Habibi Javanbakht, Aydin orcid.org/0009-0005-1371-8120 AI Agent–Enabled Case Scoring and Assignment: Strategic Impact on Customer Lifecycle Management in Regulated Financial Services. Masters thesis.
Abstract
This consultancy project investigates the role of artificial intelligence (AI) in customer service case management within the financial services sector, focusing on a stock brokerage firm with CRM integration. The study explores how AI-driven case scoring and automated assignment can improve operational efficiency, service quality, and compliance in regulated environments. A mixed- methods design combined an online survey of industry practitioners (n=150), 12 semi- structured interviews with CRM managers, IT specialists, and compliance officers, and secondary performance data. Findings indicate that AI-enabled case routing enhances service-level agreement (SLA) compliance and reduces response times, while also surfacing concerns about data privacy, transparency, and employee trust. Both survey respondents and interviewees acknowledged AI’s benefits but stressed the importance of explainable algorithms, governance, and effective change management to ensure adoption. The report provides actionable recommendations: a phased AI deployment supported by human oversight, robust governance frameworks to address ethical and regulatory issues.
Metadata
| Item Type: | Thesis |
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| Authors/Creators: |
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| Keywords: | Customer Relationship Management (CRM); Artificial Intelligence; Case Assignment, Service Operations; Financial Compliance; Mixed-Methods Research., AI Agent, |
| Institution: | The University of York |
| Academic Units: | The University of York > University of York Science Education Group (UYSEG) The University of York > Research Groups (York) > Centre for Leadership and Management (York) |
| Date Deposited: | 05 Dec 2025 09:24 |
| Last Modified: | 05 Dec 2025 09:24 |
| Status: | Unpublished |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:235171 |

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