RM-led Wealth Management CRM for HNI/UHNI segments — built on Salesforce Financial Services Cloud (FSC) + Sales Cloud + Service Cloud, with Einstein/Agentforce AI, and deep backoffice integration (e.g., Miles, Wealth Spectrum) for holdings, transactions, orders, statements, and servicing straight-through processing.

Who this is for

This solution is designed for Wealth management firms (e.g., RM-led models) that manage HNI/UHNI relationships across Equity + Debt asset classes including:

• Mutual Funds, ETFs, Direct Equity
• Alternates distributed via wealth desk (AIFs, REITs/InvITs, private credit, etc.) …and need a unified front office + service desk with analytics and AI.
• Bonds / Fixed Income (G-Secs, SDLs, corporate bonds, NCDs)
• PMS
• Structured Products

Typical Users

• Relationship Managers (RMs) and Senior RMs / Team Leads
• Investment Counselors / Product Specialists / Advisory desk
• Branch / Region Heads (business oversight, coaching, escalations)
• Service/Operations teams (post-trade support, statements, profile changes)
• Dealing desk / Execution desk (where applicable)
• Compliance / Risk / Audit teams (governed communications & approvals)
• Sales Ops / CRM Admins (routing, data quality, dashboard governance)

A single Salesforce FSC-based wealth platform that delivers:

• Lead → Opportunity → Client lifecycle for RM-led acquisition and relationship growth
• Customer 360: Household mapping, relationship graphs, interaction timeline, preferences, risk profile, mandates
• RM 360 + Book of Business: AUM, revenue, net flows, product mix, client health, tasks, pipeline, servicing load
• Holdings Analytics: deep portfolio insights acrossMF/ETF/equity/bonds/PMS/structured/ alternates
• Model Portfolios: centrally defined models + suitability mapping + drift detection
• Recommendations & Rebalancing: portfolio review workflows, proposal packs, approvals, and execution handoff
• Omni-channel Servicing: governed service requests across email/CTI/WhatsApp/web/app/chatbot with SLAs
• Backoffice Integration: holdings/transactions/ledger/order status/statement generation via Miles/Wealth Spectrum
• AI-first Productivity: Einstein/Agentforce for scoring, summarization, next-best-actions, and assisted servicing
• Analytics & Governance: MIS dashboards for AUM, flows, pipeline, adherence, service SLAs, and compliance

• Relationship and portfolio context is spread across backoffice screens, Excel trackers, emails/WhatsApp
• RMs lose time on manual portfolio preparation, limited insight into client holdings and drift
• Weak governance for lead routing, opportunity stages, and service execution
• Low visibility into client health, wallet share, cross-sell potential, and churn risk
• Inconsistent proposal quality (pitch decks, product notes, suitability), causing conversion leakage
• Service experience inconsistent: no unified ticketing, SLA enforcement, or customer interaction timeline

Salesforce FSC + Sales Cloud + Service Cloud is the system-of-work for client engagement and servicing, supported by:

1. FSC Core Data Model

• Person Accounts, Households/Groups, Relationships, Interaction Summaries
• Financial Account / Holdings context (read/replicated or virtualized based on design)

2. Sales Cloud Workflows

• Lead & Opportunity management, activities, pipeline governance, campaign influence

3. Service Cloud Workflows

• Case management, omni-channel routing, SLAs, escalations, Knowledge base

4. Backoffice / System-of-Record Integrations (Miles / Wealth Spectrum / OMS/DP/Payments)

• Holdings, transactions, valuations, ledger, order status, statements, corporate actions, KYC status

5. Einstein + Agentforce AI Layer

• RM assist, Sales agent, Service agent automations with guardrails and audit trail

6. Analytics Layer

• RM dashboards, Branch dashboards, Leadership MIS; optional Data Cloud for advanced segmentation/propensity

Module 1 — Lead Intake, Routing & Lead-to-Client Conversion

Goal: high quality intake and fast RM assignment for HNI/UHNI leads.

