Retail and Commercial Banking

Agentic AI in retail and commercial banking refers to AI systems that autonomously execute multi-step tasks, such as document extraction, risk assessment, and compliance reporting, without continuous human intervention. Brillio deploys this capability through modular agent libraries, GenAI copilots, and an AI-first software development lifecycle with built-in observability, enabling banks to automate complex workflows across onboarding, lending, and payments. This architecture, part of Brillio’s Enterprise AI Accelerator practice, is purpose-built for banking environments where auditability and regulatory adherence are non-negotiable.

AI improves loan processing and underwriting by enabling seamless document verification, intelligent data extraction, and always-on customer engagement throughout the lending journey, replacing slow, manual review cycles with continuous, automated workflows. Brillio’s loan processing accelerator applies these capabilities to streamline each stage of the lending process, from application intake to credit decisioning, reducing friction for both applicants and operations teams. For banks processing high application volumes, this translates directly into faster cycle times and lower per-loan operational cost.

Brillio’s banking practice covers more than 50 validated AI use cases spanning six core domains: digital onboarding, core banking transformation, automated regulatory compliance and reporting, loan processing and underwriting, payment modernization, and fraud prevention and management. Each use case is tuned specifically to banking workflows, including client targeting, servicing, and compliance, rather than adapted from generic enterprise AI templates. This depth of industry focus allows Brillio to deliver relevant AI in commercial banking services without the extended discovery and customization cycles typical of generalist technology providers.

AI improves fraud detection accuracy in banking through predictive analytics and real-time scoring models that continuously detect emerging transaction patterns and adapt to new threat vectors faster than rule-based systems can. Brillio’s fraud prevention and management accelerator applies these models within payment modernization workflows, achieving a 70% increase in fraud detection accuracy for banking clients. This real-time scoring capability ensures that legitimate transactions are not unnecessarily blocked while suspicious activity is flagged and investigated with speed and precision.

Banks implementing Brillio’s AI-powered digital onboarding accelerator have achieved a 68% improvement in client onboarding speed, driven by automated document intelligence, real-time risk insights, and automated data extraction that eliminate manual bottlenecks. Beyond speed, the architecture also supports commercial client onboarding through AI agents that perform initial risk assessments, reducing the time relationship managers spend on administrative tasks. These outcomes are delivered through prebuilt agents and reusable assets that allow Brillio to deploy production-ready onboarding solutions three times faster than traditional build approaches.

Brillio’s banking AI architecture is built to satisfy SEC, FRB, and CFPB regulatory requirements, with audit trails and agent lifecycle governance embedded by design rather than added as an afterthought. This trust-centered approach means every AI agent operating across onboarding, lending, or payments functions within a governed framework that supports examiner review and compliance reporting. Automated regulatory compliance and reporting is also a dedicated accelerator within the practice, reducing manual overhead and improving accuracy and response times in regulatory submissions.

Brillio accelerates core banking modernization with AI by deploying cross-functional squads trained in GenAI, prompt engineering, and agent engineering alongside deep banking domain expertise, eliminating the ramp time that slows traditional vendor engagements. Prebuilt agents, playbooks, and reusable assets enable three times faster delivery compared to conventional development approaches, while platform integrations across Salesforce, Snowflake, ServiceNow, and Databricks mean banks can modernize within their existing technology ecosystem rather than replacing it wholesale. The result is a measurable speed-to-value advantage for institutions that need to move quickly without sacrificing architectural integrity.