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Revolutionizing Commercial Credit with AI

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 Revolutionizing Commercial Credit with AI - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Machine Learning
  • Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
  • Education
  • Finance & Insurance
Use Cases
  • Predictive Maintenance
  • Time Sensitive Networking
  • Data Science Services
The Challenge
One of the largest banks in Asia, Africa, and the Middle East, with a presence in over 60 countries, was grappling with the complexity of its commercial lending process. The bank, responsible for providing clients with more than $100 billion worth of credit, had to efficiently offer a variety of credit products and services to thousands of businesses across numerous countries and sectors. The process of assessing the creditworthiness of its clients was time-consuming and required the collection, review, and analysis of thousands of fields of both qualitative and quantitative information. This included financial statement line items, performance metrics, credit history, and natural language assessments of the borrower’s business prospects. The bank's credit officers had to navigate disparate systems, collaborate with relationship managers and credit analysts on credit structure and conditions, and request additional information before making a final decision. The average time-to-decision was often measured in weeks.
The Customer
About The Customer
The customer is one of the largest banks operating across Asia, Africa, and the Middle East, with a presence in over 60 countries. The bank manages an end-to-end commercial lending process, providing clients with more than $100 billion worth of credit. The bank employs a team of hundreds of relationship managers, analysts, and credit officers to efficiently provide a variety of credit products and services to thousands of businesses spread across dozens of countries and sectors. The bank has an annual operating income of $14 billion and employs 85,000 people globally.
The Solution
The bank adopted C3 AI® Smart Lending, a SaaS application built with the C3 AI Platform, to reengineer its lending process. This solution uses machine learning to reduce the average approval cycle time by 30%. The streamlined process enabled the bank to extend more credit, accelerate revenue, and improve customer satisfaction. The C3 AI Platform applies machine learning to all relevant data sources to rapidly generate predictive insights. These insights can be used to enhance rules-based banking systems, improve critical compliance and operational processes, and transform customer experiences. The implementation of the C3 AI Platform across the enterprise was projected to bring significant economic value.
Operational Impact
  • The implementation of the C3 AI® Smart Lending solution transformed the bank's commercial lending process. The use of machine learning significantly reduced the average approval cycle time, enabling the bank to extend more credit and accelerate revenue. The solution also improved customer satisfaction by streamlining the lending process. The C3 AI Platform's ability to rapidly generate predictive insights from all relevant data sources enhanced the bank's rules-based banking systems and improved critical compliance and operational processes. The transformation of the bank's lending process also had a positive impact on customer experiences. The bank was able to process 68,000 applications from 20 different countries, reflecting four years of history, in just 12 weeks. The precision and recall rates for approved cases were 98% and 81% respectively.
Quantitative Benefit
  • 12 weeks from kick-off to production-ready application
  • 68,000 applications processed, 4 years of history from 20 different countries
  • $100 million expected annual economic revenue benefit

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