Editor’s Note: We are thrilled to feature this guest post by Tracy Julian, Financial Services Industry Lead & Architect at Perficient. With over 20 years of experience across retail banking, wealth management, and fintech, Tracy is a systems architect who specializes in turning complex data hurdles into high-velocity, future-ready AI solutions.
Executive Summary
Financial services organizations face mounting pressure to deliver highly personalized client experiences while navigating increasingly complex regulatory requirements. At the same time, relationship managers and advisors spend a significant portion of their week searching for client information across disconnected systems. This administrative burden reduces time available for strategic client engagement and limits the ability to proactively identify cross-sell, retention, and risk management opportunities.
Agentforce, Salesforce’s enterprise-grade agentic AI platform, addresses these challenges head-on. By automating data aggregation, surfacing real-time insights, and embedding compliance-aware intelligence directly into workflows, Agentforce helps financial services teams operate more efficiently and intelligently.
This article explores real-world Agentforce financial services use cases and provides a practical implementation roadmap for organizations evaluating AI agent deployment.
Key Takeaways
- Agentforce reduces client research time through automated, multi-source data aggregation
- Four proven Agentforce financial services use cases across banking, wealth, and asset management
- A 4–6 week implementation timeline is achievable with proper planning
- Built-in compliance automation aligned with SOC 2 and financial services standards
The Challenge: Data Fragmentation in Modern Financial Services
Financial services teams across B2B banking, wealth management, registered investment advisors (RIAs), and workplace services face a shared set of challenges that directly impact revenue, efficiency, and client satisfaction.
- Information Silos Create Operational Inefficiency
- Client data is scattered across multiple Salesforce orgs, legacy core banking systems, portfolio management platforms, and document repositories
- Financial advisors manage information across many different systems
- There is no single, unified view of client relationships, risk indicators, or cross-sell opportunities
- Time-Intensive Meeting Preparation
- Client-facing teams spend disproportionate time on administrative tasks rather than strategic interactions
- Relationship managers manually compile company summaries, account histories, and risk assessments before each meeting
- Information retrieval delays slow response times to client inquiries
- Escalating Regulatory Complexity
- Increasing regulations around data privacy (GDPR, CCPA, GLBA), personally identifiable information (PII), and record retention
- Manual compliance reviews create operational bottlenecks and increase the risk of human error
- Document scanning for sensitive data (SSNs, account numbers, tax IDs) is often reactive rather than preventive
- Missed Revenue Opportunities
- Without unified intelligence, leaders struggle to identify upsell, cross-sell, and retention risks in real time
- Fragmented data limits proactive account planning and relationship management
- Inconsistent visibility into consultant and intermediary relationships reduces partner channel effectiveness
Real-World Example: Multi-Org Complexity
A Perficient financial services client operates 20+ production Salesforce orgs across marketing, sales, and service. This complexity has resulted in:
- Significant manual effort by relationship managers searching for client information
- Inconsistent data interpretation across sales and service teams
- Compliance vulnerabilities caused by manual PII identification processes
- Delayed opportunity identification due to siloed account intelligence
This scenario is common across enterprise financial services organizations—and represents one of the most compelling Agentforce financial services use cases.
How Salesforce Agentforce Helps
Agentforce is Salesforce’s next-generation AI platform, combining:
- Natural language processing (NLP) for conversational interfaces
- Multi-source data aggregation across Salesforce objects, external systems, and documents
- Workflow automation triggered by agent-driven insights and actions
- Compliance-aware processing with PII detection and security controls
- Real-time intelligence generated from both structured and unstructured data
Unlike traditional chatbots or rule-based automation, Agentforce agents:
- Understand context and intent from natural language queries
- Access and synthesize information from multiple data sources simultaneously
- Generate actionable insights and recommendations—not just raw data
- Learn from user interactions to improve relevance over time
- Integrate seamlessly with existing Salesforce workflows and third-party systems
Agentforce leverages Salesforce Einstein AI, Data 360 for unified data access, and the Hyperforce infrastructure to deliver enterprise-grade security, compliance, and trust for financial services use cases.
Four High-Impact Agentforce Financial Services Use Cases
The following Agentforce use cases have been developed specifically for financial services and can typically be implemented within four weeks.
Client Intelligence Agent: Gain 360-Degree Relationship Insights
The Client Summary Agent consolidates comprehensive client intelligence in seconds, eliminating manual data gathering. It aggregates:
- Company & Contact Details: Legal entity structure, key decision-makers, organizational hierarchy
- Financial Position: Account balances, asset allocation, liabilities, portfolio performance
- Relationship Health: Engagement scores, activity frequency, NPS data, retention risk indicators
- Opportunity Pipeline: Active deals, proposal status, estimated close dates, win probability
- Service History: Open and closed cases, resolution times, satisfaction ratings
- Interaction Timeline: Meetings, calls, emails, and all historical touchpoints
Business Outcome
Relationship managers can prepare for meetings faster, personalize conversations, and proactively identify engagement and retention risks. Time previously spent gathering data is redirected to strategic client interactions. This represents one of the foundational Agentforce financial services use cases.
