Overview
A leading global investment bank and long-standing Evalueserve client sought to implement AI across its deal origination and deal execution teams to reinvest the resulting efficiency gains. With a partnership spanning more than two decades, beginning with research support in 2003 and expanding into investment banking and capital markets in 2018, the bank had already built a strong foundation of scaled, global operations supported by Evalueserve across multiple service lines.
While automation was already in place, leadership recognized the opportunity scale agentic AI across core investment banking workflows. Agents could automate repetitive tasks, reduce the workload of the deal origination and deal execution teams, and enable the team to expand support to new groups. For our client, AI deployment was about converting operational efficiency into strategic capacity and creating a durable advantage, not just a cost-reduction experiment.
Challenge
Despite operating at scale with well-established processes, our client’s deal origination and deal execution teams faced structural constraints. Analysts across global delivery centers supporting more than 600 bankers in India, Chile, and China were already near full utilization, leaving limited room to absorb incremental deal activity or expand support across business units.
At the same time, the bank was navigating a broader industry challenge: while AI adoption was a strategic priority, many solutions in the market lacked a clear path to measurable impact or failed to account for the complexity and regulatory rigor of investment banking workflows.
The bank needed to answer several critical questions:
- Where in the investment banking workflow could AI deliver consistent, high-confidence outputs?
- How could agentic AI be deployed without compromising accuracy, auditability, and compliance?
- How could efficiency gains be quantified and sustained over time?
Crucially, success requires more than introducing tools. It required embedding AI into the “plumbing” of existing workflows, where tasks, dependencies, and quality standards were already well understood.
Solution
Leveraging its deep investment banking advisory expertise, Evalueserve partnered with the global investment bank to design and operationalize a structured, agentic AI deployment model grounded in workflow-level understanding and measurable outcomes.
1. Workflow-led identification of AI opportunities
Rather than applying AI generically, the team conducted detailed workflow scans across deal origination and deal execution processes such as company profiling, trading and transaction comparables, slide creation, and industry research.
This allowed for precise identification of tasks that were:
- High-volume and repeatable
- Rules-based or semi-structured
- Suitable for human-in-the-loop validation
2. Targeted deployment of agentic AI
Specialized AI agents were developed for distinct work products, including:
- Company profiles
- Trading comparables
Each agent was trained and refined based on domain-specific context, ensuring outputs aligned with investment banking standards rather than generic AI behavior. This modular approach also avoided “agent sprawl” by aligning agents to specific workflows and use cases.
3. Human-in-the-loop design for precision workflows
Recognizing the importance of accuracy in banking, AI outputs were integrated into a human-in-the-loop model. Analysts validated, refined, and contextualized outputs—ensuring reliability while still capturing efficiency gains.
4. Governance and lifecycle management
A structured governance model was implemented to ensure consistent performance and compliance, including:
- Designated agent owners and AI champions
- Continuous training and refinement processes
- QA frameworks to validate outputs and maintain auditability
- Monitoring systems to track performance, drift, and reliability
This governance layer was critical to meeting regulatory standards and ensuring scalable, long-term adoption.
5. Measurement framework for AI impact
To address a common industry gap, the engagement included a clear framework for measuring AI-driven efficiency gains. Time savings and productivity improvements were tracked at the workflow level, enabling transparent reporting and continuous optimization.
Business Impact
Within the first few months of deployment, the agentic AI initiatives began generating measurable value. We achieved ~10% efficiency gains in year one and redeployed the gains, resulting in:
- Significant reduction in manual effort for repetitive, time-intensive tasks
- Increased capacity for analysts to focus on higher-value activities such as analysis, interpretation, and banker engagement
- Improved consistency and standardization of outputs across global teams
- Expanded ability to absorb incremental work across groups
Together, these outcomes established a strong, scalable foundation for sustained productivity gains and broader AI adoption across investment banking workflows. Building on this momentum, we are on track to reach ~25% efficiency gains in year two as additional use cases scale and more deal origination and execution teams adopt the new workflows
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Overview & Impact
A leading global investment bank partnered with Evalueserve to transform deal origination and execution workflows through agentic AI, delivering measurable efficiency gains, increased analyst capacity, and standardized outputs while enabling scalable, governed adoption across global teams without compromising accuracy, compliance, or auditability.