Kooperativa and ČPP: AI underwriting tool "Data Digger" turns a company ID into a structured risk report (Built by BigHub)

Kooperativa and Česká podnikatelská pojišťovna (ČPP), the two Czech insurers of Vienna Insurance Group, worked with Prague-based AI firm BigHub to build Data Digger, an AI-powered underwriting intelligence tool for commercial insurance. Per the project team, administrative activity can consume up to 40% of the underwriting process, as underwriters collect data by hand from public registers, company websites and property records before they can begin assessing risk. "We perceive BigHub as a true expert who brings functional and well-thought-out solutions," said Radek Starosta, Director of the property and liability insurance department at Kooperativa. The problem was fragmentation: underwriters had to gather and validate information across many internal and external systems, assessment quality depended on individual experience, and inconsistent data gathering raised the risk of underinsurance and of missed risk signals. Data Digger starts from a single input, the Czech company registration number (IČO). From it, the system automatically retrieves and consolidates data from business registers, company websites, insolvency registers, land-registry (cadastral) records, property valuation services and public media, then structures it into a standardised underwriting report covering company information, financial indicators, property details and flagged risk factors. For property insurance it combines cadastral data with automated building valuation to give a more consistent view of insured asset values. Final underwriting decisions remain with human underwriters. The solution was delivered in three months on Azure OpenAI and Azure Storage, with LangChain, Tavily, FastAPI, TypeScript and React. BigHub reports expected benefits rather than measured results: more consistent risk evaluation, reduced underinsurance risk and less manual data gathering. Data Digger won the VIG Xelerate Audience Award 2026 among innovation projects from across Vienna Insurance Group. As of the case study, Data Digger is progressing from demonstration and validation toward production deployment, with property insurance as the initial focus. Planned next steps include additional external data sources, flood and catastrophe risk data, claims history integration, more advanced risk scoring, and broader rollout across other insurance products and VIG Group companies.