Lead Intake Sources (Typical):

• Bulk uploads (events/partners/branches), API ingestion (web/app), referrals, call-center leads
• Third-party lead sources (campaigns, partners, affiliates)
• Manual creation by RMs for self-sourced leads

Routing & Assignment (Wealth-Specific):

• Rules by city/branch, AUM potential, segment (HNI/UHNI), language, product desk, RM capacity
• Named account overrides (existing household relationship / referrals)
• SLA-based acceptance (auto-escalate/reassign if untouched)

Qualification Governance:

• Stage Gates: profile completeness, risk appetite capture, initial discovery, documents requested
• Disposition Framework: qualified, nurture, disqualified (reason codes)

Module 2 — Opportunity Management for Wealth (Multi-asset)

Goal: standardize RM pipeline and track conversion across products.

Opportunity Patterns:

• Investment opportunity (new allocation / incremental)
• Switch / Rebalance opportunity (existing holdings optimization)
• Consolidation opportunity (bring external assets)
• Retention opportunity (save churn, resolve dissatisfaction)

Multi-Asset Product Support:

• Equity: direct equity basket, ETF allocations, thematic ideas
• Debt: bonds/NCDs, fixed income ladders
• MF: SIP/lumpsum, goal-based investments
• PMS: onboarding + mandate + model mapping
• Structured Products: suitability + risk disclosures + approvals
• Alternates Distributed Via Wealth Desk: AIF/REIT/InvIT/private credit (as per firm strategy)

Opportunity Governance:

• Mandatory suitability and risk alignment checkpoints
• Approval workflows for exceptions (fee waivers, structured products, alternates)
• Proposal pack generation and version control (pitch deck + investment rationale)

Module 3 — Customer 360 (FSC) for HNI/UHNI

Goal: one view of the client and household to drive personalized engagement.

• Person Account as client master; mapped to Household / Family group
• Relationships: family members, entities, nominees, introducers, CA/wealth advisors (as allowed)
• Interaction Timeline: meetings, calls, emails, WhatsApp/chat transcripts, servicing cases
• Key Flags: VIP level, grievances, high-risk servicing alerts, churn risk indicators

Module 4 — RM 360 and Book of Business

Goal: RM cockpit to run the business daily.

Book of Business Essentials:

• AUM (total + product-wise), net flows, revenue, brokerage/fee metrics (as available)
• Client Segmentation: HNI/UHNI, lifecycle stage, potential, engagement score
• Pipeline Summary: open opportunities, stage aging, expected closures
• Service Summary: open cases, SLA risks, escalations, repeat issues
• Productivity: meetings, proposals sent, conversions, follow-ups due

Manager Views:

• Team Book of Business rollups, RM benchmarking, leakages, pipeline hygiene, service SLA compliance

Module 5 — Holdings, Portfolio Analytics & Deep Insights

Goal: convert backoffice data into actionable insights for RMs and clients.

Holdings Views (Integrated from Miles/Wealth Spectrum):

• Consolidated holdings across MF/ETF/equity/bonds/PMS/structured/alternates
• Cost vs current value, XIRR/returns, allocation by asset class and issuer/sector
• Concentration risks, credit quality mix (for debt), equity sector/style tilt
• Cash/ledger snapshot and pending corporate actions (where available)

Analytics Outputs (Examples):

• Asset allocation vs target allocation (per risk profile/model)
• Drift detection and “why drift happened” (market movement vs flows)
• Exposure overlaps (same underlying across MF + direct equity + PMS)
• Product risk flags (duration risk, credit risk, liquidity risk, concentration)

Module 6 — Model Portfolios, Suitability & Rebalancing Workbench

Goal: operationalize advisory at scale while keeping RM ownership.

Model Portfolio Engine (Wealth-Specific):

• Central model definitions by segment (HNI/UHNI) and risk profile (Conservative/Balanced/Growth)
• Cost vs current value, XIRR/returns, allocation by asset class and issuer/sector
• Model Components: MF/ETF baskets, equity baskets, bond ladders, PMS sleeves, alternates sleeves
• Suitability mapping rules and constraints (client exclusions, issuer caps, sector caps)

Rebalancing Workflow:

• Trigger: drift threshold breach, market events, client goal change, cash inflow
• Create “Portfolio Review” record → propose actions (switches, adds, trims)
• Approvals where required (structured products, alternates, fee exceptions)
• Generate Proposal Pack: rationale + recommended changes + expected impact + disclosures
• Hand-off to execution desk / straight-through execution (based on operating model)

Module 7 — Recommendations & Proposal Pack Automation (RM Enablement)

Goal: consistent, compliant, fast recommendations for RMs.

