A decision made too late
The call came the day it was made. Then a list moved, and nothing told you. The file still reads clear, so nobody looks at it again.
Screen every customer in real time. Catch every change within minutes.
Sanctions, PEP and watchlist screening at onboarding, continuous rescreening against data refreshed every 15 minutes, and one explainable risk score your regulator can follow & audit.
Every screening vendor sells the same thing: more lists, more sources, faster refreshes. But your team does not spend its day with data. It spends its day making decisions, and each one carries a name and a date. Fusion is built around the decision rather than the record, because a decision is the only part of screening a regulator can actually examine.
The call came the day it was made. Then a list moved, and nothing told you. The file still reads clear, so nobody looks at it again.
When almost every alert is noise, attention becomes the scarce resource. The name that mattered was not missed through negligence. It was missed through volume.
After a while, an auditor asks why. If the match logic, the list version, and the approver aren't attached to the decision itself, you can't demonstrate you're right.
One CSV, one API call, or a live sync from your core system. Entity resolution de-duplicates before anything is screened. You can also do this screening manually through our platform.
Fuzzy, phonetic, and transliteration-aware matching runs inside the API call. Choose your configuration, threshold, and profile.
Lists can change every minute; nobody knows when, but we can monitor our customers against to changes in real time and get updates immediately.
If you get an alert, you have to manage it. With our ultimate case management features, you can easily make decisions, take notes, and take action.
Transliteration-aware across Latin, Cyrillic, Arabic, Greek and Chinese. Catches aliases, spelling variants and name order differences.
Date of birth, nationality, Gender, ID, and passport number are scored alongside the name, so a common name doesn't trigger a common alert.
The same individual/company appears across dozens of sources under different spellings. Fusion resolves them into a single profile, so you review once, not the same person a dozen times.
PEP exposure rarely sits in the PEP's own name. We screen and surface associate and family links, showing the relationship with our super-extended PEP data.
Retail, corporate, and high-risk portfolios carry different risk appetites. Each has its own match threshold from different lists, and they follow different review paths, documented in policy rather than configured ad hoc.
Every score shows which field matched, which list it came from, the source text and the threshold in force at the time. A cleared name stays cleared until the underlying record changes.
Type a name, pick which data types apply, and read the matches ranked by score. Every row carries its list origin.
Alerts arrive grouped by customer, ranked by Fusion score, with the reason on the row. Auto-cleared deltas never reach the queue.
| Level | Ref | Detail | Score |
|---|---|---|---|
| High | #8841 | A. Volkov Sanctions | 98 |
| Med | #4102 | M. Aydin PEP tier | 71 |
| Med | #7719 | Delta Corp Adverse | 66 |
| Low | #2277 | J |
Aliases, dates of birth, roles, relatives and every source document behind the designation, with the original language text kept intact.
Customers are automatically rescreened against sanctions, PEP and RCA, watchlist data based on their risk level. Lists update every 15 minutes. Any change in a risk profile raises an alert, and results land in case management.
Every vendor lists the same regimes. The question an examiner actually asks is narrower: what did your system hold on the day the decision was made, and why didn't it fire? Every record in Fusion is versioned and timestamped, so the answer is a query, not a reconstruction.
Client Screening returns a position on a name. Fusion turns that into a position on a customer: KYB adds the owners behind the entity, Transaction Monitoring & Fraud adds how they actually behave, and Adverse Media adds what is being reported about them. Multiple inputs, one unified score you can defend.
Send the company, get the resolved structure with every party screened and the aggregate calculated. Subscribe to structural change and threshold events.
Manual list checks ran monthly and covered one jurisdiction. After migration, the whole base is rescreened every 15 minutes across 220+ countries, and clearances carry a reason code.
Bring a sample file. In 30 minutes you will see the matches, the scores and the audit export they produce.
The data it contains consists of sanctions and watchlists, PEP records relating to relatives and close associates, and wanted lists, all of which are obtained from more than 3,000 sources in over 220 countries. Two things are not included in it: adverse media screening and monitoring is a separate product that is incorporated into the same customer profile, and document and biometric identity verification is entirely outside the scope of Complead, being managed by your IDV provider.
With a synchronous search the median time is 50 ms, which is fast enough to be sent as part of your onboarding request without the need for a loading screen. Bulk screening is carried out asynchronously and a report is provided for each batch.
Certainly, most teams begin by doing so. You can load the existing database using CSV, via an API or through a live sync with your main system. Entity resolution first removes duplicate entries, so even if the database contains 1.2 million records, it does not result in 1.2 million reviews.
The lists are updated every 15 minutes and your base is continually checked against any changes. The rescreening depth is based on the customer's risk level rather than being carried out on a fixed monthly basis, so customers with a high risk level do not have to wait for the same schedule as those with a retail profile.
A name which has been cleared remains cleared until the original record is altered, so each time the list is updated the same false positive does not reappear. Likewise, delistings work in the same manner and end the alert by giving a reason code instead of leaving it open.
Right, the internal blacklists, the lists provided by the local regulators and the customer-specific watchlists are just as much a part of the global data as the rest of it, are assessed using the same methodology, and are included in the same audit record.
There are four points, and none of them involves a lower threshold; score bands for each customer segment, together with secondary identifiers such as date of birth and nationality, are scored along with the name, there is one profile per entity rather than one per list, and pattern level bulk clearing is carried out once a match pattern has been tuned.
It depends on how you define it. Once authorised, Nova auto deals with the deltas, for example in the case of a confirmed delisting or when a pattern which has already been cleared is repeated. In all other cases the matter is passed on to a person, and each automated action is logged together with the signals that led to it, so that the record indicates what decision was made and by whom.
The name of the alert, who was responsible for it, their decision and when it was made, the list version that was in effect at that time, and the source text associated with the designation; the information can be exported in the form of an evidence pack either per case or per period.
Sandbox keys are handed out right away and the first live call takes place within 15 minutes. Production integrations, including the setup of monitoring webhooks, are usually completed in the same week. However, if your policy prohibits the sending of names, screening can be carried out using hashed identifiers. Information regarding data residency, retention and subprocessors can be found in the Trust Center.
We went from checking customers one by one to a single platform that screens more than 3,000 of them around the clock, so our analysts can finally focus on real risk.
We moved from screening customers one by one to a unified platform where our analysts can focus on what actually matters.
We focus on real risks, not false positives, meeting our AML obligations and our customers' expectations.