What is FinFloh?
FinFloh revolutionizes accounts receivable management through advanced AI and machine learning capabilities. The platform seamlessly integrates with existing ERP/CRM systems to automate invoice creation, collections, dispute resolution, and cash application processes. Its intelligent system leverages ML-driven credit scoring and predictive analytics to enhance decision-making accuracy and reduce payment delays.
The solution offers comprehensive features including automated collection workflows, centralized buyer-seller communication, ML-based OCR engine for payment processing, and AI-driven credit suggestions. Organizations implementing FinFloh have reported significant improvements, including 40% reduction in DSO, 250 man-hour savings per month, and 50% reduction in high-aging balance.
Features
- AI Credit Decisioning: ML-driven scoring based on buyer behavior & market intelligence
- Automated Collections: Scheduled follow-ups with customizable tonality based on buyer category
- Smart Dispute Resolution: Predictive analytics and centralized communication platform
- Intelligent Cash Application: ML-based OCR engine for payment matching
- ERP/CRM Integration: Native integration with major systems
- Automated Workflows: Customizable processes for collections and dispute management
Use Cases
- Automating accounts receivable processes
- Reducing Days Sales Outstanding (DSO)
- Streamlining credit decision making
- Managing invoice disputes
- Automated cash application
- Credit risk assessment
- Payment collection optimization
FAQs
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How long does it take to implement FinFloh?
Typically, it takes 2-6 weeks for complete setup and go-live, depending on the complexity of scope. -
What ERPs does FinFloh integrate with?
FinFloh is ERP agnostic and can integrate with any ERP/accounting system, including Netsuite, SAP, Microsoft Dynamics 365, Oracle and more. -
Does FinFloh offer a free trial?
Yes, FinFloh offers a 14-days free trial of its accounts receivable software.
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FinFloh Uptime Monitor
Average Uptime
100%
Average Response Time
617.8 ms
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