← All case studies

Banking & Insurance · CRM · Regulated Financial Services

Dynamics 365 CRM in banking and insurance

These were not standard CRM rollouts. Each engagement was shaped by the regulatory complexity, data segregation requirements, and approval layers that define financial services in Italy. Delivered at Avanade, Capgemini, and as independent consultant — always with hands-on architectural and delivery leadership.

5+
CRM implementations
Banking & Insurance
Core sectors
Enterprise
Scale

Clients

Banking / Wealth Management

Banco Mediolanum

Italy's largest network-based wealth management bank, with thousands of financial advisors operating across the country. The CRM implementation had to support the full advisory lifecycle — lead management, opportunity tracking, regulatory reporting — while integrating with core banking systems and respecting the strict data segregation between advisory network, operations, and compliance. Custom Power Apps extended the platform to field advisors on mobile.

Digital Banking / Fintech

illimity Bank

A digital-first bank focused on SME lending and distressed credit. The CRM architecture had to accommodate complex lending workflows with custom Dataverse entities, integrated with the bank's proprietary credit scoring engine. Being a natively digital organisation, the implementation moved fast — but regulatory constraints on data handling and decision auditability were the same as any traditional bank.

Insurance

Unipol

One of Italy's largest insurance groups. Dynamics 365 Customer Service deployment for claims management and policyholder engagement. Omnichannel integration — email, phone, web chat — with SLA-driven routing and Power BI operational dashboards. The challenge was not the technology but the organisational complexity: multiple business units, each with its own approval layers, compliance requirements, and legacy system dependencies.

Banking-grade implementation context

These were not standard CRM rollouts. Each engagement required:

  • Compliance-aware data architecture with segregation between front office, risk, and operations data
  • Integration with core banking and regulatory reporting systems
  • Audit-trail requirements aligned with internal control frameworks
  • Change management across regulated business units with multiple approval layers

This is the operational context that shapes how we approach every AI or data project in financial services — governance is not a feature added at the end, it is the starting constraint.

Why this matters for AI projects

The governance patterns we implemented in these CRM engagements — role segregation, audit trails, approval gates, data compartmentalisation — are the same patterns required for AI agent systems in financial services today. The technology has changed from Dynamics 365 to LLMs and agentic workflows, but the constraints have not: who authorised this action, on what data, with what model, and is the log immutable. Our financial services experience means we design AI systems that meet these requirements from day one, not as a retrofit.

Technologies used

Dynamics 365 SalesDynamics 365 Customer ServicePower PlatformPower AutomatePower BIAzure Active DirectoryDataverseAzure Integration Services

Let's talk about your project

AI infrastructure to build, a legacy system to modernise, or an ERP to connect to the future? Get in touch.

Start the conversation →