Key Takeaway: Financial AI in the UK is shifting front-line investment work, forcing investment professionals to adopt algorithmic workflows faster.
Why it matters: New capital into startups like Model ML, backed by FT Partners, speeds product rollouts and raises stakes for incumbents and boutiques.
Model ML’s Series A redraws the map
The SiliconANGLE News report on Model ML's $75M raise says FT Partners led the round to scale AI tools for investment professionals.
Source: SiliconANGLE News, 2025
Model ML Inc. builds predictive and workflow AI aimed at asset managers and traders. The capital will fund product development, hiring and commercial expansion.
Source: SiliconANGLE News, 2025
The investment bank FT Partners joined the round, signalling confidence from a specialist dealmaker. For Model ML, that means faster access to institutional customers and distribution channels.
"Capital like this compresses product-market fit cycles and forces the industry to decide: adopt or be outpaced,"
— Angus Gow, Co-founder, Anjin.
Source: Anjin comment, 2025
The £Xbn opportunity many still miss
Most firms focus on model accuracy and forget workflow change. That overlooks client-facing gains from automation, bespoke signals and compliance tooling for investment professionals.
Regulators note the rapid uptake. The Financial Conduct Authority has guidance on firms using machine learning and AI, stressing governance and explainability.
FCA guidance on using AI and machine learning in financial services
Source: FCA, 2024
In the UK, financial AI is already shifting procurement priorities at asset managers, with procurement and portfolio teams seeking auditable models.
Source: FCA, 2024
This opportunity is especially relevant to investment professionals who need faster, compliant insight pipelines, with less manual reconciliation and clearer audit trails.
Your 5-step roadmap to capture value
- Audit existing workflows within 30 days and map where financial AI removes repetitive work (aim for 30-day pilot).
- Run a pilot over 60 days measuring signal lift and latency for investment professionals (track Sharpe or hit rate).
- Integrate model explainability tools in 90 days to meet FCA-style governance and audit checks.
- Scale to production across one desk in 120 days and measure time saved per trade or report.
- Iterate quarterly using client feedback and performance metrics to reduce model drift (target 20% fewer false positives).
How Anjin’s AI agents for investing delivers results
Start with Anjin's AI agents for investing to automate signal generation, compliance checks and research summarisation.
In a recent scenario, a mid-sized UK asset manager deployed the investing agent across equity research teams. Projected uplift was a 35% reduction in analyst time spent on data gathering, with a 12% improvement in actionable trade signals.
We expect those gains to scale across portfolios and geographies. Use the AI agents for investing solution to standardise model outputs and to reduce audit friction.
Source: Anjin internal projections, 2025
Pair that agent with commercial engagement via Anjin pricing options or setup via Anjin contact for enterprise onboarding to shorten procurement cycles.
Source: Anjin commercial information, 2025
Expert Insight: "Deploying targeted agents unlocks the twin wins of productivity and auditability for investment professionals," said Angus Gow, Co-founder, Anjin.
Source: Angus Gow commentary, Anjin, 2025
Claim your competitive edge today
Start by prioritising the workflows that most affect returns. Financial AI in the UK now separates leaders from laggards.
A few thoughts
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How do UK asset managers adopt financial AI without breaking compliance?
Map data lineage, apply explainability, and run short pilots tied to FCA expectations for governance in the UK.
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What metrics prove ROI from financial AI for investment professionals?
Track time saved, signal hit rate, and cost per trade to show clear ROI within a fiscal quarter in the UK.
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Which supporting tools speed deployment of investment-focused AI?
Use model deployment agents, versioning, and compliance wrappers to get usable results faster for UK teams.
Prompt to test: "Using Anjin's AI agents for investing, draft a 60-day pilot plan for financial AI deployment in the UK aimed at reducing analyst time by 30% while meeting FCA governance requirements."
Ready teams should trial agents now; an organised pilot can cut onboarding time by up to 40% and reveal measurable alpha sources.
Contact Anjin’s enterprise onboarding team to design a compliant pilot that targets measurable uplift such as reduced analyst hours and cleaner audit trails.
Source: Anjin pilot outcomes, 2025
