AI
Reengineering financial services with AI
Capco experts share how generative AI is reshaping the software lifecycle. Discover its impact across global financial services.
AI is not a single project or static strategy, it's a journey of transformation.
Transforming Software Delivery for an AI-First World.
AI is reshaping the software development lifecycle (SDLC) into a growth engine – supercharging how businesses can respond to change. By embedding intelligent tooling, automating critical steps, and embracing new ways of working, organizations can accelerate delivery, improve quality, and scale innovation securely.
At Capco, we bring together AI-infused software delivery teams with tooling, accelerators and capabilities. This combination not only speeds up delivery cycles but also ensures solutions remain compliant, sustainable, and ready to evolve with future technologies.
Why it matters
Traditional enterprise software delivery processes are burdened by exploding complexity, mounting compliance requirements, and shrinking budgets. AI changes this equation by enabling engineering teams to do more impactful work using existing capacity.
Modern AI capabilities provide the opportunity to redesign and transform the change delivery engine into a faster, smarter, self-optimizing process that delivers innovation in days or weeks instead of months.
1. https://techreviewer.co/blog/ai-in-software-development-2025-from-exploration-to-accountability-a-global-survey-analysis
2. https://www.microsoft.com/en-us/research/publication/the-impact-of-ai-on-developer-productivity-evidence-from-github-copilot
3. https://arxiv.org/abs/2410.12944
How Capco can help
Capco partners with financial services organizations to reimagine how they design, build, and evolve software by embedding AI across the SDLC and change journey. Our approach centers around delivering quality at speed and adapting to constant, iterative changes in SDLC.
With tooling and custom accelerators identified for all stages of the SDLC – from automating requirements gathering, to designing and documenting architecture, to AI-driven testing – we have demonstrated it is feasible to accelerate the delivery of business value with every change. In doing so, we reduce delivery risk, compress timelines, and enable smoother adoption of change across large, complex enterprises.
Key elements
Our AI-infused SDLC of tomorrow is based on three principles: compliance aware, contextually crafted, and collaboration driven.
Compliance aware: AI-enabled development systems must align with responsible AI guardrails and secure SDLC principles.
Contextually crafted: Development activities must be tailored to shorter cycles, new ways of working, and evolving roles.
Collaboration driven: Change management must be embedded so teams are ready to work with AI.
Our approach
As every organization’s AI transformation journey is different, we employ three different approaches to deliver AI infused SDLC acceleration.
Assessment & pilot-first transformation: We start with a rapid assessment of your current SDLC, followed by tailored recommendations on how and where to apply AI. Using our custom accelerators and transformation expertise, we design a measurable pilot-first program – moving teams to developing from concept to prototype in weeks, not months –while embedding training and change management to ensure adoption and scale
Managed transformation: For organizations seeking accelerated outcomes without worrying about complex AI implementations, we take on delivery responsibility directly. Our teams focus on achieving pre-defined outcomes – such as faster throughput, higher quality, or lower cost – harnessing embedded AI capabilities to deliver.
Custom AI accelerator development: We design and build bespoke AI accelerators that integrate into your unique toolchain and workflows. From AI-driven requirements generation to agentic testing these solutions provide your software delivery teams differentiated capabilities tailored to your ecosystem and objectives.
Success story
Accelerated development of elevated customer enrollment experience.
Client challenge
Delivery delays had risked a client’s preparation for a major executive presentation showcasing the vision for a new enrollment experience. AI-infusion, with Capco’s support, was eyed as a potential solution to accelerate delivery.
How Capco helped
- Utilized AI accelerators to analyze customer pain points and synthesize a catalog of options for reimaging the enrollment workflow.
- Harnessed AI-infused design tools to wireframe target state experience.
- Developed an interactive prototype demonstrating the highlighted features, using prototyping tools controlled by AI agents.
Client outcomes achieved
- Accelerated definition and design going from rough concept to end-to-end enrollment flow within 1 week.
- Developed interactive prototype with demonstrable feature components within within 2 weeks.
- Achieved 100% adherence to client’s branding and design guidelines in prototype.
- Received glowingly positive feedback from executives and industry experts upon presentation.
Success story
Client challenge
Defining business requirements is typically a highly manual task involving conversations between key business stakeholders and SMEs facilitated by analysts. Accelerating business requirements definition enables us to speed up the SDLC overall and reduce time to market. Capco’s BA Genie accelerates requirements gathering by enhancing the capabilities of Business Analysts, Product Managers, and Testers.
How Capco helped
- Use AI to analyze input from SMEs (video conversations, transcripts, project documentation, etc.)
- Synthesize detailed requirements capturing the change as Epics, Features, and User Stories.
- Generate test plans, scenarios, and test steps for documented changes.
- Create and link generated work items in backlog management tools like Jira or Azure DevOps.
- Refine outputs through built-in human-in-the loop feedback.
Client outcomes achieved
- Reduce manual effort in requirements definition and documentation by 40-60%.
- Achieved greater consistency in output across all requirements using standardized AI outputs.
- Strengthened SME-analyst-developer collaboration with rapid drafts of requirements.
- Elevated BA teams to focus on differentiating strategic work vs repetitive documentation tasks.
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