Distributed financial data processing platforms, which carry payments, trade capture, market data, risk aggregation and regulatory reporting workloads, have long treated reliability as an engineering discipline. Recently that discipline was reshaped by three forces acting at the same time. Regulation turned operational resilience into a supervised, time-boxed obligation: the EU Digital Operational Resilience Act (DORA) became applicable, and the UK operational resilience transition period has ended. Open observability standards matured, with OpenTelemetry adding profiling as a signal type, stabilising database semantic conventions and absorbing eBPF-based zero-code instrumentation, while Apache Kafka 4.0 removed its ZooKeeper dependency. AI-driven site reliability engineering (SRE) agents moved from prototypes to generally available products. Using an integrative review of recent regulatory, technical and industry sources, combined with a thematic synthesis of 205 peer studies on monitoring, risk governance, security operations, payments and AI governance, this paper develops the Integrated Financial Data Reliability (IFDR) model. The model links regulatory, technological and failure-environment drivers to four core capabilities (data-centric service level indicators, a unified telemetry pipeline, governed AI autonomy and telemetry-based regulatory classification) and to three resilience outcomes, and it is expressed as five propositions. A major AWS US-EAST-1 outage is used as an illustrative case. The paper discusses implications for practitioners, supervisors and researchers, sets out its limitations, and proposes a research agenda including financial-domain semantic conventions, correctness observability at scale and the evaluation of AI agents against realistic incident corpora.