Laundering succeeds by looking like ordinary commerce — until you chart the people, companies and cash events that keep recycling the same value through new costumes. Transaction monitoring throws alerts; case files narrate suspicions; corporate data sits elsewhere. Analysts struggle to show layering across entities when each tool truncates context. Briefings either drown in tables or oversimplify into a cartoon arrow from crime to yacht. linkchart lets financial investigators build money-laundering link analysis as a real network: persons, companies, addresses, phones and value-moving events with labels like placed, layered via and integrated into. The story of the funds becomes briefable without abandoning complexity.
Why a real link chart for money laundering
Most people start this work with tools that were never designed for networks. Documents narrate. Spreadsheets tabulate. Whiteboards photograph poorly and refuse to scale. A dedicated money laundering link analysis approach treats every person, place, asset and event as a node — and every meaningful connection as an edge you can label, question and revise.
That shift matters because decisions in money laundering are rarely about a single record. They are about patterns: who introduces whom, which address keeps appearing, which phone bridges two clusters, which event changed the shape of the network. linkchart exists so those patterns stay visible while you work, not only in the final slide.
Specialists searching for money laundering link analysis, layering diagrams or financial flow charts need entity-level clarity across people and companies. linkchart.art supports that investigation-friendly view in a collaborative browser canvas.
Who this map is for
AML investigators and financial crime analysts following value through accounts, cash, and corporate layers.
The signature move on the canvas: Animate the flow: edges should answer how value moved, not merely that two entities somehow relate.
What belongs on the map
Every money laundering link analysis gets noisy when the wrong things dominate the board. Prioritise these domain-specific anchors before decorative extras:
- Originators, mules, and beneficiaries
- Accounts, wallets, and cash points
- Companies and trade invoices
- Placement, layering, and integration steps
Sample relationship labels
Prefer short, scannable edge text. Useful starters for this domain include: transferred to, cashed out at, invoiced, owns account, smurfed via, integrated through.
Your first week on this canvas
Anchor on a suspicious transaction set and identify the first hop outward. Create cards for every account and controlling person. Label amounts and dates in notes on the edges that matter. Midweek, add corporate invoices or cash businesses that break the bank trail. By week’s end, produce a three-phase view — placement, layering, integration — even if some hops remain missing. Document why each card earned its place so the money laundering board does not drift into decoration. Before the week closes, freeze a viewer link for one outsider and capture their first three questions as backlog edges or notes.
What not to do
Do not draw undirected “associated” lines when you know a payment direction. Avoid flooding the chart with every customer of a busy MSB. Never treat a shared surname as a laundering cell. Resist presenting incomplete flows as closed proof. If an edge cannot be explained in one plain sentence, it is not ready for a briefing view of your money laundering map.
What success looks like
Success is a flow narrative a prosecutor or FIU liaison can follow: value enters, value obscures, value lands. Gaps are explicit, controllers are named where evidenced, and the next production order targets a real missing hop. When someone new opens the money laundering canvas, they should grasp the live question, the strongest links, and the next check within minutes. That is the operational definition of a successful money laundering link analysis on linkchart.
How to use linkchart for money laundering
You do not need a special template to begin. Open the linkchart app, create a map, and build outward from the question you must answer. The workflow below is a proven path for people doing money laundering who want speed without losing structure.
- Scope the map to a value stream or predicate offence, not every alert in the bank.
- Add originators, intermediaries and beneficiaries as person and company cards.
- Link transfers and cash events with amounts and dates in labels or notes.
- Attach high-risk addresses, MSBs and vehicles used in cash collection.
- Mark structuring windows and integration purchases as events.
- Prepare a regulator-ready viewer map that highlights the spine of the typology.
As the map grows, resist the urge to make it decorative. Beauty comes from clarity: consistent card titles, honest labels, and notes that explain uncertainty. A slightly ugly accurate chart beats a pretty misleading one every time — especially when money laundering work has consequences.
