Eighty-one percent of global fintechs cite data issues as the biggest technical challenge they face, with almost three-quarters (74%) of fintechs whose solutions are in the early adoption phase and almost all (85%) of those with an established offering or whose products have large scale adoption see it as their biggest technical challenge.

According to research commissioned by InterSystems, a data technology provider, these struggles are split between leveraging data for analytics, machine learning, and artificial intelligence (41%) and connecting to customers’ applications and data / legacy systems (40%).

Security was also found to be a significant challenge for 40% of respondents, followed by cloud support / multi-cloud deployment and administration (39%).

The survey of over 500 senior decision-makers at fintechs across 12 countries, including the UK and Ireland, North and South America, and Australia and Southeast Asia, found that cloud tops the list for over half (51%) of respondents adopting new technologies in the next 12 months. This is followed closely by plans to invest in data management technology (48%), artificial intelligence (AI) and machine learning (ML) (45%) and data fabric technology (42%).

“While the majority of fintechs currently face significant data challenges, it’s encouraging to see many of them are looking to implement data management technologies like data fabrics to overcome them,” said Mike Hom, Head of Financial Services Solutions, InterSystems.

“This is an important step for both established and emerging fintechs, as getting their data in order will ensure any new data-related initiatives they undertake, such as implementing AI or ML, prove effective and worthwhile. By picking the right data management solutions, fintechs can also gain access to those more advanced technologies and analytics capabilities that are so desirable.”

The levels of investment into these technologies do differ in relation to the maturity of the organization, with the more established fintechs focusing more on data management (49%), cloud (54%) and data fabric initiatives (44%). Meanwhile, those fintechs whose offerings are still in the early adoption phase are more likely to prioritize investments in AI and ML (51%).

This indicates that more established organizations are focused on overcoming the data issues they are facing before considering implementing new technologies like AI/ML, which rely on data.

These investments are being driven by a number of different initiatives:

• 55% said customer demand / improve competitiveness
• 52% want to improve scalability and reliability
• 48% are hoping to increase agility
• 47% want to enable better integration with customers and third parties

However, it was found that a number of fintechs still face barriers to implementing new technology, with a lack of flexibility within their current environment to integrate new technology (54%) and a lack of internal expertise / skills (51%) cited as the largest.

Looking at their offering, 39% of fintechs surveyed offer a cloud-based managed service available in multiple public clouds and almost a quarter (23%) offer a hybrid application.

This prevalence of cloud is despite 39% of respondents previously saying cloud support is one of their top technical challenges. This is a problem felt across the board from start-ups to established players, which could point to issues such as vendor lock-in, lack of real-time cloud availability and a shortage of expertise in security, cost-management, data-locality and integration of services.