AI Solutions for Always-Optimized Operations

Fraud

September 10, 2021

The digitization of fraud

The pandemic has seen fraudsters develop new schemes to exploit the transition of bank workforces to remote operations and the broad population shift to digital channels.  SparkBeyond’s Discovery identifies criminal activity and alerts at-risk cohorts and individuals by detecting subtle signals in vast amounts of data.

The platform uses anomaly detection variables to uncover previously undetected, fast-changing fraud patterns trends (account takeover, money-laundering), flagging and identifying suspicious call and customer patterns, enabling teams to react swiftly to reduce first- and third-party fraud.

For insurance clients, Discovery reduces the number of ‘false positives’ and improves investigator efficiency by enabling automated decision making for simple claims and claims adjudication for potentially fraudulent claims.  Pharma teams can use track-and-trace information to reduce fraud across the supply chain – from manufacturers, logistics companies and wholesalers to pharmacies and hospitals.  In CPG, Discovery can identify subtle fraud patterns (purchases/returns) and bogus warranty claims, and enhance quality assurance programs by analyzing default patterns.

A major US card issuer and online bank wanted to improve its fraud loss detection and prevention capabilities.  SparkBeyond integrated with the client’s secure cloud to ingest anonymized customer data and its fraud solution was deployed to address $30+ million of cases.  Outcomes:

  • Consistent identification of compromised cards 1+ day in advance.
  • 8% of total fraud losses mitigated through daily card reissue.
  • $5 million in impact (10x+ ROI) within 6 months.

AI-driven analytics are helping combat COVID-driven growth in global fraud by analyzing vast amounts of data and revealing previously undetectable, ultra-subtle anomalies and signals. 

This article is part of our “Always-Optimized” series exploring how businesses can harness AI technologies to drive continuous improvement across operations and strategy.

About SparkBeyond

SparkBeyond delivers AI for Always-Optimized operations. Our Always-Optimized™ platform extends Generative AI's reasoning capabilities to KPI optimization, enabling enterprises to constantly monitor performance metrics and receive AI-powered recommendations that drive measurable improvements across operations.

The Always-Optimized™ platform combines battle-tested machine learning techniques for structured data analysis with Generative AI capabilities, refined over more than a decade of enterprise deployments. Our technology enables dynamic feature engineering, automatically discovering complex patterns across disparate data sources and connecting operational metrics with contextual factors to solve the hardest challenges in customer and manufacturing operations.

Since 2013, SparkBeyond has delivered over $1B in operational value for hundreds of Fortune 500 companies and partners with leading System Integrators to ensure seamless deployment across customer and manufacturing operations. Learn more at SparkBeyond.com or follow us on LinkedIn.

Features

No items found.
No items found.

It was easier in this project since we used this outpout

Business Insights

Apply key dataset transformations through no/low-code workflows to clean, prep, and scope your datasets as needed for analysis

Predictive Models

Apply key dataset transformations through no/low-code workflows to clean, prep, and scope your datasets as needed for analysis

Micro-Segments

Apply key dataset transformations through no/low-code workflows to clean, prep, and scope your datasets as needed for analysis

Features For
External Models

Apply key dataset transformations through no/low-code workflows to clean, prep, and scope your datasets as needed for analysis

Business Automation
Rules

Apply key dataset transformations through no/low-code workflows to clean, prep, and scope your datasets as needed for analysis

Root-Cause
Analysis

Apply key dataset transformations through no/low-code workflows to clean, prep, and scope your datasets as needed for analysis