What we automate
We build AI for financial services systems that integrate with the operational reality of Australian financial services businesses. Common workflows we automate end-to-end:
- KYC and AML onboarding workflow with document verification
- Transaction monitoring and exception flagging
- Compliance and breach reporting
- Reconciliation across custodians, brokers, and platforms
- Client review meeting prep and file note drafting
- AFSL and reporting obligations support
- Investment performance reporting
Built for the realities of financial services
AUSTRAC and ASIC reporting obligations have specific structured formats and zero tolerance for breach.
Customer data sovereignty and AU privacy law apply strictly.
Auditability and explainability of automated decisions are regulator-facing requirements.
Integration with platforms (Macquarie, BT, Praemium, etc.) varies in quality and requires pragmatic engineering.
Why work with us on AI for financial services
AI for financial services built with familiarity in Australian licensing frameworks (AFSL, ACL), AUSTRAC obligations, and the platform ecosystems advisers and brokers actually use day to day.
Where most AI in financial services goes wrong
Most AU financial services AI projects get scoped without enough attention to the prudential standards that apply, then run aground at the supplier risk assessment. The fragmented patterns: AI tools deployed without a CPS 234 vendor risk assessment, customer-facing models without explainability layers required for regulator scrutiny, data flowing to commercial LLM APIs without enterprise terms that satisfy APP 8 cross-border disclosure obligations, AI-driven decisions in credit or claims that don't carry an audit trail capable of surviving a regulator review, and "AI for compliance" that doesn't integrate with the actual compliance monitoring stack. Financial services regulation in AU has teeth, and AI engagements that don't design for the prudential expectations end up either rebuilt or removed.
Systems we integrate against
Financial services AI engagements typically integrate against Murex, Calypso, Avaloq, Temenos, FIS, Finastra core banking, internal Java/COBOL ledger systems, Salesforce Financial Services Cloud, Bloomberg, Refinitiv, Iress, Bravura wealth platforms, custom loan origination systems, KYC and AML platforms (NICE Actimize, FICO Tonbeller, ComplyAdvantage, Refinitiv World-Check), GRC platforms (RSA Archer, ServiceNow IRM, MetricStream), and the data warehouse layer (Snowflake, Teradata, increasingly Databricks). Most mid-market AU financial entities run a substantial portion of this stack, with custom integration glue that AI workflows must respect.
If your stack isn't listed above, reach out anyway. The systems vary by industry but the integration patterns don't. We can usually work with whatever you're running. Tell us your stack.
Regulatory and compliance landscape
The AU financial services regulatory stack is the deepest of any vertical: APRA CPS 234 (information security), CPS 230 (operational risk), CPS 232 (business continuity), CPS 235 (managing data risk), the FAR (Financial Accountability Regime) personal obligations on senior executives, ASIC AFSL and ACL obligations including the design and distribution obligations (DDO), AML/CTF Act obligations through AUSTRAC, the Privacy Act and APP 8 for cross-border data, and the Consumer Data Right (open banking and energy). For AI work specifically, ASIC has issued guidance on AI in financial services and APRA expects supervised entities to apply equivalent rigour to AI-driven decisions as they do to other model risk. We design against this stack from the architecture stage.
Operational outcomes we move
Defensible outcomes we have moved on financial services engagements: customer service cycle time on identity verification, transaction queries, and document requests reduced; advisor-facing case prep time compressed through cross-system synthesis; credit decisioning evidence overhead reduced (note: AI augments the existing decisioning model, it does not replace it); reconciliation exception triage handled at a fraction of the previous human cost; AML and KYC review queue throughput improved; advisor-coaching evidence generation for design and distribution obligations. Numbers that survive board reporting, not numbers that survive a vendor pitch.
Common deployment patterns
Common deployment patterns for AU financial services: in-VPC open-weight models for the most sensitive workloads (customer PII, credit decisioning context), with commercial AU-region endpoints for less sensitive work; identity-aware retrieval across the ledger, CRM, and compliance systems with role-based access scoping; AML/KYC triage agents that surface evidence to human reviewers in a structured workflow; advisor copilots grounded in the firm's product disclosure documents and policy library; CPS 234-aligned evidence trails produced contemporaneously.
Related Bedstone services
Financial services teams typically pair this work with custom financial systems, security audits for APRA CPS 234, IRAP-aware infrastructure, and sovereign AI deployment for CPS 234-aligned workloads. Or look at Bedstone OS for an identity-aware AI workspace across your ledger and CRM.
How we engage
Five-step delivery, scoped to fit. Audit, scope sprint, proof of concept, verification, rollout. Wrapped as a fixed-scope sprint, monthly retainer, fractional engagement, or one-off audit. See services for the full process and commercial structures.
Common questions about AI for financial services
Is AI for financial services safe given regulatory requirements?
Yes, when built properly. Customer data stays in AU, every automated decision has an audit trail, and breach-reporting workflows route through human reviewers. We work to standards expected by ASIC and AUSTRAC.
Can you integrate with the platforms my licensee uses?
Yes. We integrate against Macquarie, BT, Netwealth, Praemium, HUB24, Class, Xplan, and others. Where APIs are weak, we work with file drops or middleware.
Do you work with advice firms, brokers, or fintech startups?
All three. Advice firms benefit most from client meeting prep and ROA support; brokers from origination and discharge workflows; fintechs from full-stack product engineering.
Is this eligible for R&D Tax Incentive?
Most agentic AI and novel integration work qualifies. We document sprints so your tax specialist can file with confidence.
Across Australia
We work with financial services operators across the country. See city-specific context: AI agency Australia, Brisbane, Sydney, Melbourne, Perth.