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Turn Insurance Digital

Automate business processes and create new, innovative business models integrating data analytics and providing next generation customer experience.
Current Situation

Insurers have widely built data lakes – which often lack a semantic “understanding” of data points and their interconnections. Analytics and reporting require manual model definitions by data scientists – largely limiting capabilities and speed of analytics.

Objective:

Establish a semantic core graph and scale it up with ontologies, covering business structures and models as well as external graphs, all engineered decentralized.

(e.g., lines of business, products, policy data)

How CID can support:
  • ‍CID’s Neuro Computing blends graphs from internal and external sources,
  • Builds dynamic structures without a static model definition, and
  • Continuously updates an unified, agile graph
Objective:
How CID can support:

Add clients, companies, risks, causes of loss, product recalls, and other up-to-date topics and their relationships based on data analytics.

(e.g., healthcare clients, autonomous driving, airbag issues)

  • ‍Unsupervised topic detection in claims, research, CRM...
  • Automated creation of graph nodes and edges for insureds, persons...
  • Enrichment of master and meta data
Objective:

Apply real-time graph and event analytics to derive actionable insights and business process support.

(e.g., emerging risks, trigger events, sentiment)

How CID can support:
  • ‍Automated detection of trigger events (e.g., M&A activity, product liability issues, lawsuits)
  • Qualitative and quantitative evaluation (e.g., sentiment)
  • Agile perspectives on graph (e.g., matching investment exposure with financial market developments)
Objective:
How CID can support:
Objective:
How CID can support:
Objective:
How CID can support:
How Insurers Benefit

Apply Artificial Intelligence to data lakes and create a truly comprehensive, agile Knowledge Base ready to power pro-active analytics, business applications, and processes with reliable but dynamic models and up-to-date information.

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