Financial Services · Export Credit Insurance

AI Roadmap for a Government Export Credit Insurer

Starting point

A government-mandated provider of German export credit insurance processed audit reports and decision memos entirely by hand. Existing technology — transformer models for data extraction — covered roughly 30 data points. For the actual goal of querying complex questions against the full document corpus, there was no viable approach. On top of that came a structural knowledge-transfer risk: a demographically aging underwriting team holding years of implicit case knowledge — with no scalable access for new colleagues.

What we did

Together with the leadership team, we developed a comprehensive AI transformation strategy. Scope: process analysis, use case identification and prioritization, a 4-stage transformation roadmap, and two scenarios for building internal AI capabilities. Duration: 6 weeks. Team: 2 Principals. The result was a decision-ready strategy that served as the foundation for the leadership team's implementation planning.

Results

6 Wochen

from analysis to roadmap

4 Etappen

transformation roadmap

prioritized use cases with business case

2 Szenarien

for internal AI capability development

What we learned

In analog-driven organizations with externally governed processes, the greatest resistance to transformation lies not in the technology but in the decision-making structure. The most critical decision was use case selection: the first application must be quick to implement while also advancing multiple strategic objectives — otherwise the organization loses the project before it gains momentum.

This is the summary. How we approached it methodologically — which architectural decisions we made, what we discarded and which patterns can be transferred to other contexts — we discuss in a personal conversation.

Not because we want to sell you something. But because this depth is what our clients engage us for — and it does not belong on the open internet.