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You own the risk and answer to regulators for how its screening works. So why does changing a threshold mean filing a support ticket? With Minerva, you hold the settings. Tune match scoring, screening frequency and adverse media yourself, test every change against real cases in a separate workspace, and show the regulator exactly who changed what and when.

Most screening platforms run on an open dataset with about 4,000 Canadian PEP records. This isn't even close to meeting FINTRAC's definition which reaches every mayor, reeve, judge and band council chief in the country, right down to towns of 500. Minerva's agents built Canadian PEP coverage from scratch: nearly 16,000 PEPs identified, over 4x most providers, each with verified locations, a date of birth or estimated age range, and primary sources cited.

How much of your alert queue is noise? Duplicate alerts, near-miss name matches, the same subject cleared last month. Minerva reduces false positives by up to 99% with AI entity matching, repeat-alert suppression, and an AI agent that resolves the rest with its rationale attached.

FINTRAC, Canada's anti-money-laundering regulator, counts the mayor of any town as a politically exposed person (PEP), whatever the size of the town. A quick Google search on a small-town mayor's name returns that fact instantly. Many screening platforms don't carry the name at all. Most cover the premiers and the big-city mayors and stop there, and every name they miss is a compliance risk for the company relying on them. So Minerva built its own Canadian PEP data from scratch. It reaches the small-town mayors and reeves, the councilors, the Indigenous chiefs and the judges, alongside the federal and provincial names, and every customer is screened against it at onboarding and in ongoing monitoring. It means Minerva has some of the best PEP coverage in Canada. Each name carries a location and a published date of birth or an estimated age range. That detail is what rules a wrong match out. A customer decades younger than the mayor whose name they share scores down before anyone opens it, so there are fewer false matches to clear. And every record keeps its sources, so when an examiner asks why a name matched, the answer is written down. It's live in Minerva screening now. The full story: https://lnkd.in/e_y2Da95 #AML #Compliance

One of Canada's largest fintech companies, cut the time its team spends on alert triage by about 90%. On its previous screening platform, 99.9% of alerts were false positives, and every one of them needed a manual review: open the match, pull the list entry or the article, check the date of birth and the location against the customer file, write down why it wasn't the customer. Every new customer added more alerts, and screening was becoming a bottleneck on growth. The team moved to Minerva and set screening up around what it screens for, with broad coverage when a customer signs up and ongoing monitoring narrowed to the lists that fit each relationship. On top of that, Agentic Disposition reads each alert first against the source evidence and recommends a decision with its reasoning. An analyst makes the final call. The result is about 90% less time on alert triage, and alerts cleared the same day they arrive. The analysts spend more of their time investigating true risk, and screening keeps pace as the customer base grows. Every decision carries the agent's reasoning and the evidence it read, so when an examiner asks why an alert was cleared, both are on file. Try it on your own queue: https://lnkd.in/e--zaGXW #AML #Compliance

Your screening tool over-matches by design, and your analysts pay for it every week. Minerva's three-layer approach resolves up to 99% of false positives so your investigators spend most of their time on real risk.