Cognitive computing for financial services

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.

What is AI and HPC for financial advisory?

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.

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Why is AI and HPC important for the sector?

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.

• The sector depends on speed and accuracy: Financial advisory is one of the most data-intensive and time-sensitive industries. The ability to process and interpret large datasets quickly has a direct impact on winning mandates and delivering value.
• Adoption is already showing measurable benefits: Early adopters of AI in investment banking and M&A have reported up to 20 percent increases in deal volume and 30 to 40 percent reductions in due diligence time. AI-driven pricing tools have also improved margins by 10 to 15 percent in competitive bid environments.
• Manual workflows limit scalability and expose risk: Firms relying on traditional methods face regulatory and reputational risks due to human error, inconsistent analysis, and missed insights. These inefficiencies become increasingly costly in high-stakes transactions.
• AI and HPC unlock new strategic capabilities: These technologies enable automated data ingestion, prediction of cultural mismatches in M&A, simulation of cross-sell potential, automated target identification, and divestiture analysis. They help firms deliver deeper strategic insight at scale.
• Market forces demand transformation: With global M&A volumes exceeding 4.7 trillion US dollars in 2021 and continuing to rise post-pandemic, firms that fail to embrace AI and HPC will struggle to compete with faster, tech-enabled rivals.

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What impact will AI and HPC have onto the sector?

AI and HPC will transform the financial advisory landscape into a real-time, insight-led service model. Over the next decade, they will:

• Shorten deal cycles: Firms embedding AI have already cut average deal timelines by up to 25 day. By 2030, AI-native platforms could reduce this even further through automation of prep work and pre-built diligence.
• Expand market access: AI can make mid-market and cross-border deals more viable through automated screening and target matching. For example, a European advisory firm used AI-powered deal matching to increase cross-border transaction leads by 38 percent in one year.
• Improve recommendation quality: Advanced models are able to factor in non-traditional indicators such as sentiment from earnings calls, employee reviews, or environmental impact, providing differentiated insights.
• Support complex scenario modeling: HPC enables detailed simulations of tax, regulation, and integration outcomes under multiple macroeconomic conditions. This supports higher confidence in cross-border and large-scale deals.
• Enable new service models: Capabilities such as M&A-as-a-Service, automated deal origination, and always-on client advisory will be enabled through persistent AI models and scalable computing.

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What technologies are emerging for AI and HPC?

Several transformative technologies and platforms are coming into use and will expand significantly over the next decade:

• AI-powered valuation engines
  

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• Natural Language Processing for financial intelligence
  

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• Predictive deal scoring and target forecasting
  

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• Post-merger integration simulators
  

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• Client segmentation and outreach optimization
  

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• AI-enhanced due diligence
  

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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.