Our experts large self-clearing broker-dealers handle relentless regulatory change and conduct scrutiny—Reg BI, CAT, AML, market-abuse, and complex supervisory expectations—by redesigning end‑to‑end compliance and supervision frameworks, from governance and policies to surveillance and testing. We deploy AI- and ML‑based trade and communications surveillance, LLM “co‑pilots” that help supervisors interpret rules and case history, and RPA with AI to industrialize CAT, blue sheet, and other regulatory reporting. The result is regulator‑ready evidence, faster issue closure, and proactive compliance that supports, rather than slows, business growth.

Phoenix supports self‑clearing broker-dealers in strengthening resilience against trading outages, cyberattacks, vendor failures, and account‑takeover fraud that can rapidly cascade through the franchise. We design end‑to‑end resilience frameworks spanning trade capture, clearing, settlement, and digital channels, aligned with evolving regulatory expectations on impact tolerances and third‑party risk. Deep‑learning anomaly detection and AI‑driven user and entity behavior analytics surface cyber and fraud signals in near real time, while LLM‑powered playbooks guide incident‑response teams step by step. Executives gain a clear, board‑level view of operational health and the confidence that critical services will remain available under stress.

Our experience team members will partner with broker-dealers whose self‑clearing platforms, fragmented books and records, and manual post‑trade workflows struggle under T+1 and emerging real‑time settlement demands. We map the current clearing and post‑trade landscape, then design a target operating model that consolidates platforms, streamlines workflows, and reduces breaks across asset classes. AI agents orchestrate RPA bots for reconciliations, corporate actions, and exception management, while ML and deep learning predict failure points and capacity constraints. Our architects guide modernization of core clearing systems—including cloud migration, open APIs, and quantum‑ready security—so your post‑trade stack becomes resilient, scalable, and cost‑efficient.

We help broker-dealers whose clients, advisors, and introducing brokers now benchmark them against the best digital platforms anywhere, not just other firms on the street. We reimagine retail, advisor, and institutional journeys—particularly onboarding, KYC, and account servicing—to remove friction, errors, and paper. AI‑enhanced document recognition, LLM-based data extraction, and RPA with AI accelerate digital onboarding, while unified advisor desktops and LLM assistants streamline research, proposals, and client communications. By opening your platform via secure APIs and embedded‑finance partnerships, we turn your self‑clearing capability into a differentiated, growth‑ready ecosystem.

Our advisory teams help broker-dealers facing balance-sheet pressure and tightening capital rules optimize margin, collateral, and liquidity without sacrificing client growth. We build integrated risk, capital, and profitability frameworks that reveal where capital is trapped and which clients, products, and channels truly earn their cost of funds. ML-driven stress testing, scenario analytics, and portfolio margin models are combined with emerging quantum optimization techniques for complex collateral and funding problems. With stronger governance, limits, and real‑time dashboards for intraday funding risk, leadership can reallocate capital confidently and improve returns on every dollar deployed.

Phoenix works with broker-dealers sitting on vast but fragmented trade, client, and operational data who need a governed, forward‑looking data and AI strategy. We establish data products, ownership models, and quality controls, and design AI and model‑risk governance that safely covers ML, deep learning, LLMs, AI agents, and RPA at scale. Our “AI Factory” approach turns high‑value use cases—LLM knowledge assistants, intelligent routing of service requests, early‑warning risk dashboards—into production solutions with clear controls and metrics. We also help boards assess quantum‑computing impacts on security, pricing, and risk so your innovation roadmap stays both ambitious and regulator‑ready.