Account Relationship Agent: Manage Complex Accounts & Client Risk
For firms that work with consultants, brokers, or intermediaries, the Account Relationship Agent provides a unified view of partner relationships by consolidating:
- Partner Profile: Firm details, key contacts, AUM/AUA influenced, areas of specialization
- Referral History: Opportunities sourced, conversion rates, deal size, revenue attribution
- Engagement Metrics: Meeting cadence, co-marketing activity, webinar participation, content engagement
- Pipeline Analysis: Active referrals by stage, forecasted revenue, deal aging
- Collaboration Activity: Shared plans, joint calls, tasks, and communication history
Business Outcome
Sales teams gain clarity into partner performance and potential, enabling better territory planning, stronger collaboration, and more strategic channel investment.
Client Prospect Agent: Optimize Sales Intelligence & Next Best Action
The Client Prospect Agent transforms raw data into actionable sales intelligence by analyzing:
- Company Intelligence: Industry position, competitive landscape, growth signals, news mentions
- Buying Signals: Website engagement, content consumption, event attendance, RFP activity
- Relationship Mapping: Existing connections, decision-makers, organizational structure
- Whitespace Analysis: Current services versus product catalog, cross-sell and upsell opportunities
- Next Best Actions: Prioritized recommendations based on engagement and firmographic data
Business Outcome
Sales teams can prioritize accounts more effectively, uncover whitespace opportunities, and focus on actions that accelerate deal progression. This Agentforce financial services use case is most beneficial for acquisition teams.
Document Scanning Agent: Automate PII Compliance Safeguards
Regulatory compliance is non-negotiable in financial services. The Document Scanning Agent provides automated, pre-upload document scanning for:
- Social Security Numbers (SSNs): Multiple formats (XXX-XX-XXXX, XXXXXXXXX)
- Tax Identification Numbers (TINs/EINs): Business and individual identifiers
- Account Numbers: Bank, credit card, and brokerage accounts
- Passport Numbers: Government-issued identification
- Custom PII Patterns: Configurable regex for institution-specific data types
Business Outcome
Organizations reduce human error, strengthen compliance posture, and protect sensitive client data—automatically and proactively.
Getting Started: Next Steps for Your Organization
If your organization is evaluating Agentforce, consider the following steps:
- Assess Your Current State
- Map data fragmentation across systems and or within the Salesforce org across objects
- Quantify time spent on manual data gathering
- Identify high-impact pain points
- Establish baseline metrics for measuring improvement
- Define Success Criteria
- Business outcomes: Efficiency gains, revenue impact, compliance risk reduction
- Adoption targets: Percentage of users actively engaging with agents
- Technical performance: Accuracy, response time, data completeness
- ROI expectations: Payback period and time to value
- Prioritize Use Cases
- Identify quick-win Agentforce financial services use cases that deliver value in 30–60 days
- Assess team readiness and change appetite
- Evaluate data availability and quality
- Align use cases to regulatory risk and compliance priorities
- Engage Expert Partners
- Schedule a discovery workshop with Perficient
- Review reference architectures and live demonstrations
- Develop a phased implementation roadmap
- Establish governance, KPIs, and success metrics
AI Agents as a Competitive Advantage in Financial Services
The financial services industry is at an inflection point. Organizations that successfully deploy Agentforce financial services use cases to augment human expertise will gain durable competitive advantages, including:
- Superior client experiences through faster, more personalized, and proactive service
- Improved operational efficiency by shifting effort from administration to relationship management
- Revenue growth through earlier identification of cross-sell, upsell, and retention opportunities
- Increased compliance confidence with automated safeguards that reduce regulatory risk
- Data-driven decision-making powered by unified, real-time intelligence
Agentforce represents Salesforce’s most significant AI advancement for financial services—combining trusted CRM data with cutting-edge agentic AI capabilities. Organizations that move quickly, but strategically, will establish lasting advantages in client relationships, operational efficiency, and market leadership.
Meet Your Expert
Tracy Julian
Financial Services Industry Lead & Architect, Salesforce Practice
Tracy brings more than 20 years of financial services experience in retail banking, wealth management, capital markets, and fintech, spanning both industry and consulting roles with firms including the Big 4 across the U.S. and EMEA.
She leads Perficient’s financial services industry efforts within the Salesforce practice, partnering with clients to define the vision and goals behind their transformation. She then uses that foundation to build smarter, future-ready solutions that deliver business first, scalable solutions across strategy, cloud migration, and innovation in marketing, sales, and service.
A systems architect by trade, Tracy is known for aligning teams around a shared vision and solving complex problems with measurable impact.
