Artificial Intelligence and Cognitive Analytics

Machine Learning

Machine Learning Use Case: Fraudulent detection

INDUSTRY: BANKING

Problem: How do I protect my company/bank from future fraudulent transactions?

Solution: AI Predictive Analysis and Fraudulent detection

Development of a fraud detection model using a synthetic financial dataset

• Rapid integration of actual transactions and checking for fraudulent transactions.
• Discover features that are linked to fraudulent transactions by providing visuals of the data.
• Reduce time and resources for manual detection of fraudulent transactions.

Machine Learning Use Case: Digital Footprint Engine

INDUSTRY: MEDIA

Problem: How can a media company augment their understanding of consumer segments on the digital space

Solution: Digital Footprint Engine – an integrated solution that processes image, text, and video content into a single format that can be analyzed for detecting topics on the digital space

Aggregating different data sources and to to find and understand customer behavior patterns and segments. Profiling and coming up with different applications– possibly a recommendation engine, a consumer consumption.

Machine Learning Use Case: Store Network Optimization

INDUSTRY: REMITTANCES

Problem: How do I know where to build my next remittance center to maximize foot traffic and transactions without cannibalizing the business of my existing stores?

Solution: SNO Mapping using Predictive Analytics and Statistical Modeling

Retailing and networks. Data points are market indicators, statistical measures

Image Processing & Video Analytics

Image Processing and Video Analytics Use Case:ECG Anomaly

Client’s Industry: Hospitals, Clinics, Wearables

Problem: How do I quickly and efficiently analyze my ECG reports?

Solution: AI powered platform in ECG reading and diagnosis

Natural Language Understanding

Natural Language Understanding Use Case: Topic Modeling and Sentiment Analysis

Client’s Industry: Politics / Media

Problem: How can I tell in real time how my constituents / customers feel about me and what topics are they most interested about?

Solution: Topic Modeling and Sentiment Analysis Dashboard