Case Studies Accelerated Customer Onboarding and Credit Approvals with Automated Systems

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	Accelerated Customer Onboarding and Credit Approvals with Automated Systems

Accelerated Customer Onboarding and Credit Approvals with Automated Systems

Technology Category	Analytics & Modeling - Predictive Analytics Application Infrastructure & Middleware - Data Exchange & Integration Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries	Agriculture Mining
Applicable Functions	Business Operation Quality Assurance
Services	Cloud Planning, Design & Implementation Services System Integration
Challenge	Mosaic faced significant challenges in their credit process within the order to cash cycle. Administering from North America and Brazil, they had a complex credit approval hierarchy with 7 to 10 layers of approval, which slowed down the process and affected customer experience. Additionally, they had to manually fetch credit data from various sources, which was time-consuming and labor-intensive. Their rigid credit scoring model did not account for country-specific risk factors, making it inefficient. Furthermore, the lack of real-time visibility into negative payment trends and macroeconomic fluctuations hindered their ability to proactively manage credit risk. Read More
About Customer	Mosaic is the largest US producer of potash and concentrated phosphate, serving farmers globally. Headquartered in Tampa, Florida, this Fortune 500 company operates in six countries and reported a revenue of $8.9 billion in 2020. Mosaic employs a large workforce to manage its extensive operations and is a key player in the agriculture industry. Read More
Solution	Mosaic leveraged HighRadius' Credit Cloud solution to address their challenges. The AI-based solution automated the approval workflow by categorizing customers into different risk buckets, enabling auto-approvals for low-risk customers and redirecting higher value approvals to senior management. The solution also automated the aggregation of credit data from multiple global and local agencies, reducing manual effort. Customized credit scoring models allowed Mosaic to develop credit limits based on specific business units and risk segments. Real-time credit risk monitoring provided continuous oversight of customer portfolios, alerting the credit team to any changes in risk and recommending revised terms. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Functional Applications - Enterprise Resource Planning Systems (ERP)

Applicable Industries

Agriculture

Mining

Applicable Functions

Business Operation

Quality Assurance

Services

Cloud Planning, Design & Implementation Services

System Integration

Challenge

Mosaic faced significant challenges in their credit process within the order to cash cycle. Administering from North America and Brazil, they had a complex credit approval hierarchy with 7 to 10 layers of approval, which slowed down the process and affected customer experience. Additionally, they had to manually fetch credit data from various sources, which was time-consuming and labor-intensive. Their rigid credit scoring model did not account for country-specific risk factors, making it inefficient. Furthermore, the lack of real-time visibility into negative payment trends and macroeconomic fluctuations hindered their ability to proactively manage credit risk.

About Customer

Mosaic is the largest US producer of potash and concentrated phosphate, serving farmers globally. Headquartered in Tampa, Florida, this Fortune 500 company operates in six countries and reported a revenue of $8.9 billion in 2020. Mosaic employs a large workforce to manage its extensive operations and is a key player in the agriculture industry.

Solution

Mosaic leveraged HighRadius' Credit Cloud solution to address their challenges. The AI-based solution automated the approval workflow by categorizing customers into different risk buckets, enabling auto-approvals for low-risk customers and redirecting higher value approvals to senior management. The solution also automated the aggregation of credit data from multiple global and local agencies, reducing manual effort. Customized credit scoring models allowed Mosaic to develop credit limits based on specific business units and risk segments. Real-time credit risk monitoring provided continuous oversight of customer portfolios, alerting the credit team to any changes in risk and recommending revised terms.

Impact #1	The automated approval workflow significantly reduced the number of approval layers, streamlining the process.
Impact #2	Auto-aggregation of credit data from multiple sources minimized manual effort and improved efficiency.
Impact #3	Customized credit scoring models provided more accurate and flexible credit assessments.

Impact #1

The automated approval workflow significantly reduced the number of approval layers, streamlining the process.

Impact #2

Auto-aggregation of credit data from multiple sources minimized manual effort and improved efficiency.

Impact #3

Customized credit scoring models provided more accurate and flexible credit assessments.

Benefit #1	50% reduction of credit approval layers.
Benefit #2	55.5% reduction in average approval time.
Benefit #3	15% increase in auto approvals.

Benefit #1

50% reduction of credit approval layers.

Benefit #2

55.5% reduction in average approval time.

Benefit #3

15% increase in auto approvals.

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Overview

Accelerated Customer Onboarding and Credit Approvals with Automated Systems

Operational Impact

Quantitative Benefit