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One Network. One Standard. Zero Blind Spots.

Fraud travels across institutions. Intelligence must too.

Sentinel unifies the financial network under a single, shared AML signal.

Why Now

Fraud Is Real-Time. Compliance Must Be Too.

Digital rails have exploded: 100M+ daily MFS transactions 1 and $400M+ in annual fraud exposure 2. Regulators now expect real-time AML. But no bank can see threats across the network.

With BFIU endorsement, we can finally build the solution.

The Challenge

Banks are losing billions to fraud they cannot see.

Fraud moves in real-time across institutions. Legacy AML is siloed and slow—built to file reports, not stop active theft.

Siloed Intelligence

Fraud hops between Bank A → B → C. Cross-bank threats remain invisible to individual FIs.

90%+ False Positives

Compliance teams drown in noise from outdated, rule-based systems. Analysts waste hours chasing low-risk alerts.

Legal & Privacy Barriers

Institutions *cannot* legally share raw customer data to collaborate. This legal barrier is the criminal's best protection.

The FI Value Proposition

Immediate, Measurable ROI for Banks

BFIU endorsement enables the network, but FIs are the primary beneficiaries, gaining a direct return on investment.

Stop Real-Time Fraud Loss

Detect and block network-based fraud (mules, Hundi) *before* the funds leave your system.

Slash Compliance Costs

Reduce the 90%+ false positive burden, where each alert costs an estimated $30-$50 to investigate 3.

Improve Audit Outcomes

Demonstrate proactive, network-aware AML/CFT monitoring to regulators, improving your audit rating.

Market Opportunity

A Foundational Market, Poised for Transformation.

This explosive growth in digital volume has created a corresponding surge in systemic risk. Regulators now expect real-time intelligence, but banks lack the cross-network tools.

The market consists of 60+ Scheduled Banks, 35+ NBFIs, and 9 MFS providers, all facing a 30%+ CAGR in digital payment volume 4. This is our captive audience.

MFS Growth & Fraud Exposure

More transactions = more velocity for fraud.

90%+ False Positive Burden

Sentinel turns noise into signal.

Our Solution

The National AML/CFT Network

A shared, privacy-preserving intelligence network for all FIs, built on three pillars of next-generation technology and governed by the BFIU.

Federated AI Engine

AI models train *locally* inside each bank. Only insights are shared, not raw data. This is the key to compliant collaboration.

Zero-Knowledge Proofs

Cryptographic proofs allow Bank A to confirm a suspicion with Bank B *without either side revealing customer data*.

Permissioned DLT

A Hyperledger Fabric ledger acts as the immutable, regulator-auditable "source of truth" for all shared intelligence alerts.

How It Works

A Regulator-Centric Workflow

This is the 5-step flow that enables compliant, real-time intelligence sharing under BFIU governance.

1. Local Transaction

A customer transacts at their FI. The FI's internal system processes it as normal.

2. Anonymize & Commit

The FI hashes transaction data and commits the anonymized hash to the DLT. A regulator-governed canonical hashing schema ensures cross-bank matchability. No PII ever leaves the bank.

3. AI Analyzes Network

The Federated AI engine analyzes the entire network's hashes in real-time, spotting cross-institutional patterns (like a Hundi ring) invisible to any single bank.

4. Shared High-Confidence Alert

A single, high-quality alert is generated and sent simultaneously to the BFIU and all FIs involved in the suspicious activity.

5. Coordinated Action

For the first time, regulators and FIs can collaborate on the same alert, using the DLT as the common source of truth for faster investigation.

Technology Edge

Purpose-Built for Privacy & Scale

Our stack is built for national-scale intelligence: private inside each bank, connected across the network.

Graph Analytics

Maps relationships in real-time. Detects mule rings & Hundi flows as they form.

Federated Learning + ZKPs

AI trains locally; only “learnings” leave the bank. No data ever moves — regulator compliant.

Hyperledger Fabric (DLT)

Immutable, tamper-proof ledger for AML intelligence sharing.

Kubernetes Deployment

Modular microservices. Update fraud engine without touching AML layer.

Governance & Business Model

A National Utility, Not Just Software

This is structured as a Public-Private Partnership (PPP). Our BFIU endorsement and first-bank commitment are the foundation of this model.

Governance Framework

Policy Alignment

Co-designed with regulators to align with the MLPA 2012, Anti-Terrorism Act, and upcoming Data Protection Act.

Data Governance

The core rule: PII never leaves the bank. Federated learning and ZKPs make this technically enforceable.

