The Transformative Power of AI: Leveraging Data for Smarter Insurance Decisions
The Transformative Power of AI: Leveraging Data for Smarter Insurance Decisions
By Tom Nicholls, Chief Commerical Officer
The insurance industry is experiencing a revolution, driven by the power of artificial intelligence (AI) and data analytics. Advances in AI and enhanced features and functionality in modern, scalable data platforms like Databricks are reshaping how insurers operate, offering new ways to enhance efficiency, reduce costs, and improve customer experiences.
The rapid rise of InsurTech organisations, insurance firms that have technology imbedded at the core of their business from the outset, has challenged the status quo. These firms have come to market quickly, can respond quicker to market changes and are more in-tune with their customers, allowing them to meet their needs and expectations.
Not wanting to be left behind established insurance firms are focussed on escaping their legacy technology estates, embracing enterprise-wide data solutions and intelligent AI solutions. The goal being to improve flexibility, agility and responsiveness, while delivering a clear business impact to ensure value is realised and end customers are positively impacted.
The goal for both, InsurTechs and established firms alike, is to unlock the full potential of their data.
AI is a game changer
AI is making a significant impact across various areas of the insurance business:
- Smarter Risk Assessment: AI helps insurers evaluate risk more accurately by analysing a wide range of data, from social media activity to historical claims. This means more personalised policies and better pricing for customers.
- Faster Claims Processing: AI can automate the claims process, speeding up approvals and reducing the workload for human agents. For example, AI can quickly assess vehicle damage from photos, leading to faster settlements and happier customers.
- Enhanced Fraud Detection: AI continuously monitors transactions and claims to detect suspicious patterns. This proactive approach helps insurers minimise losses due to fraud, protecting both the company and its customers.
- Improved Customer Service: AI-powered chatbots and virtual assistants provide 24/7 support, answering questions and guiding customers through the claims process. This not only enhances the customer experience but also allows human agents to focus on more complex issues.
For example, an insurance provider who can respond quicker to a broker’s enquiry is more likely to win business than one with an extended response timeline – however speed isn’t everything. The response needs to be accurate and well informed, and an accurate response means the insurer needs to correctly understand the ask, and then return an appropriate, risk considered proposal. AI can help read, interpret and action a broker’s request, pulling the necessary underlying data from internal systems to generate an accurate and meaningful response.
To do this you will need an effective cloud based data platform capability upon which you can build and run AI solutions – an intelligent data platform!
An Intelligent Data Platform is Essential
Step forward Databricks - a game-changer for the insurance industry with its Data Intelligence Platform solution. Here’s why:
- Scalability: Databricks can handle large volumes of data, making it ideal for insurers who deal with vast amounts of information daily.
- Integration: Databricks seamlessly integrates with various data sources and tools, providing a unified view of customers and operations.
- Advanced Analytics: With Databricks, insurers can apply advanced analytics and machine learning models to their data, uncovering insights and making more accurate decisions.
- Collaboration: Databricks fosters collaboration among data scientists, analysts, and business teams, driving innovation and improving outcomes.
Databricks provides the ability to bring multiple data sets together, unifying it in one central location so that previously disparate data sets can be combined and aggregated to generate new, value adding insights. The platform also democratises access to the data empowering more people in the business to take ownership for accessing and gaining insights from it, increasing the overall data literacy, and improving the level of data driven decision making across the organisation.
As if that wasn’t enough the built in AI features provide a simple path to building custom AI solutions, and for optimising the platform itself! It can help you streamline your end to end Data Science workflow, securely connect your data with any AI model to create accurate, domain-specific applications, and build effective and secure agentic AI systems.
Don’t take my word for it, here what AXA France say about how they ingested 200 terabytes and 60 data sources into Databricks, halving their data related operational costs while enabling 800 people to use date every day to make better decisions.
So, where to start!
Do you know where the high-value opportunities are for improving how you use data and AI in your business?
No – we recommend undertaking a Business Value Chain Mapping exercise to identify where in your business the opportunities are to deploy AI and / or make better use of your data. This combined with a quick assessment of your underlying data capability and technology landscape will identify where you need to start.
Yes – you need a clear value realisation plan to ensure you unlock as much value as possible as quickly as possible. It’s important to ensure you aren’t developing any ‘throw away’ solutions, and so we recommend developing iteratively, building a thin ‘end to end’ slice of the final technology solution you will need, being use case led, and value / impact focussed. This is your evolving Minimum Viable Product (MVP).
If you have already started making improvements that is great. Just remember to keep an eye on value realisation and operational costs – is the value being realised and recognised, are costs reducing, staying the same or are they outstripping the benefit being delivered? If it’s any of the latter, then a technical / use case health check could be required to course correct focus and efforts bringing your initiatives back on track.
Conclusion: Don’t get left behind
Wherever you are, and whatever you end up doing, don’t leave anything to chance. Your competitors won’t, and you can’t afford to fall behind in this race. Those with solid, scalable data foundations, and integrated, user friendly AI solutions will reap the rewards.
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