Saudi Arabia
Mozn's FOCAL software scores bank customers and transactions for money-laundering risk
Mozn, a Riyadh company, sells banks FOCAL, which combines rules, machine learning and an AI agent. Most results below, such as the $5 million and 38% figures, come from Mozn or its own channels.
What FOCAL does
FOCAL is a platform Mozn sells to banks. According to Mozn, it puts machine learning models, a rules engine that can be changed over time, and agentic AI into one system. The system screens transactions and flags those that look suspicious.1
Mozn says FOCAL is designed to catch specific laundering patterns. It names layering, pass-through transfers and structuring, and says it does this by combining rules with machine learning.2
Customer profiles and networks
Mozn says FOCAL builds a risk profile for each customer and ties transaction monitoring to that profile. In practice, the same activity can be judged differently for different customers.2
According to Mozn's own page, the fraud module does more than check single payments. Mozn says it links people, companies, accounts and activities into networks. Its FOCAL Anti-Fraud product also checks a payee's identity by comparing the entered data with the records of the destination account.3,4
Sorting alerts
Monitoring systems produce alerts that staff must review. According to the FOCAL website, the platform has a built-in agentic AI feature that automates alert triage and auto-closures.5
Customers, results and recognition
Mozn is headquartered in Riyadh and, according to a release on PR Newswire, serves customers across the region and beyond. On 11 March 2026 it announced a partnership with D360 Bank, a Saudi digital bank, to deploy FOCAL in Saudi Arabia.6,7
Mozn says FOCAL helped one leading GCC bank prevent roughly $5 million across more than 16 fraud typologies. A FOCAL blog says a leading Saudi bank using Mozn's delivery model reduced fraud losses by 38%.3,8
A PR Newswire release says Chartis named FOCAL a Category Leader for AML and KYC, one of only 10 vendors worldwide.9
What could not be verified
- The $5 million prevented across more than 16 fraud typologies is Mozn's own figure, and the GCC bank is not named.
- The 38% fall in fraud losses comes from a FOCAL blog. The bank is not named and the period and baseline are not given.
- Whether the results at the Saudi bank came from FOCAL itself or from Mozn's wider delivery model is not stated.
- How much alert closing the AI agent does, and how accurate its triage is: the FOCAL site describes the feature but gives no figures.
Sources