Banking downtime spends customer trust, not just revenue.

A banking or fintech outage triggers regulatory scrutiny and customer anxiety about their money in ways a typical revenue model undercounts. Defaults below reflect a retail banking or fintech profile, not trading infrastructure.

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Estimate SLA breach risk

Annual downtime cost

$0

Hidden outage tax: $0

Direct loss $0
Hidden tax $0
0h Annual outage time
0h SLA budget
0h Budget overrun

Customers don't wait calmly when money is involved.

A payment or account-access outage triggers a different kind of customer reaction than most software failures — anxiety about their own money, not just inconvenience — which shows up in call center volume and account churn.

01

Call center surge

Payment and account-access outages typically generate a disproportionate spike in support calls compared to outages of similar length elsewhere.

02

Regulatory reporting

Many financial regulators require incident disclosure within defined windows, adding a compliance workstream on top of technical recovery.

03

Account attrition risk

Repeated access outages are a commonly cited driver of primary-account switching, a slower but real cost beyond the immediate incident.

Finance industry outage cost, answered.

Questions that come up when sizing the cost of a banking or fintech outage.

How is this different from the broker-dealer calculator? This page models retail banking and fintech account/payment infrastructure. See the broker-dealer calculator for trading-specific dynamics with much tighter MTTR expectations.
Should I include regulatory fine risk in the estimate? No — fines are case-specific and not built into the hidden-tax multiplier. Treat this as the operational and reputational cost, and add regulatory risk separately if relevant.
Why is the hidden tax often higher for finance? Regulatory review, mandatory customer communications, and elevated support volume all add cost that compounds faster than in less regulated industries.
What SLA target is typical for core banking systems? 99.95% or higher is common for customer-facing payment and account systems, reflecting both customer expectations and regulatory pressure.

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