Insurtech Bdeo’s CEO talks digital transformation & adoption

Julio Pernía Aznar, CEO and co-founder of Bdeo, discusses the insurance market predictions for 2023 and beyond, for digital adoption

Launched in 2017, the Spanish insurtech Bdeo was created by co-founders Julio Pernia and Manuel Moreno, when they saw a need for B2B, SaaS services in the insurance industry. Today, they work with a wide range of customers including Chubb, Generali and Admiral, to create solutions specifically for the auto insurance industry. 

We spoke to Julio Pernia, Bdeo’s CEO, to find out more about industry predictions for digital adoption over the next few months.

What’s your view of the current rate of adoption of digital transformation in the insurance industry? Is it fast enough? Or is insurance still playing catch-up?

While I believe the pandemic-induced digital transformation of the insurance industry is well underway, many insurance companies are still “playing catch-up” to reduce operational costs and remain relevant – especially as geopolitical crises, supply chain disruptions, labor shortages, and changing consumer habits continue to impact the costs of doing business. 

Over the next year, I believe we will continue to see insurance companies double down on digital transformation efforts that improve the customer experience and help them tackle a whole new set of challenges, such as insurance fraud and climate-related risks. 

Which technologies are driving the most industry-wide changes, and why?

Artificial intelligence (AI) is certainly driving the most changes in the insurance industry as companies are using it to improve customer experience, eliminate bottlenecks and automate tasks across their organisations. More specifically, I would say that “Visual Intelligence” AI technology is driving some of the most significant improvements we have seen to date – especially in claims processing.

Because visual evidence plays such a crucial role in claims processing, “Visual Intelligence” technology can help insurers remotely analyse images submitted by policyholders and resolve claims more quickly. The technology can be used to identify the texture of the damage, categorise objects or attributes, and ultimately, identify the cause of damage. For example, in the case of property claims, this could be a flood or burst pipe. For vehicle claims, it could mean identifying the parts of a vehicle that need to be fixed or replaced and calculating the cost to repair them. 

Automating claims processing with Visual intelligence technology helps insurance companies reduce the manual time spent on repetitive processes and resolve customer inquiries faster (claims can be processed in minutes rather than days or weeks). These improvements in operational efficiencies mean a better experience overall for the end customer.

What are the biggest challenges currently faced by legacy system companies that are in the process of digitising their services?

I believe insurance companies face the most challenges when they assume that digitising their services requires an organisation-wide overhaul. Digitising services “one step at a time” can make the digital transformation process much more manageable. For example, insurers can automate the most critical tasks first as a way to experiment and get feedback before making more changes or automating the following process.

Has the recent drop in investment slowed down the digital transformation process? And if so, is there a solution?

I don’t believe the recent drop in investment has slowed down the digital transformation process for too many insurance companies. In fact, we are now seeing more companies embrace digital solutions that help them cut costs and deliver a truly digital customer experience. 

What changes will we see over the next 12 to 18 months?

One significant change facing the insurance industry is the acceleration of climate-related risks. Insured losses from natural disasters have skyrocketed over the past 20-30 years. We will see the demand for solutions that can help companies leverage and embed climate-risk data into their models increase drastically. We will also see companies automate processes to be able to respond to the peak in demand in these situations.


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