Finance audits rise as hybrid database strain grows

Redgate has published its 2026 State of the Database Landscape: Finance Edition. It found that 81% of finance organisations underwent a compliance audit in the past 12 months.

The survey of 2,150 IT professionals worldwide points to mounting pressure on finance technology teams as database estates become more fragmented. It found that 42% of finance organisations now operate a permanent hybrid model combining cloud and on-premises hosting, while 36% manage four or more database platforms.

That mix is adding to the compliance burden in an industry already under close regulatory scrutiny. Finance teams are 20% more likely to face audits than the global average, and 79% of respondents described database security as a strategic concern.

At the same time, the report highlighted a gap between compliance pressure and the use of formal data controls. Only 14% of finance firms use data governance or data quality frameworks in analytics, compared with 23% in other sectors.

The findings suggest many firms are still trying to reconcile complex infrastructure with demands for auditability and traceability. In regulated industries, the ability to account for where data came from, how it moved and who changed it can be central during reviews by supervisors and internal audit teams.

Hybrid strain

Finance groups have spent years moving parts of their technology stack to the cloud while keeping significant on-premises systems for legacy, operational or regulatory reasons. For many organisations, the result is a long-term hybrid model rather than a transitional phase.

Managing multiple database platforms across those environments can make routine tasks harder to standardise. It can also complicate patching, access controls, monitoring and change management, all of which matter in audit processes.

The research also examined the use of artificial intelligence in database management. It found that 47% of finance respondents already use AI in that area, and 54% of those users apply it to automate management tasks.

Those figures place AI adoption alongside a broader push to reduce manual work in database operations. However, the report warned that weak governance structures could increase risk if automation is applied to estates where data quality and oversight are inconsistent.

DevOps shift

One area where the finance sector appears to be moving faster is Database DevOps tooling. The report found that 55% of finance organisations use dedicated tools to support repeatable, auditable delivery of database changes.

That reflects the need for clear records of how changes are made across environments, especially where multiple teams are responsible for development, operations and compliance. In banking, insurance and other financial services settings, undocumented or inconsistent database changes can create both operational and regulatory problems.

Redgate framed the challenge as one that goes beyond isolated fixes to individual systems. Resilience in finance increasingly depends on addressing analytics governance, data quality and auditability together rather than as separate workstreams.

The report also pointed to the need for delivery practices that provide evidence trails and visibility across all environments. For organisations with a mix of cloud services, legacy platforms and varied database technologies, that can mean replacing ad hoc processes with more standardised controls.

Graham McMillan, Chief Technology Officer at Redgate, commented on the findings.

"In finance, losing control of your data is a regulatory target on your back. Over 4 out of 5 companies are facing audits this year. You don't want to be reconstructing your data lineage because of potential audit scrutiny or while the regulator is in the room. You need a delivery pipeline that proves you're in control by default, not by luck. This is especially true now that AI is going to amplify every weakness in your data estate," McMillan said.

The results add to a broader picture of financial institutions trying to modernise technology under intense regulatory oversight. While many have adopted cloud infrastructure, automation tools and AI-based systems, the report suggests that core questions around control, quality and evidence remain unresolved for a large share of firms.

With nearly half of respondents already using AI in database management and only a small minority applying governance or quality frameworks in analytics, the findings point to a mismatch between adoption and control.