• Central repository of product notes, house views, model rationale, risk disclosures
• “Suggested recommendations” by segment and portfolio gaps (with guardrails)
• Pitch deck and proposal templates with auto-filled client context and charts
• Versioning + approvals (so only compliant content goes out)

Module 8 — Customer Servicing (Omni-channel Service on Service Cloud)

Goal: unify service requests without breaking RM-led relationship experience.

• Channels: Email-to-Case, CTI, WhatsApp, web/app tickets, website chatbot (KB-first)
• Case Taxonomy: service requests, statements, profile updates, order inquiries, payment queries, complaints
• SLAs: service TAT per request type; escalations; controlled closure reason capture
• RM + Service Collaboration: RM visibility into client cases; “RM assist” tasks for VIP clients

Straight-Through Service Requests Via Backoffice:

• Statements (ledger/holdings/capital gains/contract notes)
• Profile updates (bank/contact/address with maker-checker)
• Order/payment inquiries (status, payout issues, margin blocks)
• Ticket status sync back to customer channels
• Hand-off to execution desk / straight-through execution (based on operating model)

Module 9 — Backoffice Integrations (Miles / Wealth Spectrum / Similar)

Goal: ensure Salesforce reflects the truth while backoffice executes.

Integration Principles:

• Backoffice remains system-of-record for holdings/ledger/orders
• Salesforce is system-of-work for engagement, proposals, service workflows, and approvals
• Integration layer supports retries, reconciliation, audit logs, and a sync call backs
• Suitability mapping rules and constraints (client exclusions, issuer caps, sector caps)

Typical Interfaces:

• Client master + KYC status sync
• Holdings/transactions/valuation feed (scheduled + on-demand)
• Order initiation / status updates (if supported)
• Statement generation requests + document links
• Limits/margin/payout status lookups (as applicable)

Module 10 — Einstein / Agentforce AI Use Cases (Wealth-Specific)

Goal: increase RM productivity and improve service quality with guardrails.

RM / Sales AI (Agentforce)

• Lead scoring for HNI/UHNI based on source, potential, engagement, profile completeness
• Meeting Prep Briefs: summarize household, holdings, prior interactions, pending service issues
• Conversation Summaries (Calls/Meetings/Emails): capture outcomes, objections, next steps
• Next-Best-Action: propose follow-ups, content to share, portfolio review triggers
• Churn Risk Signals: repeated service issues, drop in engagement, negative sentiment

Advisory / Portfolio AI (Guardrailed)

• Portfolio Gap Insights: concentration risk, drift, overlaps, under-allocation flags
• Rebalancing suggestions aligned to model portfolio constraints (recommendations as “suggested”, RM-approved)
• Explainability Drafts: plain-language rationale for recommended changes and disclosures

Service AI (Agentforce)

• Sentiment detection for emails/chats and escalation triggers
• Auto-classification of service requests + routing suggestions
• Draft responses using Knowledge + case context (agent review mandatory)
• Breach prediction and supervisor assist for backlog management

• RM Dashboards: AUM, flows, client health, opportunities, tasks due, service risks
• Manager Dashboards: team BoB, conversion funnel, pipeline hygiene, productivity, SLA compliance
• Leadership MIS: AUM growth, product mix, revenue, net new money, churn, segment performance
• Advisory Analytics: model adoption, drift distribution, recommendation-to-execution conversion
• Service Analytics: channel volumes, SLA, escalations, repeat drivers, KB deflection

• Role-based access: RM, SRM, branch head, service agents, product desk, compliance
• PII controls, audit trails for approvals and communications
• Suitability disclosures and “reason capture” for exceptions (especially structured/alternates)
• Controlled content approvals (research notes, pitch decks, templates, KB)

We recommend a phased implementation for immediate adoption and ROI visibility.

Phase 1 — Wealth CRM foundation (FSC + Sales Cloud)

• Customer 360, household mapping, lead/opportunity, RM 360 + BoB dashboards, activities, basic integrations (client master + holdings snapshot)

Phase 2 — Service Cloud omni-channel servicing

• Cases, SLAs, chatbot (KB-first), STP for statements/inquiries/profile update governance

Phase 3 — Portfolio intelligence & advisory workflows

• Holdings analytics, model portfolios, portfolio review & rebalancing workbench, proposal packs, approvals

Phase 4 — Agentforce automation + advanced analytics

• AI scoring, summaries, next-best-actions, churn risk, SLA risk prediction, continuous optimization