Removing manual processes, and a steady approach to tech: the way to data management success

Legacy systems are a major obstacle for insurers

Developing more effective financial data management processes is a top priority across the modern insurance landscape. Like all other sectors of the financial world, however, creating more data-driven business models will require working alongside and transitioning away from legacy systems—a highly complex challenge.

Not only are these systems rigid and difficult to integrate with, but firms with many legacy systems also face the task of working with data from multiple sources and in various formats. Perhaps worse is that drawing data from disparate systems might raise doubts over the data’s accuracy, completeness and overall integrity.

AutoRek’s online polling survey during the Intelligent Insurer webinar in September titled  “Streamline your financial data management to increase profitability” reflected these concerns, with a third of attendees suggesting that “different data formats” was the biggest challenge to their intersystem reconciliations.

Insurers should be mindful that high quality management information and reporting is contingent on high levels of granularity in data that feeds process flows—something which is not always achieved when working with outdated solutions. Failure to overcome the legacy question will leave business leaders unable to access the data required to make informed decisions.

Speed of data delivery is paramount

Although insurers have traditionally worked with data from the past, the trend today is towards real-time data analytics. Modern financial data management and reporting is a snapshot of a specific point in time. So much so that, as soon as an output is generated, it is already out of date in some contexts. This is only exacerbated by the fast-moving digital world in which we now live.

These developments mean that insurers now use data in ways that are speed-critical both for informing management decisions and for customer-facing processes. Comparison sites will often reject potential providers who fail to deliver a price within the agreed timeframe. The ability to deliver data with speed will therefore be instrumental for insurance firms to adapt to changes in the market and reprice products accordingly.

Manual processing is falling away

Modern policyholders want prices to be delivered in real time. Meeting these expectations is a complex issue for insurers, who are often dealing with hundreds of millions of datasets. Processing and analysing these quantities of data manually is simply not efficient or effective. Firms who are yet to automate will ultimately find that they cannot deliver information in a timely enough fashion for it to be used proactively to inform overall business strategy.

Insurers should further be mindful that data delivery is commonly delayed by manual reconciliation processes. This was recognised by webinar attendees, 25 percent of whom highlighted “manual processes” as the biggest challenge to their intersystem reconciliations; 21 percent highlighted “manual errors” as the reason for their firm considering automation.

Insurers are embracing emerging technologies

Insurers now recognise that building best-in-class ecosystems requires superior tools and systems. Since the advent of COVID-19 especially, intelligent automation has been used to enhance traditional extract, transform, load (ETL) activities, which many view as a dynamic way to address clunky processes to achieve faster processing times. There has also been a significant uptake in no-code solutions (which have now replaced low-code solutions), as well as the adoption of software as a service-based models to help solve legacy challenges.

Another notable trend is the shift towards cloud-based, data warehouse and data lake type models. While these central data repositories are no doubt an effective way to store information, firms should still be mindful that such models require further solutions to unlock the true value of any stored information.

Enabling technologies such as AutoRek will be critical in allowing business users to create financial data management processes through a no-code user interface, where the results can then be driven to other areas of the business.

Central to the success of these emerging solutions is that they are flexible, rules-driven platforms that work alongside traditional limitations within business data architecture and connect disparate systems together.

Those who fail to harness these advancements in technology will find themselves falling behind in an increasingly competitive and fast-moving insurance landscape. Almost a third of webinar attendees recognised this, highlighting “keeping up with peers” as the main factor driving their firm to automation.

A methodical, incremental approach is the way forward

Although enhancing financial data management should be the central concern for modern insurance firms, senior decision-makers should still be aware that a full-blown data transformation is likely to prove too complex—it will be far more effective to start small.

It will pay dividends for firms to focus their efforts on specific data use cases. By evaluating the return on investment of individual projects, decision-makers can justify spending and align any financial data management projects with overarching business objectives.

Creating a more data-driven business model is an issue that has implications for all areas of insurance firms and must therefore be a board-level, collective initiative. This will require continued investment not only in foundational capabilities but also in data teams.

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