Entity types that shine for this use case
linkchart supports investigation-ready cards you can reuse across domains. For money laundering, start with these and expand only when a new type earns its place on the canvas:
Person Company Address Event Phone Vehicle
Person and organisation cards carry identity. Addresses anchor geography. Phones and communication profiles expose bridges between clusters. Events give you time. Vehicles and items capture the physical world that money laundering narratives often depend on. Together they form a vocabulary you can teach a teammate in minutes.
Real-world scenarios
Cash-intensive shops as layering nodes
Several takeaways show deposits inconsistent with footfall. Company cards, shared suppliers, and person cards for common delivery drivers form a loop. Event cards for bulk cash lodgements sit beside vehicle cards for the same nightly drop-off van. What looked like four noisy SMRs becomes one layering circuit. The narrative for the FIU names the circuit, not a pile of uncorrelated merchants. FIU narratives improve when the typology spine — placement, layering, integration — is visible as labelled hops.
Trade-based laundering in invoices
Import values and shipping weights refuse to make sense. Mapping seller and buyer companies, the goods as item cards, ports as addresses and payment events exposes circular invoicing through a third intermediary. A phone used to chase ‘amended’ paperwork bridges both sides. Investigators stop arguing about one discrepant invoice and start briefing the trade loop. Crypto and fiat bridges sit on one canvas so off-ramp moments stop disappearing between specialist teams.
Crypto off-ramp into property
On-chain hops end at an exchange account controlled by a quiet company. Person cards for directors, address cards for a newly bought flat, and event cards for the completion date sit downstream of the off-ramp. Vehicle purchases cluster on the same week. Integration stops being a buzzword — it is a short labelled path from wallets to keys. Redacted viewer maps let partners discuss the circuit without circulating full account identifiers.
Across these scenarios the constant is the same: when money laundering information stays trapped in siloed files, people argue about memory. When it lives as a labelled network, people argue about evidence — which is exactly where productive work happens.
Field practices that keep maps trustworthy
- Keep predicate crime entities visible so the ‘why’ of the money never disappears.
- Normalise counterparty names early — spelling variants fracture graphs.
- Use event cards for bursts of activity that typologies care about.
- Redact account numbers on shared views; keep references internal.
Common pitfalls
- Do not equate complexity with laundering — document the purpose of each hop.
- Avoid merging entities across weak name matches in common surnames.
- Never assume lifestyle assets prove integration without the funding edge.
Compared with slides, whiteboards and generic diagram tools
Slide software is excellent for presenting a finished argument and poor at hosting an evolving network. Whiteboards are wonderful for a one-hour workshop and hostile to long-running money laundering work. Generic diagrammers can draw boxes and arrows, yet they rarely treat investigative entities as structured records with fields your team actually fills in. linkchart sits in the gap: fast enough for a working session, structured enough for a case file, visual enough for a briefing.
FAQ: Money laundering
Can we show crypto and fiat on one map?
Yes. Treat wallets and exchange accounts as items or company-linked assets, then bridge to fiat events explicitly.
How does this help with SAR / SMR quality?
A clear network spine improves narratives: who, through which vehicles, toward what integration.
Is linkchart an AML transaction monitoring system?
No. It is the investigative visualisation layer once alerts or intelligence warrant deep analysis.
Can compliance and law enforcement share a chart?
When legally permitted, viewer maps align typology understanding without handing over entire case systems.
Related ways to use linkchart
Ready to build your own money laundering link analysis? Open linkchart, place your first cards, and let the network tell the story you have been trying to hold in your head.
Ethics, privacy and good judgement
Any powerful mapping tool can be misused. For money laundering, draw a bright line between legitimate analysis and voyeurism. Collect only what you need. Share only with people who have a role. When working with personal data, follow the laws and policies that apply to your organisation or community. linkchart is a canvas — responsibility for what you place on it remains yours.
Especially when maps include minors, victims, or confidential sources, default to minimisation. Use initials, role titles or delayed identifiers when full names are unnecessary for the analytical task. A precise network with careful labelling beats a sensational wall of private detail.