Financial Services

Consumer analytics and engagement

Engaging your customer at the right time with the right offering through the right channel is critical to market to customers today.

Consumers are generating approximately 2.5 exabytes of data every day, through different channels, internal and external, which finance companies must tap into to effectively market their products.

With disparate sources, such as CRM, ERPs, social media feeds, web data—with structured, unstructured, and real-stream data—BIRD provides the most effective analytics platform.

Some use-cases that BIRD can address

  • Customer segmentation
  • Tracking campaigns
  • Understanding customer attrition
  • Discover key influencers on your customer transactional behaviors
  • Identify key topics of interest for your customer
  • Sentiment analysis

Advanced custom solutions: we use advanced ML-based solutions and models to predict customer lifetime value, customer attrition, and profitability.

Real-time fraud detection

There is no question as to the seriousness and the need for financial institutions to have this functionality. Fraud happens in various aspects of an institution such as identity thefts, system hacking, data theft etc. It is especially important that these threats are detected in real-time.

Using descriptive and advanced ML models, we can identify customers’ behavior patterns using their large amounts of data. Millions of customer interactions, transactions, system logs should be analyzed in real-time to detect any unusual behaviors using learned model behavior.

BIRD’s lambda architecture in which real-stream data can be fused with batch data helps to ensure that no details are missed in this pattern detection.

Risk management

Risk management is mandatory for financial institutions to preserve trust and comply with regulatory requirements.

Risks can arise from different sources such as competitors, investors, regulators, and customers. Risks can also differ in importance and cost. With BIRD, you can identify, prioritize, and monitor risks. With machine learning and its automated, advanced risk-scoring models, BIRD uses huge amounts of data from customers, financial lending, and insurance products, etc., to help improve efficiencies and mitigate risk.

Credit Risk Assessment is one of the most important applications of Risk Management. BIRD offers a solution to automatically identify the creditworthiness of customers based on data coming from their past payment behavior, credit history, and net value etc.

There are many other financial user cases such as analysis of P&L statements, identifying areas of revenue growth. BIRD lets users easily slice and dice data down to the row level, often important for financial institutions.

BIRD is the fastest Big Data analytics platform offering full-stack BI & AI-driven analytics