Posting record
Open 11+ days
- Capitex's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Capitex, so its true age is longer.
Last checked Nov 4, 2026.
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Upload your resumeWhat the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
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Skills mentioned
About the role
ABOUT THE ENGAGEMENT
Capitex is a specialist Financial Crime Compliance talent provider. We are building a fraud operations team for a 6-month staffing engagement with a leading Kuwaiti bank's 24/7 digital fraud operations function.
This is a 6-month consultancy engagement with a defined delivery model: the first two months are delivered fully remotely, and from Month 3 the role relocates onsite to the bank's offices in Kuwait City for the remainder of the term. Onsite presence in Kuwait from Month 3 is a firm requirement of the role, not a preference - please only apply if you are genuinely able and willing to relocate for the onsite phase.
THE ROLE
You will be the analytical engine of the fraud operations team: turning alert, transaction and case data into detection improvements, management information and tuning decisions. You will work under the bank's direction, alongside Capitex L1 and L2 analysts and a senior fraud investigator, and be the bridge between what the operation sees and what the detection estate does.
WHAT YOU WILL DO
- Analyse fraud alert and case data to identify trends, emerging typologies, detection gaps and false-positive drivers.
- Support rule and threshold tuning on the bank's fraud monitoring platform - build the evidence base, model the impact, and document proposed changes for the bank's approval.
- Design and produce operational MI: alert volumes, disposition outcomes, SLA performance, fraud losses and prevented losses, shift-level throughput.
- Build and maintain dashboards and recurring reporting for the fraud operations leadership team.
- Support post-incident and thematic reviews with data deep-dives.
- Work with L2 and the senior investigator to convert case observations into measurable detection improvements.
Requirements
ABOUT THE ENGAGEMENT
Capitex is a specialist Financial Crime Compliance talent provider. We are building a fraud operations team for a 6-month staffing engagement with a leading Kuwaiti bank's 24/7 digital fraud operations function.
This is a 6-month consultancy engagement with a defined delivery model: the first two months are delivered fully remotely, and from Month 3 the role relocates onsite to the bank's offices in Kuwait City for the remainder of the term. Onsite presence in Kuwait from Month 3 is a firm requirement of the role, not a preference - please only apply if you are genuinely able and willing to relocate for the onsite phase.
THE ROLE
You will be the analytical engine of the fraud operations team: turning alert, transaction and case data into detection improvements, management information and tuning decisions. You will work under the bank's direction, alongside Capitex L1 and L2 analysts and a senior fraud investigator, and be the bridge between what the operation sees and what the detection estate does.
WHAT YOU WILL DO
- Analyse fraud alert and case data to identify trends, emerging typologies, detection gaps and false-positive drivers.
- Support rule and threshold tuning on the bank's fraud monitoring platform - build the evidence base, model the impact, and document proposed changes for the bank's approval.
- Design and produce operational MI: alert volumes, disposition outcomes, SLA performance, fraud losses and prevented losses, shift-level throughput.
- Build and maintain dashboards and recurring reporting for the fraud operations leadership team.
- Support post-incident and thematic reviews with data deep-dives.
- Work with L2 and the senior investigator to convert case observations into measurable detection improvements.
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