Post-M&A, insurance firms will need to integrate their data to provide the new products and services that customers want. Now there’s an easier way to do it.
After five years of slow growth in gross written premiums, many European insurers are turning to mergers and acquisitions (M&A) to grow market share.
In a recent survey by Deloitte, 72% of insurers said they believed M&A will drive at least 50% of industry growth within the next five years. What’s more, 52% expect to complete two or more M&A deals in the next three years.
Insurers are looking to grow their customer base through mergers with other providers, while acquisitions of insurtech start-ups can give them access to innovative technologies to improve products and services.
“M&A activity will centre around core markets and products but will also be used, either via acquisition or partnership, to access technologies that enable improvements within the industry. However, the successful integration of newly acquired assets will be crucial in determining the success of this strategy.”
But the key to success will be the ability to integrate data from across the merged entities. Without that single pool of data, the ability to deliver modern, personalised services will be significantly eroded.
A mass of disconnected systems and databases
The more M&A activity insurers complete, the more legacy systems and databases they acquire. These disparate data silos mean customer data is fragmented across the business, preventing the firm from developing a single customer view, and hampering their ability to analyse data ‘in the round’ to surface trends and indicators.
That puts a serious brake on their ability to provide the fast, personalised and connected service that customers now expect, or to innovate the kinds of new product and service models we explored in our previous blog.
55% of UK consumers believe insurance companies provide a disconnected experience across online and offline channels. (Mulesoft)
And disappointed customers and throttled innovation aren’t the only threats insurers face from proliferating systems. Regulatory reporting becomes increasingly complex too, and in the worst-case scenario, a legitimate compliance risk.
With data fragmented across multiple locations and systems, their ability to capture an accurate view for statutory and regulatory reports like IFRS, Solvency II and GDPR is thrown into doubt.
Fragmented data also makes it harder to get real-time business insight in front of the right people at the right time, resulting in strategic decisions being made based on outdated or inaccurate information.
Integrating data with a Modern Data Warehouse
To deliver innovation and personalisation at scale, insurers require a seamless, 360-degree view of each customer and their activity. As such, a top priority for any insurer embarking on a merger or acquisition must be integrating data from across the different organisations.
This could mean replacing disparate legacy systems with a single, new system, but a more practical approach is to unite all data in a single place where it can be accessed, analysed and reported on – anytime, anywhere.
Historically, that’s been done using a data warehouse, but the problem is that traditional data warehouses take a long time – weeks or even months – for data to be ready for use and analysis.
Now, by taking advantaging of new technologies in the Microsoft Azure Cloud, insurers can create a Modern Data Warehouse architecture that makes data from multiple source systems available in near-real time.
A foundation to deliver new, customer-centric services
With on-demand access to a rich source of accurate data, the merged entity can enjoy significant benefits, including:
- Access to accurate, contextual data: making it faster and easier to compile and deliver accurate internal and external reports, and reducing the risk of non-compliance.
- A basis to explore the potential of AI: A Modern Data Warehouse can take advantage of new AI tools and services available on the Azure platform – paving the way for new, customer-centric models like personalised and parametric insurance.
- Accurate risk assessment: AI-driven predictive analytics can scour historical claims and payout data, to more accurately gauge risk and price insurance products.
- Elimination of manual processes: With customer data centralised, chatbots and robotic process automation can be applied to processes like customer communications and first-line customer support, saving time and reducing costs.
Take the next step
In our new white paper, Data: The Key to Transformation for UK Insurers, we explore how customer-centric insurers are making smarter use of their data to deliver the services and experiences that today’s customers expect.
We also take a closer look at the role data plays in supporting efficient M&A integration, and how Adatis – as a Microsoft Gold Partner specialising in data and analytics – can support that integration.
