Digital Transformation of Travel Expense Management in the Banking Sector: Implementation Experience and Economic Effect Assessment

The article examines digital transformation of travel expense management using a large Russian commercial bank as a case study. Key bottlenecks of the traditional process are identified: employee time per advance report — 3.5 hours, approval period — up to 30 days, manual booking error rate — 12%. A full automation model is developed via direct API integrations of the corporate system with a travel management company and a taxi aggregator. The TDABC method is applied to calculate labour costs. The architecture is designed to close up to 90% of advance reports without employee or accountant involvement; at the current implementation stage the actual share achieved is 30%: integrations do not yet cover all trip types and routes (e.g. regional transfers or group check-in by list at offsites, team-buildings, conferences and coworking events are still processed manually), and not all legal entities (subsidiaries) have been migrated to the new system; the share is growing as coverage expands. Processing cost per trip decreased by 58.9%; once the target automation share (90%) is reached, the projected total net annual economic effect is estimated at 177.9 million roubles (at prices of the study period). Practical recommendations are provided for scaling the model to subsidiary companies, along with directions for further development (AI-based travel-policy compliance verification, integration with navigation services).