Consortium Model

Operated as a national utility. Governed by a consortium of BFIU, BB, and participating FIs. BFIU endorsement and direct FI ROI are designed to drive adoption as a de facto standard.

Commercial & Risk

Risk Mitigation

Risks are managed via independent audits, a phased sandbox-first rollout, and clear governance.

Commercial Model

A hybrid model: 1) One-time consortium setup fee. 2) Annual, volume-based SaaS license. Foundational bank cohorts receive preferential economics tied to early risk.

Regulator-Grade Guarantees

Zero PII movement, an immutable DLT audit trail for all shared alerts, and independent cryptographic audits to guarantee privacy.

Roadmap

A Phased, De-Risked Rollout

This isn't a "big bang" launch. It's a careful, three-phase plan to build trust, prove the tech, and scale with regulatory approval.

Phase 1 (Months 1-9)

Legal & Sandbox Foundation Finalize the PPP charter. Launch the regulatory sandbox with BFIU and our first partner bank to test the core DLT.

Phase 2 (Months 10-24)

AI Pilot & Validation Deploy the Federated AI engine. Onboard 2-3 more FIs. Key Deliverable: the first live, cross-bank alert, validated by BFIU and pilot FIs.

Phase 3 (Months 25+)

National Rollout Phased, regulator-approved onboarding of all FIs. Extend to new use cases such as Trade-Based AML and cross-border flows.

GTM Snapshot

Investor GTM Snapshot — First 5 Years

A sequenced playbook: prove Sentinel in Bangladesh, replicate the model into high-velocity digital markets, and compound value through a network of regulator-backed utilities.

Years 1–2 · Bangladesh Anchor

  • · Close BFIU PPP + sandbox charter.
  • · Connect 1–3 founding banks + 1 MFS operator.
  • · Ship v1 network alerts into live rails.
  • · Publish first regulator-grade impact metrics.

Years 3–4 · Regional Clones

  • · Replicate PPP template in 2–3 new markets.
  • · Anchor each rollout with regulator + 2 banks.
  • · Local system integrator & audit partners.
  • · Cross-border corridor pilots (remittance, trade).

Year 5+ · Network Effects

  • · Interlinked Sentinel utilities across regions.
  • · Premium modules: TBML, sanctions analytics, fraud-as-a-service.
  • · Consortium data network with anonymised benchmarks.
  • · Strategic partnerships with global AML platforms.

Revenue Architecture

Hybrid model: setup fees, volume-based SaaS, and optional premium modules. Early markets subsidise entry into larger, slower-moving jurisdictions while preserving capital efficiency.

GTM Motions

Policy-led, top-down engagement with central banks and regulators, paired with bottom-up proof with innovation, risk, and fraud teams inside anchor banks.

Proof to Scale

Core thesis: once one regulator-grade Sentinel is live, each new market becomes a structured clone — faster sales cycles, lower integration risk, and compounding reference power.

Team

A Team Built for National-Scale Systems

Ex-regulators, bank compliance leaders, and distributed systems PhDs. Our team is uniquely positioned to win in Bangladesh—and scale beyond.

Photo of CEO

[Founder Name]

Chief Executive Officer

Ex–Bangladesh Bank / major FI leadership. Deep expertise in payment rails & compliance frameworks.

Photo of CTO

[Founder Name]

Chief Technology Officer

PhD in Distributed Systems. Architected national-scale blockchain systems.

Photo of CCO

[Founder Name]

Chief Compliance Officer

20+ years in fraud & AML. Former Head of Compliance at a multinational FI.

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[Advisor Name]

Strategic Advisor

Former Head of BFIU. Guides regulatory alignment & AML policy strategy.

Pilot Fund

The Ask

We are raising a $X.XM Pilot Fund to launch the official BFIU regulatory sandbox and build the core platform.

Use of Funds

Key 18-Month Milestones

  • Finalize the PPP consortium, governance, and data-sharing charter.
  • Launch the official BFIU Regulatory Sandbox with our first bank.
  • Build and audit the core DLT (Hyperledger) & Federated AI (V1) engines.
  • Onboard 2-3 additional FIs to the live sandbox environment.

Footnotes & Citations

  1. BB Est.: Bangladesh Bank estimated figures on digital transaction volume.
  2. Industry Est.: Industry estimates based on regional fraud exposure percentages applied to transaction volume.
  3. Global Benchmark: Global benchmark data on the operational cost of investigating a single AML alert.
  4. BB: Bangladesh Bank published data on digital payment growth (Compound Annual Growth Rate).