Internship: Agentic AI for financial investigation and management reporting
ELCA
Job Description Start date: February 2027 • Duration: 6 months
Please include your latest academic transcripts with your application. Applications submitted without transcripts will not be considered. Monthly analytical financial reporting is a critical process for business steering. Today, the production of management reports for each Business Unit remains highly manual, requiring data collection, reconciliation, validation, investigation of unexpected deviations, and interaction with business stakeholders across multiple systems. As a result, reports are typically available around 7 working days after accounting close. The objective is to reduce this lead time, enabling Business Owners to take corrective actions sooner and allowing financial analysts to focus more on business
partnering and leadership activities rather than data consolidation and investigation. Recent advances in Agentic AI open the possibility of creating a Financial Investigation Agent capable of analyzing
information from multiple enterprise systems, identifying the root causes of financial variances, validating figures,
reconciling inconsistencies, and generating evidence-based explanations. Objectives This internship explores how Agentic AI can support financial controlling and management reporting while maintaining the level of accuracy, traceability, and trust required in a finance environment. The following activities are foreseen:
Please include your latest academic transcripts with your application. Applications submitted without transcripts will not be considered. Monthly analytical financial reporting is a critical process for business steering. Today, the production of management reports for each Business Unit remains highly manual, requiring data collection, reconciliation, validation, investigation of unexpected deviations, and interaction with business stakeholders across multiple systems. As a result, reports are typically available around 7 working days after accounting close. The objective is to reduce this lead time, enabling Business Owners to take corrective actions sooner and allowing financial analysts to focus more on business
partnering and leadership activities rather than data consolidation and investigation. Recent advances in Agentic AI open the possibility of creating a Financial Investigation Agent capable of analyzing
information from multiple enterprise systems, identifying the root causes of financial variances, validating figures,
reconciling inconsistencies, and generating evidence-based explanations. Objectives This internship explores how Agentic AI can support financial controlling and management reporting while maintaining the level of accuracy, traceability, and trust required in a finance environment. The following activities are foreseen:
- Process analysis and stakeholder interviews: understand the current reporting process, identify bottlenecks, and capture how controllers and business managers investigate financial deviations.
- Literature review and state of the art: study recent research on Agentic AI, trustworthy AI, financial analytics, and human-AI collaboration.
- Agent design and prototyping: design and implement a prototype capable of analyzing data from multiple systems, identifying significant variances, investigating potential causes, and generating traceable explanations.
- Validation and evaluation: compare AI-generated analyses with expert controller assessments and measure accuracy, trustworthiness, and potential effort reduction.
- Recommendations and roadmap: define how AI-assisted financial investigation and reporting can be industrialized within the organization.
- A dynamic and collaborative environment with experienced finance, data, and AI professionals
- The opportunity to work on a high-impact and highly visible business challenge
- Exposure to Agentic AI, enterprise data platforms, and financial analytics
- Master student in Computer Science, Data Science, Data Engineering or similar field
- Interest in AI, Large Language Models, and agent-based systems
- Programming skills (Python, Java)
- Strong analytical and problem-solving skills
- Interest in business analytics
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