As Deloitte stressed in its 2024 global insurance outlook report, “merely reacting to risks and challenges is no longer good enough”. Most insurers are either undertaking – or thinking about undertaking – transformation efforts with a very clear aim in mind: namely, preventing losses happening in the first place.

This transformation typically involves adopting new technologies, including advanced analytics, to extract actionable insights from growing volumes of data. To react rapidly and make the right decisions, savvy insurance finance leaders also realise that they need a joined-up picture of performance; making the reduction of data silos a particularly important priority.

Here’s a closer look at some of the insurance sector’s most pressing current concerns, and at how these are directly shaping transformation initiatives.

IFRS 17 was billed – understandably – as a “once-in-a-generation” regulatory shift. New accounting and reporting methodologies demanded a raft of new calculation capabilities, as well as the ability to validate and utilise vast amounts of data at a granular level.

For the majority of insurers, IFRS 17 implementation meant an overhaul of processes and technologies. Many considered this to be the ideal opportunity to modernise their wider processes and boost their decision-making capabilities.

However, as our recent article highlighted, the majority of insurers have discovered that the IFRS 17 compliance journey has been harder than first envisaged. As KPMG explains, “[The] focus quickly narrowed to achieving compliance by meeting regulatory deadlines and getting back to business as usual. The initial vision of a transformed function was lost”.

The smart move for insurance finance leaders is to get that vision back – and build on the changes they have implemented already; as EY puts it, to “Think big, start small, and realize incremental value”.

One way of looking at this is to consider what capabilities you need to get a better handle on your compliance obligations, alongside the capabilities needed for better decision-making. Questions worth asking include the following:

• What critical information is needed – not just for regulatory reporting – but also to enable senior executives to better understand business performance and make key decisions?
• How do we develop a commonly-defined set of performance metrics, drawing from common data sources?
• How do we break down barriers across functions, policy areas, and branches, to establish common goals, and enable us to get a joined-up picture of performance?

In the US, 2022 was the eighth consecutive year featuring at least ten catastrophes, causing over $1 billion in losses. As Lloyd’s of London illustrates, absolute climate-related insurance losses are rising, driven by an increase in exposure in climate damage-prone areas. Economic factors such as inflation and supply chain disruptions also exacerbate losses; most notably through rising rectification costs.

When a major event looms on the horizon, what are its likely implications in terms of operational costs, cash flow, and profits? How do we provide appropriate coverage to customers without exposing the business to unacceptable levels of risk? Are we overexposed in particular areas?

EY found that “agility to adapt to continuous change” is the single most important ingredient for successful finance leaders and their teams. Insurance executives need the ability to act fast and make the right decisions when potentially catastrophic events occur. But rather than being constantly on the back foot, they also need to identify ways to increase business resilience, such as identifying ways to reduce operational costs, or in deciding where to focus customer acquisition efforts.

So how does this translate into action? What capabilities should be on every finance leader’s wish list? We would suggest the following:

• The ability to capture, collate and consume data from right across the business, including operational and policy-level information.
• An ability to integrate external data streams (e.g. weather patterns, IoT devices, government databases, supply chain partner information), alongside internal data.
• A move from reliance on static reports (which become quickly out-of-date when conditions change) to dynamic planning. When internal stakeholders have questions, finance should be able to drill into the data and produce reliable, evidence-backed answers – at speed.
• Multi-scenario and what-if analysis. No matter how comprehensive the data at your fingertips, there is rarely a single, simple answer to a complex question! It’s a case of weighing up options. This is why insurance finance leaders should prioritise the development of predictive analysis capabilities combined with driver-based and multi-scenario planning. You should be able to ask ‘what if?’, alter variables to consider multiple possible sets of circumstances, and make better-informed decisions on possible courses of action.

Whether it’s Solvency 2, IFRS 9, IFRS 17, LDTI or emerging ESG standards, all recent regulatory initiatives have at least one thing in common: the emphasis on transparency. This has two important implications for how your data is managed.

The first relates to access to data at a granular level. IFRS 17 is a prime example of this: it’s going to be pretty much impossible to maintain compliance unless you have the ability to collate, validate, and utilise vast amounts of data, right down to policy level.

The second relates to silos. If underwriting, risk, operations, and finance all have their own datasets and function-specific rules in play for recording, processing, and reporting data, it becomes even more difficult to deliver the type of clear, accurate, and consistent information required by regulators.

But if you look beyond compliance, the wider business case for reducing silos and improving access to granular data is clear. Consider pretty much any challenge faced by the insurance sector at present; volatile costs, geo-political disruption, and climate-related risks being three notable examples. The impact of these challenges is not limited to specific policy books or divisions. It affects the entire business.

Strategising in the context of these types of challenges demands a new approach to planning. Reliance on top-line data won’t suffice – and nor will silos. In their place, you should seriously consider establishing one trusted source for all data – meaning that everyone is on the same page, and everyone trusts the numbers.

The end goal should be real-time visibility, and the ability to create and amend dynamic plans, budgets, and forecasts. Drilling into granular data where necessary, you should be able to weigh up your options when new circumstances arise, choose the most appropriate course of action, spot new opportunities – with insights on the full impacts of your actions across all corners of the business.