Unlocked 6 new M&A offerings and upgraded 15 deal stages using AI and computing technologies
CamIn works with early adopters to identify new opportunities enabled by emerging technology.
of CamIn’s project team comprised of leading industry and technology experts
Our financial services client wanted to confirm how AI & HPC upgrades their current services and unlocks new opportunities within 5 years. CamIn identified 6 high-impact AI services the client could build using their current infrastructure
Table of Contents
The client was losing ground in its multi-billion dollar M&A business as competitors gained an edge using AI to drive pricing advantages. Global M&A deal volumes have exceeded $4 trillion annually in recent years, with firms leveraging advanced analytics and automation achieving up to 20 percent faster deal cycles and significantly lower due diligence costs.
To stay competitive, the client needed to modernise its product and service offerings using AI, high-performance computing, and other digital innovations that could provide a first mover advantage over the next five years. The objective was to identify technologies that could improve deal execution, reduce risk, and capture greater market share in an increasingly data-driven M&A environment. Identifying the right approach required expertise in frontier technologies and strategic transactions that went beyond the client’s in-house capabilities.
15 | Identified 15 steps in the entire M&A process where significant impact can be achieved with AI & HPC, achieving quick-win opportunities for the client and their current capabilities. |
16 | Confirmed 16 AI & HPC use cases that the client could instantly upgrade their current products with to enhance performance, value to customer, and price position. |
8 | Identified 8 grand challenges of unmet customer needs, where existing solutions fall short of critical success factors, revealing clear white spaces. |
6 | Confirmed 6 new competitive products for the client to develop based upon feasibility of technology, interest from current and new customers, and straightforward implementation within current infrastructure. |
6 new products confirmed for development based on tech feasibility, customer interest, and ease of implementation.
The client developed and piloted 4 out of the 6 products: 3 to capture quick-win opportunities and 1 to capture a white space.
The client confirmed the success of the product launches, generating revenue and de-risking their $10 million investment.
AI (Artificial Intelligence) and HPC (High-Performance Computing) enable financial advisory firms to automate, accelerate, and enhance key deal-making functions such as financial modelling, target screening, risk analysis, and due diligence. AI can ingest and analyse vast amounts of structured and unstructured data, including filings, financial reports, news feeds, and transaction histories, to uncover patterns and insights at a scale beyond human capability. HPC systems provide the processing power required to run these complex models in real time, enabling simulations, forecasts, and valuations that are both faster and more precise. Together, they create a next-generation advisory stack that transforms traditional workflows into intelligent, data-driven processes.
As deal volumes grow and competitive pressure intensifies, financial advisory firms are being pushed to deliver faster, smarter, and more precise insights. The sector is characterised by high data complexity, tight timelines, and increasing demands for strategic clarity. In this environment, Artificial Intelligence and High Performance Computing are becoming essential tools for gaining a competitive edge. Firms that adopt these technologies can streamline processes, enhance accuracy, and deliver more value to clients across the deal lifecycle.
AI and HPC will transform the financial advisory landscape into a real-time, insight-led service model. Over the next decade, they will:
Several transformative technologies and platforms are coming into use and will expand significantly over the next decade:
A leading North American advisory firm implemented a proprietary diligence engine using AWS Textract, transformer-based NLP, and vector search. This reduced document review time by 60 percent and shifted analyst focus toward modelling and strategy.
Over the next 10 years, these tools will continue to evolve, powered by advances in quantum computing, federated learning for deal data sharing, and vertical AI agents for specific advisory use cases. This will allow firms to launch new service lines and operational models that are both more intelligent and more scalable.