Why Slow Cloud Storage is a Retention Risk in Finance
In financial services SaaS, cloud performance has quietly become a growth variable, not just an IT concern.
Existing customers now drive around 40% of new ARR in B2B SaaS, climbing above 50% for vendors past US$50m ARR – meaning retention is increasingly the primary growth lever rather than net-new logo acquisition.
For vendors serving banks and asset managers, that means keeping enterprise clients on platform – with predictable performance – is directly tied to revenue expansion and valuation.
That lens changes how outages and slowdowns are viewed.
Average cloud downtime is estimated to cost about US$8,600 per minute today, up from roughly US$5,600 in 2022, reflecting heavier dependence on digital channels and higher transaction volumes.
In a sector governed by strict SLAs, those minutes can mean missed commitments, potential regulatory scrutiny and the kind of service experience that encourages large clients to start shopping around.
When native cloud hits its limits
From an industry standpoint, the friction point is often not whether workloads can be moved to public cloud, but how native services behave under real financial traffic patterns.
Native cloud storage was built for elastic, general-purpose usage. Yet in trading, payments and risk environments, performance variance rather than capacity increasingly acts as the bottleneck.
Under high concurrency, standard storage tiers can introduce unpredictable I/O and inconvenient latency spikes during market events or peak trading windows.
That has pushed banks, market infrastructure providers and SaaS vendors to explore ways of smoothing performance without tearing up long-standing architectures.
One global retail trading platform serving tens of millions of concurrent users, for example, ran into storage-layer limits that threatened to cap growth unless it overprovisioned aggressively.
Addressing performance variance closer to the storage layer, instead of rewriting the application or throwing more hardware at the problem, allowed it to keep scaling user numbers and volumes without distorting its cost base.
That shift reflects a broader change in how financial services firms are approaching cloud infrastructure, according to Ed Filippine, President of Silk.
"Financial services firms don't have the luxury of slow," he says.
"Whether it's risk calculations, trading platforms or AI-driven analytics, the expectation is that the data is there and the answer is instant.
"What we're seeing across our customer base is that the biggest barrier to that isn't ambition – it's infrastructure that was never built in the cloud for this level of demand.
"The companies winning right now are the ones treating their data layer as a strategic asset, not a line item to minimise."
SimCorp and the emerging gap
SimCorp’s experience puts some numbers against these dynamics.
The company, which serves 40% of the world’s top financial firms, set out to offer its SimCorp Dimensions platform as a SaaS service on Azure – but found that native cloud performance was not meeting the expectations of enterprise clients that were used to high-end on-premises setups.
Without a way to close that gap, SaaS migration risked stalling on purely performance grounds.
By adding a software-defined storage layer from Silk, SimCorp reported up to 700% performance improvement for Oracle workloads on Azure and 20% faster performance in the cloud than its client had seen on-premises, turning a migration blocker into a reason to adopt.
“I would recommend other companies to use Silk because of their ability to provide you with the right level of performance and resiliency,” says Ulrik Elstrup Hansen, Vice President and Head of SaaS Innovation at SimCorp.
“You get a partner that is truly invested in your success. With Silk, we are able to get closer to the promise of the cloud.”
For financial services technology leaders, stories like this point to a broader competitive divide: organisations that achieve predictable cloud performance in the next 12 to 24 months are likely to see that advantage show up directly in retention rates, SaaS adoption velocity and the confidence with which they can onboard large, performance-sensitive accounts.