As the hype around AI use cases in the insurance sector continues to gather momentum, top IT leaders understand it’s their approach to data management that really counts.
From underwriting policies to processing claims, insurers rely on vast amounts of data to make informed decisions, manage risk and deliver value to customers. But ensuring your entire organisation has access to secure, readily accessible data insights is usually easier said than done.
Here we explore why a robust data strategy is so critical to compete in today’s insurance market, as well as the key trends and challenges facing those responsible for managing company data.
Why is data management so important for insurance firms?
Data management in insurance has evolved far beyond storing information and records – and there are huge advantages for those who see data as a strategic enabler, rather than just an asset.
Industry leaders are already using data to inform decision-making processes, improve customer relationships and maximise operational efficiency across core processes and day-to-day workflows. It provides new ways to personalise customer offerings, and to assess and price risks more effectively.
In many cases, an outdated data infrastructure is the biggest factor holding insurance businesses back from the next phase of their digital transformation. Firms need to overcome legacy issues, data silos and legal barriers which prevent data sharing and advanced analytics if they are to unlock their own operational potential.
There’s also the challenge of managing compliance. Heavy regulations put a lot of pressure on IT leaders to maintain precise records and data security standards. If you can’t trust your data management strategy, the task of regulatory reporting or preparing for an audit will be a far more stressful experience.
Which data points should you be tracking?
Risk assessment and pricing
Insurers rely on data to assess risks and set premiums. Accurate, well-organised data makes it easier to identify claim patterns and detect fraud, which reduces the likelihood of losses further down the line.
Underwriting data
Information in the form of health records, credit scores, property details, economic trends and other risk factors is crucial to evaluate risk and determine policy terms – all of which supports underwriters to price fairly and avoid high-risk policies.
Policyholder information
Customers have come to expect slick, personalised experiences as standard when dealing with businesses. By collecting and organising personal information and demographic data, insurers can deliver tailored products and a better-tailored service for their clients, which leads to greater customer satisfaction.
Regulatory data
Proper data management helps insurers meet compliance requirements, avoid fines and maintain trust with regulators and customers. Audit records and compliance reports should be quick to generate, so firms are always ready to demonstrate adherence to FCA, PRA or GDPR guidelines.
Data strategy in action – BMS Group
Paul Jackman, CTO at BMS Group
“True agility and efficiency in an insurance firm comes from investing in data knowledge and understanding. It’s not enough to implement the latest analytics tools – we also need to ensure the underlying data is of the highest quality and that our people have the skills to extract meaningful insights. In my experience, the businesses that empower their users to self-serve, pick up their own data and do their own analytics are the ones that truly thrive.
“Part of the challenge is avoiding disconnected initiatives that can quickly lead to data silos, quality issues and other challenges that undermine the potential benefits. We’re working to establish a robust data strategy and governance framework that ensures scalability and sustainability.”
Tools to support insurance data management
- Data integration tools – Insurance firms often deal with data silos, where information is scattered across multiple systems. Data integration platforms help consolidate this data into a unified view.
- Business intelligence platforms – BI and analytics tools like Power BI help insurers turn raw data into actionable insights, enabling better decision-making and strategy development.
- AI and machine learning – AI-powered solutions use historical data to inform risk assessment and detect fraudulent claims. Tools like Copilot now also support information workers by automating all, or part of, a wide range of operational tasks. Make sure to read our blog on AI in insurance for more detail on this.
- CRM systems – Being able to funnel client data directly into a CRM is key to track interactions and personalise customer experiences. Salesforce and Hubspot and prime examples.
Don’t skimp on data management training
Many firms are quick to invest in the latest digital tools without necessarily preparing their people to hit the ground running from launch.
Staff need to know how to analyse data to extract meaningful insights and interpret key trends, so they can then pass on this information to other stakeholders in a timely, organised manner.
Establishing data integrity standards early is key. Employees should be comfortable in collecting, entering and managing data correctly, as well as being able to spot inaccuracies or inconsistencies against pre-defined criteria and formatting requirements.
Any mishandling of data can have serious ramifications for compliance, which means regular training around data protection and best practices should be conducted to minimise liabilities and demonstrate proactive measures have been taken to limit data management risks.
Delivering data transformation for your firm
Effective data management has become fundamental to the success of modern insurance firms across the Lloyd’s market and beyond – and the frontrunners are already setting themselves apart in terms of accuracy, operational efficiency and performance.
For those still playing catch up, the task of uniting data silos and getting the right infrastructure in place to deliver secure data-driven insights should be seen as a major strategic priority. It’s also crucial not to underestimate the time and guidance required to educate staff on handling sensitive information securely and ethically, and to recognise potential security risks and take preventative measures.
Ultimately, delivering data transformation for your firm isn’t just about the technology; it’s about empowering your people, breaking down barriers and turning insights into actions that drive your business forward for years to come.
