Quantum Leap: Harnessing the power of AI at scale

How Fractal integrates knowledge graphs for better business decisions While Fractal has used knowledge graphs to solve client use cases in the past, it has also supported enterprises with its knowledge graph initiatives. The organization employs knowledge graphs built by assimilating knowledge from multiple heterogeneous sources and condensing it into a knowledge graph. Fractal helped the organization build the infrastructure for data engineering, which hands over the transformed data to NLP engines for extracting the triples (building blocks of a knowledge graph).

INPUTS

OUTPUTS

SOURCES

GRAPHS(NODES & EDGES)

AZ Internal Data like omics, literature, chemistry

Databases

Other open source data like semantic scholar

Property Graph

DATA TYPES

SEARCH & REPORTING

NLP + GRAPHS

Fig 1: Fractal knowledge graph 2 initiative for life sciences company

How Fractal is ahead of the curve in client servicing through knowledge graph solutions Cost-effective fraud detection for a top British Commercial insurance firm We detected and identified multiple frauds involving solicitors, doctors, repairers, and claimants, who were then handed over to the Special Investigative Unit. This led to 40% savings on SIU’s efforts to manually go through every claim.

With our solution, we identified incremental cash information for non-PAN accounts using fuzzy matching. We also recognized Shell companies, Benami properties, cash splits, and other such patterns using link analysis and pattern mining. This helped to establish high-risk fund flow channels in a large, connected set of accounts.

A leading pharmaceutical company in the US

Based on the members’ profiles, past purchases, and conditions, we identified pharmaceutical items for upsell.

Customer acquisition, expansion, and segmentation in a major UK-based CPG enterprise

Fractal built a Consumer 360 knowledge graph related to company purchases. This helped the organization find loyal customers across different brands and regions and enabled lead generation and customer segmentation.

Detection of tax evasion and non-compliance for an Indian Government entity

Fractal identified potential cases of tax evasion and non-compliance for an Indian Government entity. The approach was to identify entities with cash deposits, not in line with their income using pattern matching.

2 Building a Knowledge Graph with Spark and NLP: How We Recommend Novel Drugs to our Scientists (slideshare.net)

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