AI Solutions
- A framework for trustworthy AI in the insurance environmentIn the insurance industry, the push for trustworthy AI is becoming increasingly significant, driven by regulatory bodies and consumer expectations for transparency and fairness in automated decisions. To align with EU guidelines and specific insurance industry regulations from EIOPA and BaFin, insurance companies are advised to adopt frameworks that ensure… Read more: A framework for trustworthy AI in the insurance environment
- Recurring savings through global standardisation of credit workflowTechData, a wholesale company with a revenue of $35 billion, implemented a global solution to standardize credit management workflows, leading to significant savings and efficiency gains. By integrating a system that automates credit scoring, monitoring, and currency conversion for financial reporting, the company achieved a 120% improvement in credit department… Read more: Recurring savings through global standardisation of credit workflow
- Utilising synergies: one solution for all savings banks. Automation of the loan application processGuideCom AG collaborated with Buildsimple to transform the time-consuming manual credit application process at Sparkassen, reducing processing time per transaction from over 10 minutes. By utilizing AI to automate document handling such as ID verification, payroll, and tax documents, the solution integrates seamlessly into GuideCom’s service cockpit via standardized APIs.… Read more: Utilising synergies: one solution for all savings banks. Automation of the loan application process
- Automating Information Extraction with Named Entity Recognition and LLMsOur project focused on automating the information extraction process from various data sources such as textual documents and database tables, utilizing Named Entity Recognition (NER) and advanced Language Models (LLMs). The main goal was to create an automated solution that could efficiently extract relevant information using NER and enrich metadata… Read more: Automating Information Extraction with Named Entity Recognition and LLMs