Überhöhte Überwachungskosten durch manuelle Marktüberwachung
Definition
ASIC’s supervision of markets relies on a ‘significant volume of data’ and ‘specialist technologies’ to detect, understand and respond to activities in dynamic financial markets.[2] Market participants are expected to maintain proportionate monitoring, including real‑time surveillance software where trading volumes are too large to monitor manually, and to investigate and escalate alerts, file suspicious activity reports, and report breaches under the Market Integrity Rules.[1][3] ASIC also recovers its supervision costs from industry through annual invoices, so inefficient internal processes directly increase the total cost burden.[2] Where firms still rely heavily on manual checks, fragmented systems, and ad‑hoc analysis, staff must repeatedly extract, reconcile, and review large data sets to respond to ASIC queries and support internal investigations. For a mid‑size participant with a surveillance team of 5–10 FTEs, this typically represents 10,000–20,000 hours per year at average fully‑loaded costs of ~AUD 120–150 per hour (LOGIC based on Australian financial services salary benchmarks), equating to $1.2m–$3m annually in surveillance operating expense, a substantial portion of which is avoidable with modern automation.
Key Findings
- Financial Impact: LOGIC: Typical mid‑size participant incurs ~$1.2m–$3m per year in surveillance labour (10,000–20,000 hours at $120–$150/hour AUD), with 30–50% (i.e., $360k–$1.5m) attributable to manual data handling, duplicate investigations, and inefficient alert triage that could be automated.
- Frequency: Ongoing, daily recurring cost across all trading days; increases with trading volume and complexity (multi‑asset, multi‑venue, FICC).
- Root Cause: Legacy architectures not designed for ASIC‑level data volumes; lack of integrated case management; over‑reliance on spreadsheets and manual sampling; absence of risk‑based alert prioritisation; insufficient investment in regtech automation relative to trading automation (algos/DMA).
Why This Matters
The Pitch: Australian 🇦🇺 brokers and commodity exchanges spend tens of thousands of labour hours each year manually sifting through surveillance alerts to satisfy ASIC expectations. Automating data ingestion, scenario detection, and case management can cut surveillance operating costs by 30–50%.
Affected Stakeholders
Chief Operating Officer, Head of Compliance, Surveillance Team Leads, Chief Financial Officer, Head of Technology / CTO, Risk & Audit Committees
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Financial Impact
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Current Workarounds
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Methodology & Sources
Data collected via OSINT from regulatory filings, industry audits, and verified case studies.
Related Business Risks
Verluste durch Marktmanipulation und Insiderhandel wegen ineffektiver Überwachung
Trading Suspension Opportunity Costs
Compliance Monitoring Overhead
Novation Processing Bottlenecks
Novation Failure Penalties
Liquidity Overcommitment Risks
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