Agentic AI in lending: where to begin and what to prioritize

<p><b>Chart a clear path for agentic AI in mortgage lending with a defined vision, versatile use cases and integrated workflows.</b></p>

<p>Mortgage lending is at a crossroads . One road leads to more of the same—minor technology tweaks that barely keep up with technological advances, borrower expectations and regulatory demands. The other road fundamentally reimagines mortgage lending so that it’s not just faster or marginally better but radically transformed.</p> <p>The latter path is made possible with agentic AI. Beyond automating tasks, agentic AI promises to reshape lending from application through closing. The key is for lenders to define a strategic vision, focus on cross-functional use cases and build integrated workflows.</p> <h4>Why agentic AI matters in automating mortgage lending</h4> <p>Despite their sophistication, generative AI models often lack mechanisms for integrating industry-specific context, providing real-time feedback mechanisms and continuously refining their outputs. As such, they don’t meaningfully change business processes or customer experiences. As a result, organizations remain stuck in repetitive cycles of experimentation that don’t scale.</p> <p>Agentic systems, meanwhile, are designed with persistent memory and the ability to continuously learn. In addition to processing information, they also retain context, adapt to evolving environments and autonomously orchestrate complex workflows.</p> <p>What’s more, agentic AI can assist with scaling solutions and processes within lending’s complex and highly regulated environment. These systems integrate disparate data sources, automate decision-making and coordinate activities across departments to drive greater productivity and agility.</p> <p>As such, agentic AI promises to take organizations from endless cycles of pilot implementations to building a scalable, self-learning organization. Take call summarization. While generative AI can create a basic summary of a customer call, agentic AI acts. An AI agent can push out updates or enter key data points into a CRM platform, accounting for business rules. That same AI agent might flag missing disclosures needed for compliance and audits, highlight exceptions in call behavior and trigger follow-up actions.</p> <p>For lenders, the transition to agentic AI means moving beyond process efficiency to process orchestration.</p> <h4>How to get started with AI in mortgage lending</h4> <p>Despite a wealth of potential agentic AI use cases, many lenders are unsure of where and how to start. Which department would most benefit from agentic AI? Which application of agentic AI would most impact the bottom line?</p> <p>While each lender’s journey is different, we advise clients to focus on three key steps to capitalize on the promise of agentic AI in loan origination and servicing.</p> <p><b>1. Define a strategic vision.</b> Given mortgage lending’s cyclical nature and rapid changes in customer expectations, the integration of agentic AI requires a deliberate, strategic approach. The journey begins with an actionable vision that aligns AI initiatives with organizational goals. How can agentic AI enhance operational efficiency? How can it improve customer experience, manage risk and drive sustainable growth across the mortgage value chain?</p> <p>To define what success looks like, leadership collaboration is a must. So is early engagement with stakeholders from across the business—operations, risk management, compliance and customer service—to identify pressing challenges and opportunities that AI can address.</p> <p>Establish specific objectives, such as reducing loan processing times, increasing underwriting accuracy or personalizing borrower interactions. These objectives need to be clearly connected to anticipated business outcomes.</p> <p>Ground the vision in a thorough understanding of the current state of technology, data infrastructure and workforce readiness. By assessing digital maturity and identifying gaps, you can create a roadmap for AI adoption and highlight areas where foundational improvements are needed. The vision needs to incorporate a commitment to ethical AI use, emphasizing transparency, fairness and regulatory compliance.</p> <p>Finally, use the strategic vision as a framework for prioritizing investments, shaping the organizational culture and communicating the value of agentic AI to stakeholders. By establishing clear leadership, measurable goals and an inclusive approach, mortgage lenders can harness agentic AI for resilience and long-term success.&nbsp;</p> <p><b>2. Focus on cross-functional use cases. </b>The key to seeing a return on investment is to develop agents once and deploy them many times. This means identifying use cases that are versatile and applicable across the lending life cycle. Start small and look for use cases that can benefit multiple departments and functions. For example:</p> <ul> <li><b>Intelligent document processing:</b>&nbsp; Agentic AI can automate the extraction, classification and validation of data from loan applications, supporting documents and disclosures.<br> <br> <i>Who benefits:&nbsp;</i> Operations, compliance and customer service teams can reduce manual effort, minimize errors and improve processing speed.<br> <br> </li> <li><b>Workflow automation:</b> Agentic AI can orchestrate workflows, assign and complete tasks, self-learn and identify bottlenecks along the way.<br> <br> <i>Who benefits:</i> Origination, servicing and back-office operations.<br> <br> </li> <li><b>Chatbots and virtual agents:</b> AI-powered agents can drive voice and text conversations and virtual assistants that enable 24x7 borrower support. They can guide applicants through loan options, documentation requirements and status updates.<br> <br> <i>Who benefits:</i> Borrowers and customer service teams (for origination/servicing).<br> <br> </li> <li><b>Decision support:</b> Agentic AI can evaluate creditworthiness, analyze risk factors and recommend underwriting decisions using advanced analytics and real-time data.<br> <br> <i>Who benefits:</i> Origination, risk management and loss mitigation.</li> </ul> <p>By prioritizing enterprise-wide use cases, mortgage lenders can foster consistency, scalability and measurable impact. This will allow them to adopt a unified approach to transformation, positioning their organization for long-term innovation and competitiveness.</p> <p><b>3. Build integrated workflows.</b> Advancements in API-driven architectures and modular AI solutions are making AI-powered origination processes increasingly achievable.</p> <p>Unlike past modernization efforts—such as migrating to cloud-based platforms or implementing robotic process automation—integrating agentic AI demands higher data quality, interoperability and real-time orchestration. It also introduces new layers of complexity, including the need for robust data pipelines, model governance and ongoing monitoring of AI-driven decisions.</p> <p>From a technical standpoint, integration demands careful mapping of data flows, strong identity and access management and the ability to retrain AI models as business requirements evolve.</p> <p>Organizationally, successful integration hinges on cross-functional collaboration between IT, operations, compliance and business units. Such collaboration will ensure the solutions align with user needs and regulatory requirements. Change management is also critical to integration, as staff adapt to new roles and processes, and business leaders foster a culture of experimentation and continuous improvement.</p> <h4>The future of mortgage lending with AI</h4> <p>Capitalizing on agentic AI is about building a disciplined foundation that aligns technology with business goals, scales across functions and integrates into daily workflows.</p> <p>Lenders who follow this path will be positioned to move beyond incremental improvements and unlock a fundamentally new model for lending.</p> <p>For more information, visit Cognizant <a href="https://www.cognizant.com/us/en/industries/banking-technology-solutions" target="_blank" rel="noopener noreferrer">Banking</a> or contact the authors.</p>