Data maturity: Climbing the scale in financial institutions

In broad terms, data maturity measures the level of an organisation’s ability to create value from its data. To achieve a high level of maturity, data must be deeply embedded throughout the organisation and fully integrated into its every decision and activity. It is a key factor in successful digital transformation. The higher the level of its maturity, the more competitive advantages a company will have.

To measure data maturity, a maturity model is used to assess a company’s various data and digital capabilities. “There are many different maturity models available, but they all use a set of questions to rate a company’s level of maturity across many different dimensions,” explains Chris Bannocks. “These include a company’s capabilities – or maturity – in its architecture, people, analytics, ethics, privacy and so on. It’s an objective measure that can be delivered either by independent review or self-assessment.

Because regulation is a crucial issue in the world of finance, the higher the level of a bank or insurance company’s data maturity, the more likely data is to be well-controlled, well-managed, well-governed and secure.

“Data such as risk metrics, client statements or financial reporting may be deemed more accurate as a result of data maturity in those areas,” says Chris Bannocks.

But regulation isn’t the only driver for data maturity. A data mature financial institution (FI) can leverage the full spectrum of solutions that big data analytics and AI have to offer, leading to better decision making, a more connected business and greater competitive advantage. For example, a more data mature insurance company would be better at using AI to determine personalised insurance risk for each customer, leading to better-tailored policies and significant business benefits.

Many FIs still approach data maturity as a zero sum game – either you are data mature or you are not. Instead, data maturity should be viewed as a spectrum with varying degrees of maturity being appropriate for different parts of the business, says Athena. “This segmented view of maturity makes the data challenge more digestible for FIs, enabling them to target priority areas first and trading off maturity in areas that may not be as important for the business, or that may generate lower ROI.”

According to Chris, on a data maturity scale of 1 to 5, most financial institutions sit somewhere between 3 and 4. “FIs have made great strides because they’ve been hard at work in the maturity and capability space for about 15 years. But if you dive down and look at data quality or architecture or ethics, you’ll see varying levels of maturity according to industry.”

The complexity and age of legacy architecture and systems remain one of the primary challenges faced by banking and insurance companies. Of the 100 global leading banks, 92 still rely on IBM mainframe for their operations. Using an outdated system means a lack of agility and architecture that isn’t able to cope with growing workloads, especially when it comes to Big Data.

The second key challenge relates to people and organisational complexity. Behavioural change and adoption are hard to achieve across industries, not just financial institutions. But the organisational complexity of FIs makes it harder to drive data accountability and ownership and deliver business value.

According to Chris, “It may be easier for people in banking and insurance groups to change behaviour as they’re used to regulated environments and can adopt things like data governance more easily than those in other industries might. But the size and complexity of the organisational structures themselves may present different demands from a data maturity perspective: a retail bank has a different maturity need than an investment bank. The difference may be minor, but it requires that the response to each project be tailored to each case in terms of business value, not just regulatory value.”

The broad answer is to accelerate towards analytics. Here are some steps FIs can take to achieve this: