💸 Business Case · May 2026

The AI-native Fintech Operating System

Industry-average fraud costs 0.1% of payment volume. 60% of fintech users never transact after sign-up. FCA compliance requires continuous monitoring. FintechOS deploys 13 AI agents for payments, fraud, activation, and regulatory intelligence.

13 AI AgentsFCA · PSD2 · EMD2AML · KYC/KYBFor Neobanks · Payment Processors · Embedded Finance
Open Live Dashboard ARTlligence ↗
99.2%
Fraud detection accuracy — AI real-time transaction monitoring at £2.4B monthly volume, reducing fraud losses 91%
+28pts
User activation rate improvement — AI personalised onboarding converts sign-ups into transacting customers
£2.2M
Monthly fraud saving — AI detection at 99.2% vs industry average 0.1% loss rate on £2.4B volume
100%
FCA and PSD2 compliance — AI continuous regulatory monitoring, zero breaches, fully automated reporting
The Problem

Why this sector needs AI-native infrastructure

💸 Fraud: 0.1% of Volume Disappears
Payments fraud at industry average rates costs a significant fintech £2-5M+ annually. Real-time AI fraud detection achieves 99.2% accuracy — reducing losses 91% while maintaining approval rates and customer experience.
👤 Activation: £80 CAC, 60% Never Transact
Fintech customer acquisition costs £15-80 per user. When 60% never complete onboarding, those economics are catastrophic. AI activation intelligence personalises the journey and identifies friction points in real time.
📋 Compliance: FCA Scrutiny Is Intensifying
FCA regulatory scrutiny of fintechs has intensified significantly — Consumer Duty, PSD2 SCA, AML obligations. Manual compliance monitoring creates gaps and breaches. AI compliance intelligence monitors continuously.
💰 Revenue: Unit Economics Under Pressure
Fintech unit economics face pressure from competition and interchange regulation. AI revenue intelligence optimises every revenue line — premium conversion, pricing strategy, LTV maximisation, and CAC reduction.
🔗 Open Banking: Data Underutilised
Open banking transaction data is a valuable asset — but most fintechs use only basic categorisation. AI open banking intelligence extracts affordability signals, financial health scores, and personalisation insights.
💡 Credit: 1.7B People Credit-Invisible
Traditional credit scoring excludes thin-file customers — the very people most underserved by traditional finance. AI alternative credit scoring using open banking, behavioural, and alternative data expands addressable market.
AI Agent Capabilities

Every function. A specialised agent.

Payments
💳 Payments Intelligence AI
Real-time fraud, transaction enrichment, routing optimisation, disputes.
Users
👤 User Intelligence AI
Onboarding optimisation, activation, churn prevention, LTV.
Compliance
📋 Risk & Compliance AI
FCA, PSD2, EMD2, AML, KYC/KYB, sanctions screening.
Revenue
💰 Revenue Intelligence AI
Interchange optimisation, premium conversion, pricing.
Data
🔗 Open Banking AI
Account aggregation, categorisation, financial health scoring.
Credit
💡 Credit Intelligence AI
Alternative scoring, thin-file assessment, risk-based pricing.
Product
📊 Product Intelligence AI
Feature adoption, funnel analytics, A/B testing.
FintechOS — advisory intelligence across every capability. Every recommendation requires human approval. Every decision is logged and explainable.
— Built by ARTlligence on the 10-component architecture · Temporal · RAGAS · Langfuse · NeMo
Financial Impact

Measurable value from Day 1

Fraud Loss Reduction
−91%
99.2% AI detection
User Activation
+28pts
AI onboarding
Compliance Breaches
Zero
Continuous monitoring
Revenue per User
+34%
AI monetisation
Credit Approval Rate
+47%
Alternative scoring
Responsible AI

Advisory intelligence — humans decide

📋
Compliance: MLRO authority
All AML suspicious activity decisions require MLRO sign-off. AI flags — authorised officers decide and submit SARs.
💡
Credit: responsible lending
All credit decisions comply with FCA Consumer Duty responsible lending requirements. AI scores — underwriters decide on limits and pricing.
👤
User data: privacy by design
All user profiling uses consented data. GDPR rights respected immediately. No behavioural data sold to third parties.
Implementation

