Founded in 1831, Generali is celebrating 190 years as one of the largest global providers of insurance and asset management services. During that time, the Italian company has gained a reputation as a forward-thinking lifetime partner to its customers. As it charts a path for continued success over the next 190 years, Generali’s digital transformation is at the forefront of a strategy that puts the customer at the heart of the company’s goals.
Group Head of Data Science, Alessandro Bonaita, is leading Generali’s international team of data scientists, working from one of its Head Offices in Milan, supporting the sustainable and responsible adoption of analytics and Artificial Intelligence (AI) in all the regions and countries where the group operates. “Our strategic task is to steer and support our many business units, in order to create tangible business benefits by incorporating AI in all of our business processes,” explains Bonaita.
“We work very closely with them to identify the most profitable use cases for AI and help them to prioritise their analytical initiatives so we can support the development of AI solutions, directly or by building local capabilities. We also contribute to develop the technological and methodological convergence of AI practices, leading the scale up of AI solutions through a constant monitoring of local implementation plans and the development of re-usable AI assets.”
Creating value with AI
Bonaita joined the company in 2016 when Generali began the first strategic cycle of its AI journey by creating awareness of, and appetite for, analytics. “A first central function was created at group level to disseminate and evangelise through the delivery of successful AI initiatives, working on all the steps of the insurance value chain and in all the regions where we operate,” he recalls. “During this period, we demonstrated the value of AI by focusing on high impact use cases, where the financial return was clear and relevant, and we also supported the creation of the first local analytics teams across our countries of operation.”
A second strategic cycle began in 2019, when the goal shifted to consolidate and reinforce these results along three strategic pillars: People – having analytics capabilities available for all the business units of the Group; Value – introducing a rigorous approach to the calculation and monitoring of AI’s financial benefits to support further initiatives and investment; and Execution – launching a global program to accelerate the adoption of AI solutions in production with real impacts on business processes.
“The fundamental point of success of these plans was the alignment between our analytics & AI strategy and our ‘Lifetime Partner’ strategy, with the final goal to create tangible benefits for our customers,” asserts Bonaita. “We used robotics and AI to build totally personalised rehabilitation and diagnostic paths enabling services that can evaluate a patient and create personalised treatments that can be objectively measured, but also for the prediction and reduction of risk, for example instances of falling among the elderly. We also developed AI-powered chatbots that can fast-track claims allowing the client to directly upload documents and photographs via WhatsApp, assessing in a short time the consistency of the reimbursement and delivering always available, fast and efficient customer service.”
Reaping the rewards of a five-year plan
Generali deployed a structured approach to accelerate the activation of local AI teams serving multiple global business units. “First, in collaboration with HR, we designed a clear organisational model defining roles, ways of working, team sizing and mobilisation, and sourcing levers, in order to promote the consistency of AI people practices,” explains Bonaita. “We facilitated the reuse of best practices and the synergies between business units in terms of job profiles and training programs.”
Bonaita’s team worked on upskilling Generali’s employees on these new topics, with approaches to meet the target population. “In partnership with the Polytechnic of Milan we designed and launched an internal academy offering a dedicated training path for upskilling that has seen 150 new data scientists graduate at Generali,” he adds. “But we also developed data literacy initiatives for non-technical people in order to increase their awareness and knowledge of data and AI topics so that they could effectively communicate and leverage the work of our data scientists.”
Additionally, the creation of centres of excellence, such as the one for Smart Process Automation, offer specialised services to multiple business units across the group which lower costs while maximising the convergence and reusability of AI solutions.
Delivering ROI with AI
A rigorous approach to the calculation and monitoring of AI’s financial benefits is supporting investment in further initiatives for Generali as the group evolves from a laboratory to a factory approach. Bonaita notes that after the first phase of excitement at the opportunities AI can bring, it’s important to have a clear idea of its benefits
and how they align with a company’s strategic plan.
“If you don’t start to calculate benefits in a rigorous way, the main risk is that you will never leave the laboratory approach, working on lots of proof of concepts but without any real impact on business processes,” he says, highlighting the need to identify the top priorities and where AI can contribute to the achievement of these goals.
“Meeting expectations with the additional capabilities provided by AI is a hard and time-consuming task with many reiterations, for which we must learn the language of the business, its processes and the logic behind the traditional role of an analytics team. Together with the standing developed from previous successful initiatives, AI can become a credible player within the company with commitment from all lines of the business. It’s crucial that AI is seen by the business as an additional lever it has to reach strategic goals.”
