has traditionally relied on static rules and manual reviews, leaving organizations vulnerable to late payments, unmanaged credit limits, and avoidable bad debt. For AR teams, the impact is clear: rising DSO, worsening aging buckets, and quietly eroding working capital, often before any warning signs appear. As AI reshapes financial operations, finance leaders need tools that enhance, rather than replace, human judgment, and Agentic Credit Lines delivers with transparent, data‑driven recommendations that let teams act quickly while maintaining full oversight and compliance.

Proactive Intelligence for Modern Credit Management

Agentic Credit Lines represents a major advancement in Billtrust’s credit management capabilities, moving beyond rule-based automation to predictive, AI-driven insight. It analyzes 12 months of payment history, utilization, overdue balances, dispute trends, and external ratings to generate a risk score for every buyer, including those with missing or inaccurate credit limits. Monitoring more than 80 data points in real time, it only surfaces signals that indicate meaningful risk or opportunity.

These insights draw on the Billtrust Business Directory, a continuously updated repository of real B2B payment behavior, which ensures models are built specifically for credit workflows instead of relying on generic AI adapted for AR. Unlike manual reviews that focus on the top 20% of high-risk customers, it continuously scans the full portfolio and flags accounts that cross configurable thresholds, offering recommendations prioritized by urgency and impact.

This proactive approach helps finance teams address the visibility, efficiency, and risk management challenges that matter most to AR leaders and CFOs:

  • Identifying payment issues before they occur
  • Preventing unmanaged exposure across the entire buyer portfolio
  • Reducing manual review effort and focusing on the right accounts
  • Ensuring compliance with transparent, auditable rationale
  • Unlocking revenue by increasing limits for reliable payers
  • Improving working capital efficiency by acting on risk before it registers in DSO

“It’s time to stop reacting to risk and start getting ahead of it with technology that elevates human judgment instead of replacing it,” said Lee An Schommer, Chief Product Officer at Billtrust. “Agentic Credit Lines represents the next step in our evolution from workflow automation to intelligent engagement. The depth of payment data and buyer intelligence we’ve built over decades is what makes this possible – and what makes it different from anything else on the market. Finance leaders finally have the visibility to prevent risk before it affects cash flow. It’s a powerful example of how AI can strengthen financial resilience across the entire AR lifecycle.”

Key Features of Agentic Credit Lines

  • Predictive Credit Recommendations: AI-driven directional guidance increases or decreases credit limits based on payment behavior, utilization, and external risk indicators.
  • Transparent Rationale: Every recommendation includes clear, auditable reasoning to support compliance and governance.
  • Human‑in‑the‑Loop: AI works alongside existing manual and rule‑based reviews, ensuring teams maintain full control.
  • Portfolio‑Wide Visibility: Reviews all buyers, including those with no credit limit, to identify unmanaged exposure or potential opportunities for additional revenue.
  • Prioritized Reviews: Flags accounts that breach risk thresholds and ranks them by urgency and potential impact.
  • Seamless Workflow Integration: Recommendations appear directly in the existing Credit Review window for immediate action.

Agentic Credit Lines is the latest addition to Billtrust’s end-to-end AR platform, expanding the suite of intelligent Collections capabilities including Agentic VoIP and Agentic Procedures. Together, these innovations help finance teams reduce manual work, improve visibility, and make smarter, faster decisions across the full AR lifecycle. Powered by Billtrust’s multi‑agent infrastructure, these capabilities use specialized AI agents that collaborate across workflows to deliver deeper, context‑aware insights informed by the same payment data and buyer intelligence that underpins every Billtrust product. Built on a trust‑first architecture that never trains underlying models on customer data and maintains strict human‑in‑the‑loop controls, the system preserves data isolation while still learning at the workflow level through safe feedback loops that enhance accuracy without compromising privacy.

About Billtrust

Finance leaders choose Billtrust to get paid faster, control costs, and maximize customer satisfaction. As a B2B accounts receivable workflow and payment software market leader, we provide the world’s leading brands with AI-powered solutions to delight their buyers across the full AR lifecycle—from invoice presentment to payment application. With more than $1 trillion invoice dollars processed, Billtrust delivers business value through deep industry expertise and a culture relentlessly focused on meaningful customer outcomes.

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