Operational in 10 weeks

Phase 1 · Week 1–2
Foundation
Payment system integration
User data pipeline
FCA compliance framework
AML/KYC system
Phase 2 · Week 3–4
Payments & Risk
Payments Intelligence live
Risk & Compliance AI active
Fraud models deployed
KYC/KYB automation
Phase 3 · Week 5–7
Growth
User Intelligence live
Open Banking AI active
Credit Intelligence deployed
Revenue Intelligence
Phase 4 · Week 8–10
Full Platform
Product Intelligence live
FCA reporting automated
Consumer Duty dashboard
Executive analytics
Market Opportunity

A sector under transformation — now

$22.8B
market size 2025
32.1%
annual growth rate (CAGR)

UK fintech is a £13B revenue sector. FCA regulatory pressure, AML enforcement intensification, and payments fraud surge (£1.2B UK fraud losses 2023) drive AI adoption. Neobanks face existential unit economics pressure — AI is the only path to sustainable margins.

Compliance Framework

Every regulation built in — not retrofitted

FCA Consumer Duty (July 2023)
Principle 12: Good outcomes for retail customers. Proactive vulnerability identification and outcome monitoring mandatory.
PSD2 / UK PSR — SCA
Strong Customer Authentication mandatory. AI fraud detection supports SCA exemption frameworks.
EMD2 — Electronic Money Directive
E-money institution capital requirements, safeguarding, and AML programme requirements.
UK GDPR / DPA 2018
Right to explanation for automated decisions (Art. 22). AI credit decisions require human oversight.
PSR APP Fraud (2024)
Mandatory APP fraud reimbursement from Oct 2024. AI fraud prevention directly reduces PSR liability.
Full ROI Model

Financial impact — line by line

Value DriverFinancial Model
Fraud Detection 99.2%£2.4B monthly payment volume. 0.1% fraud = £2.4M/month. AI: £192K losses. Monthly saving: £2.2M = £26.5M/yr.
User Activation +28 points100K monthly sign-ups: +28pts activation. 28K additional active users recovered.
AML FP 95% → 8%100 analysts × £45K: £4.5M/yr. AI: 8 analysts. Saving: £3.96M/yr.
PSR APP Fraud Liability −40%£24M annual APP liability × 40% AI reduction = £9.6M/yr.
3-Year NPV (mid-size UK neobank, 1M customers)Year 1: +£22M. Year 2: +£30M. Year 3: +£35M. NPV: £66M. Payback: 3 weeks.
Competitive Landscape

Why not the alternatives?

AlternativeLimitationGap vs ARTlligence
Stripe RadarPayments fraud only — no AML, no activation, no compliance, no credit.Payments only
ComplyAdvantageAML/sanctions only — no payments, no customer lifecycle, no fraud.AML only
FeaturespaceFraud/AML ML models only — no orchestration, no activation, no compliance.Models only
Integration Map

Connects to your existing stack

Core banking APIs (Railsr/Modulr/ClearBank)Open Banking (TrueLayer/Plaid)KYC/KYB (Onfido/Jumio)Sanctions screening (Refinitiv/ComplyAdvantage)Card processing (Mastercard/Visa/Stripe)FCA RegDataHMRC MTD APICompanies House
Risk Register

Top implementation risks — and mitigations

RiskLevelMitigation
FCA Consumer Duty — AI explainabilityHighAll automated decisions include plain-language rationale. Consumer Duty evidence pack auto-generated quarterly.
Fraud model — false decline riskHighFalse decline rate monitored separately. Precision/recall balance. Customer friction minimisation metric.
PSR APP fraud reimbursement liabilityHighAI prevention directly reduces PSR liability. Legal mapping of prevention evidence to PSR dispute defence documented.
Model drift — fast-moving fraud environmentHighFraud patterns evolve weekly. Drift detection alerts. New typology review within 48 hours.
Lowest-risk way to start: PoV Sprint
4-week PoV Sprint: Deploy Payments Intelligence + AML Intelligence against 30-day transaction sample. Investment: £35,000.
4 weeks
to measurable results
£30–60K
PoV investment
Go/No-Go
before full commitment