IBM LinuxONE 4 offers an infrastructure designed for predictive AI workloads and secure data management. CreditX is available and supported on LinuxONE.

At FinbotsAI, we continuously seek innovative solutions that empower our clients to unlock new business value. By harnessing the capabilities of IBM LinuxONE, our clients can take advantage of an infrastructure specifically designed to support a variety of predictive AI workloads. This collaboration presents an opportunity to enhance operational efficiency while minimizing the time and effort needed to integrate AI into their existing processes.

IBM LinuxONE 4’s on-chip AI accelerator is engineered for speed and scale, providing a dedicated resource for AI inferencing to support high levels of throughput. In addition to its high-performance AI capabilities, IBM LinuxONE is designed with security at its core. It is engineered to be energy-efficient. Moreover, LinuxONE’s built-in security features, such as pervasive encryption and confidential computing environments, help sensitive data remain protected, giving businesses the confidence to innovate and grow in a complex landscape.

Example Use Cases for CreditX

Use Case 1: Credit Risk Modeling for a MSME Retail Bank in the Philippines

Challenges Faced: A leading commercial bank in the Philippines struggled to scale its lending portfolio due to several key issues:

• Development and deployment of credit models took over 3 months.
• Limited scope for model deployment and variable usage in scorecards.
• The credit modeling process was highly manual.

After using CreditX, the bank was able to develop and deploy high-performing bespoke credit models efficiently.

Outcomes Achieved*:

• Reduced Development Time: The time required to develop and deploy credit models decreased from 3 months to just 1 week, achieving a 25x faster turnaround.
• Increased Model Accuracy: CreditX’s machine learning approach enhanced the accuracy of the credit models.
• Comprehensive Risk Assessment: The solution enabled the bank to assess riskiness, utilisation, and propensity together, improving upsell targeting.
• GINI Improvement: The GINI coefficient improved by 12%, indicating better predictive performance of the credit models.

Use Case 2: Credit Risk Modeling for a B2B BNPL FinTech in Nigeria

Challenges Faced: A B2B FinTech aimed to grow purchase financing for MSMEs but faced significant obstacles:

• Recurring defaults hindered portfolio scaling.
• Manual credit application processing limited growth potential.
• Lack of reliable credit bureau data.
• Insufficient or non-credible annual financial accounts and bank statements.

After using CreditX, the FinTech was able to develop and deploy high-performance credit models effectively.

Outcomes Achieved*:

• Rapid Model Development: Successfully developed credit models within just 3 days.
• Exploratory Data Analysis (EDA): Conducted EDA on financial institution data and leveraged supply-chain data.
• Automation: Automated the entire credit risk value chain, including instant loan approvals.
• Quick Time to Value: Enabled swift implementation and results.
• Loss Rate Reduction: Decreased loss rates by 5 to 10 points.
• Increased Processing Capacity: Achieved the ability to process 50x more applications daily.

How Clients Can Leverage IBM LinuxONE 4 with CreditX

Now CreditX and its unique AI powered unified Credit Risk Modeling, Scoring and Decisioning platform is available as a ready-to-use offering for Financial Institutions within the LinuxONE ecosystem that offers enterprise-grade cyber-resilient platform for the ever-growing AI and Analytics workload requirements.

FIs can now leverage the power of LinuxONE’s efficient compute capabilities coupled with a scalable and resilient hybrid cloud offering to effortlessly build and deploy advanced AI powered Credit Scorecards and Decisioning workflows in a matter of hours.

As part of the IBM ecosystem, FinbotsAI is dedicated to helping companies maximize the value of their infrastructure investments by integrating tools and technologies designed to enable success in an AI-driven landscape. We look forward to collaborating with IBM to deliver innovative solutions to our clients.

*The following outcomes were reported by FinbotsAI.