Institution Profiling / Internet infrastructure institution

Sift enhances fraud insights with new metrics

Sift enhances fraud insights with new metrics is tracked as a internet infrastructure institution within the internet infrastructure ecosystem.

Sift enhances fraud insights with new metrics

Evidence Pack

Source records grounding the claims in this article.

CategoryInstitution Type

Sift enhances fraud insights with new metrics is tracked as a internet infrastructure institution within the internet infrastructure ecosystem.

RegionGlobal

Sift enhances fraud insights with new metrics has public-source relevance to network operations, governance, dependency mapping, or market structure.

Signal FocusInternet infrastructure institution

Sift enhances fraud insights with new metrics has public-source relevance to network operations, governance, dependency mapping, or market structure.

Content TypeProfile

Sift enhances fraud insights with new metrics is tracked as a internet infrastructure institution within the internet infrastructure ecosystem.

Primary DomainTechnology

Public-source signals support medium-impact monitoring for infrastructure visibility and dependency analysis.

TopicInternet infrastructure institution

Sift enhances fraud insights with new metrics is profiled by BTW Media because public-source evidence links it to internet infrastructure, governance, operational dependencies, or market visibility.

ImpactMedium

Public-source signals support medium-impact monitoring for infrastructure visibility and dependency analysis.

Confidence?Confidence Grade · doctrine v2 §8 / SOP §2
0.90–1.00AHigh — direct sources
0.75–0.89A/BStrong
0.55–0.74B/CMedium
0.35–0.54C/DWeak–medium
0.10–0.34DWeak signal
0.00–0.09DInternal monitoring
C · 0.72

Mixed-source

Sift enhances fraud insights with new metrics is profiled by BTW Media because public-source evidence links it to internet infrastructure, governance, operational dependencies, or market visibility.

  • Sift has updated its Fraud Industry Benchmarking Resource (FIBR), introducing new metrics to help businesses fine-tune their fraud prevention strategies.
  • The updated tool reveals that credit and debit cards are responsible for 85% of fraud across all industries, though trends differ in sectors like iGaming and online gambling.

What happened

Sift, the AI-driven fraud prevention leader, has just enhanced its Fraud Industry Benchmarking Resource (FIBR), a tool that provides key metrics about fraud across various industries and regions. These updates aim to offer businesses deeper insights into fraud patterns, helping them assess risks more accurately and adapt their fraud prevention strategies.

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The new FIBR metrics reveal important trends, particularly in how fraudsters are adapting to different industries. While credit and debit cards dominate fraud across all sectors, accounting for 85% of fraudulent transactions, certain industries like iGaming and online gambling show a marked shift. Here, credit and debit card fraud drops to 64%, with electronic fund transfers and digital wallet payments accounting for 36%. This shift highlights how fraud tactics vary based on the specific dynamics of each sector, with electronic funds emerging as a growing threat in high-velocity transaction environments.

Armen Najarian, Sift’s chief marketing officer, underscored the significance of these findings. “FIBR has quickly become the gold standard for fraud insights. This update empowers businesses, whether they use Sift’s platform or not, to benchmark their performance and refine their fraud strategies,” he said.

Why this is important

Sift’s enhancements to FIBR are a game changer for businesses across industries looking to improve their fraud prevention capabilities. With fraud tactics constantly evolving, staying ahead of the curve is essential. These insights enable businesses to identify emerging fraud trends, tailor their risk management approaches, and benchmark against industry peers.

As fraud increasingly moves to digital platforms and methods, understanding these shifts is crucial for staying competitive and protected. The tool’s ability to track changes in fraud patterns allows companies to make data-driven decisions, ensuring they can mitigate potential risks before they escalate. By offering these insights for free, Sift is further establishing itself as an invaluable resource for businesses looking to tackle fraud head-on.

Core Entity Brief

  • Entity: Sift enhances fraud insights with new metrics
  • Subject Type: Internet infrastructure institution
  • Region: Global
  • Classification: Institution Type

Service Surface / Control Surface

  • Public records support monitoring of governance, service, and infrastructure control surfaces.

Governance and Policy Surface

  • Public-source signals support medium-impact monitoring for infrastructure visibility and dependency analysis.
  • Operational criticality: Medium
  • Time horizon: Quarter (30-120d)

Decision Trigger Matrix

  • Monitoring focuses on verified service continuity, governance changes, and relationship signals.
NowMedium priority

Current state favours active tracking due to infrastructure relevance.

QuarterMedium policy sensitivity

Public-source signals support medium-impact monitoring for infrastructure visibility and dependency analysis.

YearQuarter (30-120d) continuity dependency

Long-cycle infrastructure decisions likely to remain path-dependent.

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