Compete366 works with DSG on its AI-Driven Dealer Onboarding Transformation
This case study explains how Compete366 worked with DSG to implement AI-Driven Dealer Onboarding Transformation using Microsoft Copilot Studio
DSG Business Background
DSG is a UK-based car finance provider whose systems are widely used by dealerships to offer car finance options to customers. The business operates several divisions, including main dealer networks, independent dealers, prestige vehicles, direct-to-consumer (Magnitude Finance), and partnerships. All dealers undergo a rigorous approval process to ensure FCA regulation and sound trading history.
With a strong technical focus DSG has an in-house development team which delivers an innovative approach and technical expertise within the business.
DSG had previously worked with Compete366 on their migration from Google Workspace to Office 365, as well as the move of their on-premise IT infrastructure to Azure over the last few years. They also provide ongoing expert Azure and Microsoft 365 advice and guidance.
Business Challenges
The onboarding process for new dealers was highly manual, involving extensive checks for FCA regulation, trading history, and other compliance requirements. This manual approach led to inefficiencies, inconsistencies, and significant time investment from a team of around ten people, some of whom handle onboarding as their primary role, while others do so on a more ad hoc basis as part of their wider role.
The process needed to be automated in order to remove these inconsistencies and also reduce the amount of time spent completing these essential business checks.
The Solution
To address these challenges, Mark Burgess (Chief Technology Officer) initiated a project leveraging Microsoft Copilot Studio. He worked with the Microsoft AI consultants at Compete366 to support him in this challenge. As Mark comments:
“We have found Microsoft Copilot Studio and the other AI tools from Microsoft very easy to use and experiment with. When we have got stuck, we have used our regular review call with our Compete366 consultant to give us more expert advice so that we can iron out any difficulties and really deliver some value to the business through these new technologies.”
The first solution which Mark created was a guided process that streamlined onboarding tasks (this was not a fully autonomous AI agent) and walked the team members through the tasks required, with the agent completing various research elements and providing the information back to the individual team member.
Key features included:
- Integration with the Hubspot CRM system to retrieve dealer records.
- Automated checks with external databases to gather the information required for the checking process (FCA, Companies House, Credit Safe, ICO, Autotrader).
- AI-driven data retrieval and formatting for due diligence.
- Updates to the CRM record for that dealer upon completion.
- Use of Copilot agents to guide users through standardised workflows, ensuring consistency and reducing manual effort.
- The users have been encouraged to provide ongoing feedback via a Microsoft Teams channel to allow for continuous improvement and refinement of the solution.
Benefits
- Efficiency: The project has led to a significant reduction in manual checks and time spent onboarding dealers.
- Consistency: Standardised processes are now followed that ensure all dealers are onboarded using the same criteria.
- Proof of Concept: The project has also served as a prototype for DSG, demonstrating a real-world AI application and paving the way for further innovation within the organisation.
Other AI powered projects
DSG has already taken its use of Copilot Studio wider and has implemented two new autonomous agents within the development teams at DSG. These are outlined below:
Autonomous CAB (Change Approval Board) risk advisor agent
This fully autonomous agent reviews change requests using historical incident data from Azure DevOps Boards. This means that when requesting new system changes the agent looks back at previous changes made and issues logged via the ticketing system to advise on any known issues or challenges encountered before. The agent produces a structured risk assessment for any new change request based on the information gleaned from past projects. This allows for more accurate planning and avoids the team repeating past mistakes. This should have a dramatic impact on development delivery avoiding bugs and project overruns.
Sprint planning automation agent
The development team works on a two-week sprint development cycle for all projects. This agent works to calculate team capacity based on holidays and unfinished work accessing HR systems to provide much of this knowledge . It then takes this data to allow the development tasks to be prioritised and gives a much more realistic view of which tasks can be included in each development sprint.
As Mark explains:
“We have embraced the use of Microsoft’s AI toolset. The way we have approached this is with ongoing experimentation to identify areas where AI can add value, with a focus on practical, incremental improvements rather than large-scale, top-down mandates. We believe that this is the way to get maximum value from AI in the short term.”
Conclusion
DSG’s journey illustrates how targeted AI adoption can streamline business processes, improve consistency, and foster a culture of innovation. The company remains committed to exploring new opportunities for AI integration, guided by practical needs and continuous feedback from its teams.
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