Short Description

A regulated wealth management group modernized its customer and investment operations by deploying ShareCRM and embedding AWS generative AI workflows into daily CRM processes. The organization reduced information entry time by 35%, cut repetitive work by 15–20%, and improved efficiency by 50%+ in selected teams.

About the Customer

The customer is a regulated wealth management and investment services group headquartered in Australia with operations across APAC. Serving high-net-worth clients, the group manages high volumes of relationship interactions, suitability documentation, and investment opportunity pipelines. As a regulated institution, it prioritizes data security and compliance while also needing faster cross-team collaboration between client-facing advisors, investment teams, and compliance/legal functions.

Customer Challenge

As the group expanded, teams relied on multiple overseas CRM tools and fragmented workflows to manage client interactions, investment opportunities, and internal approvals. These systems were not well-aligned with local collaboration habits and often required frequent tool switching, repeated data entry, and manual reconciliation across platforms—leading to inconsistent record quality and low user willingness to keep data up to date.In financial services, inefficiency quickly becomes a governance issue. Client records, suitability documentation, and investment opportunity sources are core assets. Without a unified system and consistent capture of critical information (meeting notes, action items, risk considerations, and approvals), the customer faced growing operational overhead, reduced visibility for management decisions, and increased compliance exposure due to incomplete or delayed documentation.

Partner Solution

ShareCRM delivered a phased CRM modernization program and embedded generative AI workflows on AWS to streamline text-heavy, compliance-sensitive processes while maintaining strong governance. The solution focused on consolidating customer and investment information into a unified operating model, improving day-to-day execution for advisors and investment teams, and reducing repetitive administrative work that previously slowed decision cycles.

Key AWS services used and how they were delivered

• Amazon Bedrock powered generative AI capabilities embedded in CRM workflows—used for structured summarization, extraction, and controlled drafting in regulated processes.
• AWS Lambda orchestrated event-driven automation (e.g., triggering AI summarization after meetings or document uploads).
• Amazon S3 stored reference documents (e.g., meeting attachments, investment memos, compliance materials) used in controlled retrieval and summarization flows.
• AWSIAM enforced role-based access control and least-privilege permissions for sensitive client and project data.
• AWSKMS provided encryption controls for data protection requirements.
• Amazon CloudWatch supported operational monitoring and workflow observability.

Architecture on AWS

Generative AI workflows embedded into CRM operations

To ensure the GenAI layer solved real business pain—not “AI for AI’s sake”—ShareCRM embedded the following workflows directly into the customer’s daily CRM usage:

1. Client meeting notes auto-generation with CRM write-back After advisor-client meetings, Bedrock generates a structured summary (key discussion points, client needs, next steps) and writes it back into CRM records. This reduces manual entry burden and improves consistency of client interaction histories.
2. Client profile summarization and next-best-action suggestions Bedrock generates concise client briefs (goals, preferences, recent interactions, outstanding actions) and suggests next steps aligned with the team’s operating rules—helping advisors prepare faster and follow up more consistently.
3. Investment opportunity / product memo extraction and standardized tagging For inbound investment opportunities and product materials, Bedrock extracts key facts (thesis, timeline, constraints, risk notes) and applies standardized metadata to improve internal search and matching—reducing manual sorting and accelerating opportunity review.

Delivery approach and support

ShareCRM conducted deep requirement discovery across advisor, investment, and compliance roles, then delivered in phases: controlled migration of high-value data, rollout of core CRM workflows, and gradual expansion of Bedrock-enabled automation modules. Post go-live, ShareCRM continued iterative optimization (workflow tuning and prompt refinement) to improve output consistency and user adoption.

Results and Benefits

After deployment, the customer achieved measurable improvements directly aligned to the initial challenges: faster information capture, less tool switching and duplication, higher record consistency, and improved cross-team coordination—while maintaining a compliance-first operating posture.

Quantified outcomes

• 35% reduction in information entry time by automating client meeting summaries and structured CRM write-back.
• 15–20% reduction in repetitive work through standardized workflows plus AI-assisted drafting and summarization for recurring documentation.
• 50%+ efficiency improvement in selected teams by enabling faster client preparation, improved opportunity review/matching via standardized extraction and tagging, and better visibility through consolidated CRM records.

These improvements reduced hidden coordination costs and improved decision readiness, supporting scalable operations across client service and investment workflows.

About the Partner

ShareCRM is an AI-powered, customizable enterprise CRM provider that helps organizations connect data, people, and business processes across the customer lifecycle. Founded in 2011, ShareCRM is trusted by 6,000+ customers, employs 1,400+ people, and operates across multiple offices globally. Since 2023, the company has invested heavily in AI to advance practical AI applications in CRM.