How can Thought Machine enhance its core banking platform to improve scalability for larger financial institutions?

Introduction

To enhance Thought Machine's core banking platform for improved scalability for larger financial institutions, we need to focus on key areas that will allow the system to handle increased transaction volumes, user loads, and complex financial operations seamlessly. I'll approach this challenge by first understanding the current state of the platform, identifying pain points for larger institutions, and then proposing targeted solutions that address scalability concerns while maintaining the platform's core strengths.

Step 1

Clarifying Questions (5 mins)

• Looking at Thought Machine's position in the market, I'm thinking they might be facing increased competition from both traditional core banking providers and newer fintech players. Could you help me understand where Thought Machine currently stands in terms of market share and how this compares to its main competitors?

Why it matters: Determines if we need to focus on differentiation or catching up to market leaders Expected answer: Thought Machine has a growing market share but still trails behind some established players Impact on approach: Would influence whether we prioritize unique features or focus on matching competitor capabilities

• Considering the focus on larger financial institutions, I'm curious about the current user base. Can you provide insights into the size range of financial institutions currently using Thought Machine's platform, and what defines a "larger" institution in this context?

Why it matters: Helps define the target user segment and their specific needs Expected answer: Current users are mostly mid-sized banks, with "larger" referring to global banks with assets over $100 billion Impact on approach: Would tailor solutions to address the specific scalability challenges faced by global banks

• Given the emphasis on scalability, I'm wondering about the current technical architecture. Could you share information about the platform's current infrastructure, such as whether it's cloud-native, uses microservices, or has any known bottlenecks?

Why it matters: Identifies potential areas for improvement in the existing architecture Expected answer: Cloud-native with some microservices, but facing challenges with database scaling Impact on approach: Would focus on optimizing database performance and enhancing microservices architecture

• Thinking about the product lifecycle, I'm curious about the platform's current stage and recent growth. Can you provide information on user growth rates, transaction volumes, and any recent major feature additions?

Why it matters: Helps understand if scalability issues are due to rapid growth or inherent limitations Expected answer: Steady growth with transaction volumes doubling annually, recent addition of AI-powered risk assessment Impact on approach: Would prioritize immediate scalability solutions while planning for long-term sustainable growth