As financial markets emerge from recession, business focus is shifting rapidly from reducing cost to growing revenue. Many organizations are looking to (big) data and analytics to drive competitive advantage and growth. Important opportunities include compliance, risk & regulatory reporting and customer 360.
A key obstacle facing most large organizations is accessing data trapped in legacy business and technology silos and making it usable by the business. Big Data solutions help - they are good at liberating and co-locating data. However, they often struggle to make it usable. Creating a "data lake" where rigid structure is not required can result in yet another silo of unusable data where context, meaning and provenance are lost.
There is a better way. Leading financial organizations are turning to semantic technology to address their data opportunities. Investment protection, speed, agility and enabling the business are key reasons for the adoption of this model-driven approach.
This is game changing for financial institutions, allowing them to accelerate existing programs and create new ones not previously possible.
Semantic technology has been around since the late '90s. It enables data to be modeled, managed and consumed in an agile, standardized, human friendly and machine readable way. Whereas search technology allows you to find data, semantic technology enables you to find it, understand it and take action on it. To learn more about semantic technology, check out the Semantic University at http://www.cambridgesemantics.com/semantic-university
So how are leading organizations using semantic technology to leverage their data? Select semantic technology enterprise use cases include:
- Customer and Data On-boarding:
Puts data mapping and automated ETL generation in the hand of business analysts, streamlining on-boarding and saving time and money. A by product of this process is active meta-data. Always up to date, it provides full data lineage and makes data consumption easy for business users. - Customer 360
Combines data from inside and outside the enterprise, including structured and unstructured sources, to create a complete view of the customer. Applications include call center compliance, know your customer and next best action - Compliance Reporting and Data Lineage
Mapping your data to industry models like FIBO (The Financial Industry Business Ontology) creates shared understanding, tracking and reporting of data. Data aggregation, data lineage and standardized reporting are all easier with semantic technology. - Forensic Investigation and Surveillance
Detect and investigate adverse events across networks of interrelated people, content and transactions. Monitor and enforce compliance with corporate email policies.
- Equity Analyst Workbench
Provides an integrated environment for tracking related companies, monitoring sentiment, spotting trends, and developing hypotheses. Integrates watch lists, trade data, social media and news sources.
Big financial institutions are using semantic technology today to better understand, manage and unlock the value of their data. To learn more about these and other practical applications of semantic technology, follow us on twitter @CamSemantics or contact me at mloughlin@cambridgesemantics.com
