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Big Data Analytics for Financial Services

Whether you’re a credit card company, a retail bank, a private wealth management advisory, an insurance/annuities firm, a private equity/venture fund, or an institutional investment bank, the common underlying problem is massive amounts of multi-structured data living in multiple disparate systems. Datameer is helping American Express, Citibank, TIAA-CREF, and others in every financial services segment to combine and analyze big data for:

Customer Analytics

Combining all customer interaction data from transaction, CRM, call center, mobile apps, website, social media, digital ads and analyzing it together helps financial services companies truly understand the customer’s journey. With big data analytics, you can answer questions like what campaigns convert prospects to customers, how do I target ads to different consumer segments for higher conversion, and what behavior predicts churn.

Compliance Analytics

Regulatory compliance mandates continue to evolve – and most involve the aggregation, analysis, and reporting of massive diverse data sets that span business lines and are managed by many teams. Responding to the latest regulatory mandate is made easy with Datameer’s architecture, which balances the needs for rapid ad hoc self-service analytics with enterprise grade governance, access controls, and scheduling/automation capabilities.

BCBS 239: The BCBS 239 mandate is a comprehensive set of principles related to risk data aggregation and risk reporting (RDARR). In order to be compliant, financial services institutions need a big data architecture that allows for comprehensive data aggregation and analysis, complete data governance and lineage, and flexible manual and automated reporting capabilities. Learn how Datameer’s capabilities align to the key principles and are the perfect solution to fast tracking BCBS 239 compliance.

Fraud Analytics

Combining and analyzing large volumes of data like transaction, geo-location, IP addresses, merchant data, network traffic data and authorization and submission data helps financial services companies to identify anomalies and patterns of behavior that signals potential fraud. With these insights you can dramatically improve security and prevent fraud.

Operational Analytics

Your employees and your business are operating at a pace and level of complexity that you’ve never experienced before. In addition, operational risk mitigation is at or near the top of every bank’s operating agenda. It is critical to monitor and report on employee behaviors, key operational process performance, and other critical KPI’s to ensure that you are operating efficiently and at a level that mitigates risk.

eBook: Fraud & Compliance with Big Data Analytics

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eBook: Top 3 Big Data Use Cases in FinServ

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