Accelerating global AI adoption
In line with the third pillar of its analytics & AI strategy, Execution, Generali wanted to ensure local AI teams adopted a robust and effective way of working for AI use cases implementation, to successfully deliver local roadmaps. “We first provided AI teams with best-in-class standards to plan and govern AI implementations end-to-end from design to production,” says Bonaita. “Then we prioritised their AI use cases into a local acceleration roadmap, identifying the enablers and investments required. This led to the selection of the top priority and the translation of the roadmap into a local project plan with a defined budget. Finally, we supported these top priority use cases with both internal and external centres of excellence. This means the creation of mixed teams with local and global data scientists but also with external contribution for specific new topics including specialised services such as Robotic Process Automation (RPA) for AI teams in 50 countries.”
A sustainable data culture
Supporting the notion that data is a shared equity, Generali was the first insurance company to join Stanford University’s international initiative for ‘Responsible Digital Leadership’ in the financial sector, operatively supporting a project to identify and describe ethical dilemmas related to the use of technology and the processing of data. “We are also active contributors on these topics in several international groups, such as the Geneva Association, where we have supported the definition of guidelines for the responsible adoption of AI in insurance,” adds Bonaita. “I’m part of the Insurtech working group in Insurance Europe that recently analysed the legislative proposal on AI made by the European Commission to express the insurers’ point of view.”
Generali achieved first place as global innovator at the 2020 EFMA innovation in insurance awards. ‘Innovation & Digital Transformation’ is a key strategic pillar at Generali where, during its last strategic cycle, the company invested €1bn across initiatives triggering a huge acceleration in the digitalisation of the group’s processes. Its vision, ‘Innovation Everywhere for Everyone’ means innovation is not limited to its 15+ dedicated teams and 100+ Champions across one global community, but is embedded in the daily efforts of Bonaita’s 70,000 colleagues across 400 companies in 50+ countries. The goal is to deliver world class experiences for customers, agents and employees by focusing on improving both internal processes and the customer experience by leveraging both external and internal innovation.
This has not only seen the implementation of AI solutions but also the roll out of IoT. “The global pandemic has accelerated the digitalisation process and the use of IoT has proven essential in addressing this health emergency,” says Bonaita. “In our current ‘Generali 2021’ plan, IoT plays a fundamental role: it has allowed us to digitise our network and the relationship with our customers, enabling them to interact with the company through apps and web services.”
But you can’t be innovative without being agile and you can’t be agile without automation, reckons this seasoned data scientist. “When we talk about ‘smart automation’ we are referring to technology but also how we process expertise and redesigning, which is fundamental to accelerate the digital transformation transition that Generali started several years ago. In 2020 we launched a dedicated Centre of Excellence that launched several automation initiatives all over the world, also supporting local development.
“However, for a post-pandemic recovery, technology alone isn’t enough. Companies must further commit themselves by prioritising their client’s changing needs and, at the same time, support their employees and their training to help them deal with the new challenges in the best possible way.”
Partnering for success
“My team’s role developing a global AI function, steering and supporting our business units, requires us to always be up to date with the latest trends,” pledges Bonaita. “It’s why we’ve selected some highly specialised partners to explore and implement the latest technological breakthroughs… From a research point of view, we became a co-founder of the Data Science & Artificial Intelligence Institute at Trieste. The goal is to create a centre of innovation to generate research and new business opportunities based on data science and AI. In particular, the Institute intends to carry out world class research and encourage knowledge transfer in machine learning and AI, pooling young talent to foster new collaborations via PhD and master programs, dissemination activities, as well as upskilling and reskilling opportunities for our employees through our ‘We LEARN’ initiative. This collaboration will enable us to boost our exploration of innovative fields such as quantum computing, computer vision and explainable AI.
“From an operative point of view, we are always trying to accelerate the concrete delivery of our AI initiatives through the contribution of reliable partners that can support our business units internationally. We have successfully collaborated with Data Reply to operationalise advanced analytics and AI-powered data services. From a technological point of view, we have strategic partnerships with Microsoft and Google to leverage their cloud platforms for innovative solutions.
The art of being a data scientist
“A good data scientist embeds with business teams,” reflects Bonaita. “Utilising a task-driven approach, typical of a code developer doesn’t allow you to embrace discovery with an open and flexible style. We are in the early stages of AI adoption, where most people don’t fully understand how they can benefit from machine learning even though many opportunities exist. Data scientists must be ready to propose solutions spending time working closely with core business teams to gain an understanding of their biggest priorities what data is most important to them, and what information could help them.”
Bonaita believes the ability to understand decision-making processes – how, when, and by whom they are made – is vital to best focus a company’s efforts on data projects that inform critical decisions. “The ability to find valuable data you can collect and embed with business teams should provide a good idea of what data the company already has, how it’s being used, and what is needed to move forward. A good data scientist should be able to make these connections to encourage a data-driven culture, adding value to the business by showing how using data to make decisions benefits all of its teams.
“Ultimately, technologies can enhance insurance by allowing us to generate powerful insights to make better decisions and identify growth potential for Generali, but above all, to satisfy our customer’s needs and provide them with assistance, aid, and trust.”