Case Study

From data to continuous improvement: how Unipol makes insurance processes more efficient with Process Intelligence and AI

Discover how the Unipol Group uses Process Intelligence, Artificial Intelligence, and advanced analytics to achieve end-to-end visibility of insurance processes, accelerate continuous improvement, and support increasingly data-driven decisions.

#FinancialServices
#Insurance
#ProcessIntelligence

The challenge

Improving the governance of insurance processes through complete visibility of operational activities.

The SCENARIO

Managing increasingly complex processes

To continue improving operational efficiency and provide an increasingly effective service to its customers, the Unipol Group has launched a Business Process Optimization program based on a structured and data-driven approach.

Among the main Italian insurance groups, Unipol manages processes that involve numerous business functions, heterogeneous application systems, and large volumes of data. Gaining a comprehensive view of their operations was a key element in identifying improvement opportunities and supporting faster decisions.

The journey began in the Claims, one of the organisation’s most strategically important processes. Claims management involves about 2,000 professionals and includes an operational cycle extending from initial claim intake through to settlement, including payments, recourse, and litigation.

THE SOLUTION

Process Intelligence to transform data into continuous improvement

Sprint Reply has accompanied Unipol on a multi-year journey of adopting Celonis, using Process Intelligence to accurately reconstruct the actual execution of processes and make them observable, measurable, and continuously optimizable.

The platform integrates data from various business systems and transforms it into a dynamic representation of activities, highlighting throughput times, operational variants, and bottlenecks.

The functionalities of Artificial Intelligence further enhance the value of the solution, allowing for:

  • Generating predictive insights;

  • Querying data using natural language;

  • Transforming complex information into content easily interpretable by the business.

In this way, insights are translated into targeted redesign and automation interventions, creating a continuous cycle of operational improvement.

HOW WE Did IT

From data to action

The project began with an assessment phase of business objectives and the definition of priority KPIs.

Sprint Reply then integrated and normalized data from business systems, building an end-to-end view of processes and ensuring quality and reliability.

Based on this information, it was possible to:

  • reconstruct actual flows;

  • identify bottlenecks and variants;

  • identify the causes of inefficiencies;

  • support standardization interventions;

  • introduce intelligent automations;

  • enrich decision-making systems with process-oriented metrics.

The approach allowed for the systematic transformation of data into action, making the improvement of processes a continuous activity.

The RESULTS

More control, more efficiency, better decisions

The adoption of Process Intelligence has allowed the Unipol Group to build an operational model based on continuous performance measurement and the ability to intervene quickly where necessary.

Full visibility
of processes

An accurate representation of operational flows makes inefficiencies, bottlenecks and variations immediately identifiable.

More
efficient processes

Identifying the root causes has reduced processing times and improved operational predictability.

Greater
standardization

Shared operational pathways allow for more uniform and controlled management of recurring cases.

Faster
decisions

Early identification of the most critical cases enables faster intervention and reduces resolution times.

A model of
continuous improvement

The insights generated by the platform fuel a continuous optimization process, supporting increasingly data-driven decisions.

The results obtained in the Claims area have led to the progressive extension of the initiative to other strategic processes of the Group, including Finance, Procurement, Accounts Payable and Agency Network.

Thanks to the methodological approach developed by Sprint Reply, the model is now replicable in new business domains, maintaining consistency in governance, KPIs, and improvement methods.

The already defined roadmap provides for further extension of Process Intelligence to other processes within the organization.

Article

Process Intelligence and AI in the insurance sector: from data to continuous improvement

How Process Intelligence, Process Mining, and AI help insurance organizations understand real processes, identify inefficiencies, and turn insights into concrete actions.

It is one of the main insurance groups in Europe and a leader in Italy in the Non-Life sectors (particularly in the Auto and Health sectors), with a total collection of 15.6 billion euros, of which 9.2 billion in Non-Life and 6.4 billion in Life (2024 data). It adopts an integrated offering strategy and covers the entire range of insurance products, mainly operating through the parent company Unipol Assicurazioni, UniSalute (a leader in health insurance in Italy), Linear (direct auto insurance), Arca Vita and Arca Assicurazioni (Life and Non-Life bancassurance, through the branches of BPER, Banca Popolare di Sondrio, and other banks), SIAT (transport insurance), DDOR (an insurance company operating in Serbia). It is also active in the real estate, hospitality (UNA Italian Hospitality), healthcare (Santagostino), and wine (Tenute del Cerro) sectors. The ordinary shares of Unipol Assicurazioni S.p.A. have been listed on the Italian Stock Exchange since 1990 and are included in the FTSE MIB® and MIB® ESG.

Sprint Reply is the Reply group company specialized in implementing Artificial Intelligence solutions dedicated to optimizing business processes. Our mission is to design and create solutions that address complex business problems, supporting clients in improving operational performance. Our expertise focuses on key technological areas such as: AI and Generative AI, HyperAutomation, Process Mining, and Computer Vision, with particular attention to research, development, and integration of the most innovative technologies available in the market.