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Named fintech and payment companies document four jobs: card and payment fraud decisions, transaction monitoring with case handling, customer and payment screening, and AI-assisted alert review. Start from your job, then look for a documented company that resembles you. The public record shows deployments and vendor-published results, not which tool performs best.
Which tool for which job?
| Your job | Documented example | The reference to read | What it documents |
|---|---|---|---|
| Move issuer clients onto a multi-tenant fraud platform |  Feedzai |  Elo | Elo migrated more than 35 issuing banks to Feedzai, which built a machine learning model per issuer and gave issuers a case manager to write their own rules. 5 |
| Raise card approval rates in new markets |  Sardine |  Prezzee | Prezzee replaced a managed fraud service with Sardine and reports up to 70% higher approvals in newer markets, with card fraud below half the industry average. 6 |
| Replace spreadsheet-based transaction monitoring |  Unit21 |  Sila | Sila moved from spreadsheets and database queries to Unit21 for transaction monitoring and reports audit prep falling from two weeks to two days. 7 |
| Replace in-house thresholds for screening and monitoring |  ComplyAdvantage |  Inpay | Inpay replaced a threshold-based in-house system with ComplyAdvantage for payment screening and transaction monitoring on its proprietary payments stack. 8 |
| Catch fraud at order creation and unify screening | ComplyAdvantage |  Mama Money | Mama Money runs customer screening and transaction monitoring in ComplyAdvantage Mesh, and its fraud team edits rules without developer work. 9 |
Which fraud and AML jobs do named fintechs document?
The public record for Fintech & Payments groups into four jobs: deciding on card and payment transactions, monitoring transactions and managing cases, screening customers and payments, and working alert queues with AI agents. Most customer stories cover one or two of these, not all four.
As of 2026-10-31, 55 companies in this sector use a tool from the Fraud & AML category: 32 are confirmed by a customer source and 23 are observed on a vendor page. These are counts of named companies, not market share, and an observed company shows adoption only, with no task attached.
Which tools make card and payment fraud decisions?
Elo, a Brazilian card network, used Feedzai's multi-tenant platform so its issuing banks could write rules, view alerts and decide on fraud themselves; Feedzai also built a machine learning model for each issuer. Elo reports a 90% drop in fraud basis points for one issuer between Q1 2023 and Q1 2024. That is a single issuer and a vendor-published figure.
Sardine's documented cases are about approvals. Prezzee, a digital gifting platform, had used a managed fraud service that worked as a black box and declined too many legitimate customers in the US and UK. After moving to Sardine it built a small team of data scientists and analysts, so the gain came with staffing. Novo took another route: step-up checks by SMS or one-time code instead of hard declines, which it says recovers 84% of previously blocked transactions and cut unauthorized disputes by over 90%.
Which tools run transaction monitoring and case handling?
Unit21's customer pages give the fullest monitoring workflows. Central Payments, which runs programs for several financial institutions, moved from one rule set for every partner to rules by product, program or bank, tested in shadow mode against historical data, with sanctions and PEP screening folded into the same workflow. Intuit uses Unit21 for transaction monitoring and case management and reports a 65% cut in alert investigation time, helped by pre-populated SAR filings. Sila's audit-prep result is in the table above.
ComplyAdvantage's documented customers pair screening with monitoring. Inpay outgrew threshold rules built in-house. Mama Money wanted rules its own fraud team could change and sanctions data in the same view as monitoring. In these Unit21 and ComplyAdvantage stories the driver is the same: rule changes should not wait for engineering. Whether one tool does this better is not something these sources can settle.
Where does AI-assisted alert review appear?
Bretton AI's confirmed fintech customers use it on alert handling. Fluz uses Alerts AI to evaluate anti-money-laundering alerts automatically, tuned to its own risk standards, and Bretton's case-study list reports a 98% cut in time spent handling false positives. Sling Money's story reports AML alert handling time cut in half. Populations and metrics differ, so the two numbers are not a benchmark. Bretton lists a SOC 2 Type II report on its trust center.
Hawk describes an AML investigative agent on its platform, and Alviere is a CONFIRMED Hawk customer; the Alviere record supports adoption only, not a specific workflow. Unit21, Sardine and ComplyAdvantage also describe agents on their own sites, but the customer stories read here for those three document rule-and-case workflows.
What do the US peers show, and at what proof level?
Seven US fintechs are named here at CONFIRMED level: Central Payments and Intuit (Unit21), Sling Money and Fluz (Bretton AI), Jack Henry (Feedzai), Novo (Sardine) and Alviere (Hawk). Five have a documented task, described above. Jack Henry partnered with Feedzai to launch Financial Crimes Defender, a fraud and AML platform for the financial institutions it serves; Alviere is adoption only.
For a US reader these are lookalike companies to study, not evidence of a preferred tool. Jack Henry's source describes a product launch, not a measured result.
What should a smaller team check before copying a workflow?
These are editorial suggestions, not vendor capabilities. First, match the job: Prezzee's approval story concerns card fraud, while Sila's concerns monitoring for a fintech aggregator. Second, check who tunes the rules: Prezzee needed analysts, while Central Payments and Mama Money value changes made without developers. Third, ask how a rule is tested before going live: Central Payments names shadow mode, and Novo's fraud lead describes back-testing a new rule over 30, 60 or 90 days.
Pricing is unknown from the sources read. ComplyAdvantage lists a self-service Starter plan for smaller businesses, and Unit21 lists a SOC 2 Type II report.
Method and limits
2026-10-31
Scope: 55 companies classified in Fintech & Payments on usedby with a public line on a Fraud & AML tool. Every count on this page covers this sector only, not the tools' whole customer base. Company size is not recorded and is not claimed.
This dated snapshot counts distinct companies in public customer evidence. CONFIRMED means a case study, named testimonial or press source; DECLARED means the company itself told usedby; OBSERVED means a vendor listing; SIGNAL means a job post. All four count, but their strength differs. Removed and unlevelled lines are excluded. Examples are a capped selection verified within 90 days. Vendor facts are sourced records checked within 60 days. Coverage is uneven and missing evidence is unknown. These figures measure neither market share nor product performance; capture dates are not adoption dates.
