Data Ownership, Data Foundations, and AI are the Key Trends for Insurtech and Data Leaders.

This month, Insurtech and Data leaders gathered in London at the Insurance Network’s TINtech Data Jam to discuss the trends and impact of data and technology on the Insurance Market. AI remains the hot topic, and the conversation is moving from the potential of AI to the reality of implementing AI initiatives. 

From the many panels, workshops, and conversations, several themes stood out, and we wanted to share those with you. 

AI is Dominating the Insurtech conversation

AI feels like it’s in every single conversation. The conversations have shifted from how AI can help us to how AI is helping us. Insurers need to keep up with the pace of change, even though there are large questions around the implementation and use of AI. Key questions insurers are asking themselves are how many POCs should we be running? Where will AI create the biggest impact? How do we scale our AI initiatives?  Do we have our foundations in place- the data, the internal skills, processes, and infrastructure to support these new AI initiatives? 

You Can’t Skip Your Foundations

It’s been said many times that when it comes to AI, it’s rubbish in, rubbish out. But it bears repeating. Having robust and strong data foundations is non-negotiable. As organizations implement their AI projects, successful initiatives require a robust data foundation. 

Your data needs to be clean, consistent and have a context layer so that your organization both understands and trusts your data and any output from AI. Robust data foundations go beyond AI, they support data-driven decision making that helps a business to gain competitive advantage and drive value.  

Organizations also need to be realistic; data foundations aren’t a single project. This is an ongoing process that will need to be monitored and maintained as the business needs and data usage change. 

Data Ownership 

Who is responsible for the data in your organization? Is it the data team? The business user? This is a key question to answer. Data teams own the processes for the capture, storage, and governance of data, but business owners are the ones who use the data and dictate business outcomes. 

Data ownership is important, since data isn’t just a data team issue, but a business issue. Data and analytics aren’t a separate function but should be embedded as a core part of building an effective data strategy. Ensuring you have the ownership and accountability in place, will help ensure you deliver positive outcomes. 

The Human Factor 

The success of any new process or tech adoption relies on your workforce. Make sure that users not only understand what the change is, but why it is happening. You can have world-changing tech at your fingertips, but it can still fail if you don’t get buy-in from the people within your business. Bring your team on the journey, so they get used to new technologies and the changes they will bring. How people use a system or process, and whether they trust it, will make or break any technology initiative or any business initiative that you put in place. 

The insurance industry can be risk-averse, so the question must be asked: can real innovation be achieved without a shift in the culture? 

Trust 

If you want to be a data-led business, then you must trust the data that you have. The input and the output. Trust is built by understanding; your entire organization needs the same understanding of the data, its governance, and its impact on the business. Data leaders are keen to stress that success with tech such as AI and data science decision-making is based on trust.  

Working in a heavily regulated industry, trust in how you operate and the safeguards and processes you put in place is more important than ever. 

Insurance, and in particular, specialty insurance, relies on experience, market knowledge, and understanding of very complex and often unique scenarios. So, how do you mix that with automation and AI? How do you get people to trust data, to trust the systems, to trust the technology, and to trust the output? Building trust within your organization is an important goal for data leaders. 

It is a fluid and dynamic time for insurance. One where your data strategy and governance is key to driving innovation and growth.  

At DQPro, we know data is an enabler of success. We are here to support specialty insurers, who must have robust data checks and controls to deliver clean data and to drive their business goals. 

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