Centific proudly presents our GenAI Foundational Workshop, designed to help financial services organizations implement Generative AI on AWS to drive efficiency across various functions, from client advisory to automated underwriting. By moving beyond the proof of concept, teams will be equipped to deploy AI solutions on AWS that automate documentation, enhance customer engagement, and improve predictive analytics.

Guided by Centific’s AI experts, you’ll explore the components of a frontier AI data foundry platform tailored for financial services on AWS. This platform is designed for agility and scalability, supporting AI models that tackle everything from customer segmentation to real-time investment insights. With its robust infrastructure on AWS, the data foundry provides a secure and efficient foundation for implementing AI across a range of financial applications, ensuring that models are built to handle sensitive data with precision and compliance.

Workshop structure

The GenAI Workshop consists of a series of joint architecture design meetings, ranging from 1 to 2 hours per session (up to 8 hours total), focusing on the following financial services-specific domains:

• Data Modernization: Prepare data platforms for AI integration across client management, loan processing, and investment strategies. This involves streamlining data from structured sources (e.g., financial records) and unstructured sources (e.g., customer interactions) for comprehensive insights.

• Data Supply: Develop data pipelines to handle diverse financial data, supporting applications such as transaction analysis, customer behavior prediction, and product recommendation. This capability strengthens personalized service delivery and timely market responses.

Model Fine-Tuning: Customize AI models for specialized tasks, including underwriting automation, market forecasting, and risk scoring. Tailoring models for industry-specific use cases enables more accurate predictions and refined decision-making, contributing to improved client service and operational agility.

• Infrastructure & Deployment: Establish secure, scalable GenAI deployment practices that support continuous integration in financial workflows. Explore secure deployment options, including cloud and on-premises hosting, to ensure high-performance AI solutions across client advisory, credit assessment, and investment analysis.

• GenAI Agents & Knowledge assistance: Deploy AI-driven agents for various applications, from financial advisory support to claims processing automation in insurance. These agents enhance operational efficiency, streamline knowledge discovery, and improve response times, adding value across customer touchpoints.

Each session emphasizes discovery, design, and education, showing how an AI data foundry platform can enhance financial services by powering predictive analytics, real-time insights, and personalized client interactions.

Deliverables

• Technical Deep-Dive Discovery Sessions: Collaborative workshops with Centific’s AI experts to align your GenAI strategy with financial services goals such as fraud prevention, secure data handling, and regulatory compliance.

• Future-State Architecture Diagram: A comprehensive framework tailored to financial services, covering secure data aggregation, AI-powered client insights, and automation in customer service and underwriting.

• Recommendations Report: A summary of key insights and strategic choices that help prioritize AI use cases such as wealth management optimization, automated portfolio rebalancing, and real-time market analysis.

• Cost Estimation: Using Centific’s cost estimation tools, forecast the Total Cost of Ownership (TCO) for your GenAI deployment, ensuring efficient allocation of resources for data management, client support automation, and operational improvement.

• Implementation Proposal: A detailed plan outlining the scope and costs of Centific’s services to safely deploy and scale GenAI for financial services, with action steps for integration into core business functions.

Timeline

The workshop is structured to be completed in approximately two weeks, depending on the availability of your project sponsor and technical teams. For convenience, we also offer the option of conducting the Workshop as an 8-hour onsite, in-person session.

Next Steps

Following the workshop, typical next steps include proof-of-concept deployments to demonstrate the AI solution’s capabilities, followed by full production implementation. These steps help ensure the AI deployment can effectively support core financial functions like client advisory, loan processing, and market analysis.