Some insights by Piotr Piekos from Future Processing, after a roundtable discussion on data handling, future trends and more.
The insurance industry, which was once stable and predictable, has been facing unprecedented changes in recent years. With rapid technological advancements, changing customer expectations and complex regulatory requirements, insurers are having to make bold choices as incremental improvements are no longer enough.
This is where data processing comes into play. By leveraging data effectively, insurance companies can accurately assess risks, provide personalised solutions, streamline operations and ensure compliance. Data processing can empower the industry to adapt to the ever-evolving landscape and provide high-quality protection to all policyholders.
Whilst the benefits of data processing are expansive, insurers are coming up against several challenges that they need to overcome. In a recent roundtable, hosted by Future Processing, its Head of Data Solutions, Krzysztof Nykiel, was joined by Artur Niemczewski, Non-Executive Director at Chartered Insurance Institute and Ian Thomas, Head of Data at Aurora Insurance to discuss the future of data processing in insurance.
Advancing with Artificial Intelligence
Insurance companies have been harnessing the power of Artificial Intelligence (AI) for many years, leveraging its ability to process and analyse vast amounts of data. This technology has revolutionised how insurers automate underwriting processes, detect patterns and trends, identify fraudulent activity and make accurate risk assessments. AI-powered chatbots have also bolstered customer service and streamlined claims processing.
Looking ahead, AI will encourage insurers to adopt real-time data processing. This opens up the possibility of providing real-time quotes, adjusting coverage based on customer’s changing needs and quickly identifying fraudulent activities. Artur Niemczewski highlighted that the speed of processing and understanding data gives insurers a competitive edge. For example, if they can respond to over 100 quotes in a day with an automated system, that insurance company will become a leader in the market. Ultimately, it’s not just the quality of data, but how efficiently insurers can ingest, process and act on it.
Predictive analytics will also become a critical tool in processing insurance data. With the use of AI, insurers can analyse historical data and develop more accurate models for claims forecasting, underwriting and risk assessment. Ian Thomas commented that humans create ‘noise’, making it difficult to identify trends in historical data. Algorithms, however, can help remove this noise to identify trends and enable underwriters to provide quicker and more accurate quotes.
As AI becomes more ingrained in the insurance industry, insurers must be able to respond and act on the changing landscape. They must be open to embracing these advanced technologies to unlock new insights, streamline processes and deliver an improved customer experience in the long term.
Magnified concerns around data privacy
As the volume of data collected by insurers continues to grow at a rapid pace, ensuring they are compliant with data privacy legislation has never been more important. From underwriting and risk assessment to claims management and customer service, insurance companies have a responsibility to not only safeguard sensitive customer data but ensure the integrity and availability of data in line with regulatory requirements.
The introduction of GDPR is just one example of the data protection laws that European insurers must comply with, and navigating these complex regulatory landscapes can often be challenging. Insurance companies are also faced with handling a staggering volume of data, and managing this effectively requires insurers to take a step back to ensure its quality, and make it accessible and usable for decision-making purposes. Niemczewski explained that businesses need to evaluate what data processing methods have been used, who has the right to that data and, most importantly, whether any rules have been violated.
Thomas added that this relates to data lake houses and provenance. A data lake house is a new, open data management architecture that combines the flexibility, cost-efficiency and scale of data lakes with the data management of data warehouses, which enables AI to effectively automate all data. He stated that insurers also need to consider where the data came from, what transformation happened and what data analysis was used.
Balancing the need for data-driven insights with the need to respect customer privacy is a challenge that most insurers will face in the near future. Encryption, access controls, regular audits, and other protective measures will be essential to maintain customer trust and meet legal obligations. Krzysztof Nykiel explained that companies need to keep track of all information with data governance procedures. Whilst this will vary between different organisations, insurers will need to track who has access to each data set with data catalogues to enable the data to be used for growth and innovation.
Integrating external data sources
As data becomes more readily available, insurance companies will begin to integrate data from external sources, such as social media or third-party databases, to gain a comprehensive view of customer behaviours and potential risks. Thomas stated that insurers are exploring external data sources as in-house data is often poor quality, inaccessible and hard to update. By removing these restrictions, insurance companies will be able to better tailor services to customers by truly understanding their needs and requirements.
To accomplish this integration, advanced data processing techniques will be needed to extract meaningful information and ensure data accuracy. Nykiel explained that systems can be designed to handle this amount and type of data, and it’s vital that businesses in the insurance space have the infrastructures in place to gather data from multiple sources to make better and more informed decisions.
Looking to the future
Data processing offers significant benefits to insurers, enabling them to offer personalised services, optimise operations and build a better understanding of their customers. Thomas concluded that there is a risk, however, of insurers being left behind if they don’t take action now. This re-emphasises the importance of staying informed and utilising emerging technologies to stay ahead of the curve while ensuring data privacy and security.
Embracing these advancements in data processing will not only enhance risk assessment, streamline underwriting processes, and detect fraudulent activities, but it will also help insurers remain competitive, agile and customer-centric as the insurance landscape continues to evolve in 2024 and beyond.
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