Introducing Bectran Intelligence Lab — AI tools for credit, risk, and collections.
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As their operations scaled and the volume of credit applications and transactions surged, the limitations of their existing order-to-cash system began to show. Thousands of credit applications arrived each month alongside growing volumes of job sheets and frequent order holds. Their credit application and job sheet workflows — while thorough and service-oriented — were highly manual, creating friction and holding back growth.
In their collection efforts, SRS struggled to maintain consistent contact with the thousands of small accounts under their service umbrella. They needed a solution that kept risk under control while letting new business move forward — one that gave large accounts the attention they required without slowing the handling of smaller ones.
Bectran partnered with SRS Distribution to support their order-to-cash foundation. Together, the teams tailored the system to mirror how SRS does business — from credit and job applications through evaluation, approval, and collections outreach.
Bectran introduced dynamic credit applications and automated job workflows that reduced the manual work behind approvals while integrating seamlessly with existing ERP systems, ensuring data consistency across all departments and business units.
To enable SRS to reach all customers for collections without overextending their team, Bectran implemented advanced dunning automation and risk scoring capabilities. This allowed SRS to prioritize outreach, maintain consistent communication, and manage collections for thousands of small accounts more effectively — without compromising service quality.
What started as an efficiency initiative quickly became a strategic advantage that reached well beyond faster approvals. With Bectran, SRS gained a single, connected view of its credit, collections, and AR operations. The sales team noticed it first: customers were onboarded faster, with fewer holds.
Finance followed, reporting steadier cash flow and cleaner portfolios. In the months since implementation, application approval times fell from an average of 6–7 days to just under 2 days, with some approvals completed in as little as 30 seconds.
Across portfolios, intelligent scoring cut each collector's account load by more than 80 percent and helped the team prioritize the customers that needed direct attention.
