Ontology normalisation

Ontology normalisation
Customer

Swiss Insurance company

Normalising existing ontology and migrating to a new standardised ontology version

Challenge

  • Existing Ontology too large, makes it hard to manage and analyse

Solution

  • Normalised existing tables by splitting them into multiple units
  • Built toolkits and ontology library to support development of new ontologies
  • Conventions and development guidelines
  • Performance optimisation and reporting

Impact

  • Normalised 3 tables resulting in final ontology of 18 tables (approx. 2.3B rows)
  • 30% reduction in total ontology build time
  • 60% reduction in disk spillage

Foundry Center of Excellence

Customer

Major Swiss Insurance Company

Supported the creation of a Foundry CoE by helping create solid bases, training internal employees, and delivering high impact projects on the new platform

Challenge

  • Contract signed by client with Palantir to use Foundry as their analytics platform
  • Lack of internal employees skilled on this new platform
  • Wanted Foundry to be widely adopted within all analytics projects and workflows in the company

Solution

  • Helped create CoE to manage and encompass all projects delivered on Foundry
  • Unit8 delivered many projects, built shared libraries and aided in the training of employees
  • CoE Responsibilities:
    • Governance
    • Enabling efficient usage
    • Sharing best practices, upskilling, training

 

Business Impact

  • Enabled all BUs to tackle big data projects efficiently
  • Created solid bases for future projects by building libraries and training internal employees
  • Increased usage of Foundry as analytical platform compared to existing, less efficient solution

Summarization and Q&A Assistant to streamline Risk Operations

Customer

Swiss Insurance

A solution based on Azure Open AI & Cognitive Search allowing users to easily understand thousands of risk documents and policies with human-like answers 

Challenge

  • With thousands of internal and external risk policy documents staying up to date and understanding which policies apply to which scenarios is challenging 
  • These insights were spread across multiple sources including PDF’s, Wiki’s, Sharepoint, Excel and others 

Solution

  • Information relevant to a user question are identified and retrieved using Azure Cognitive Search.
  • The retrieved articles are fed to Azure OpenAI services. The output consists of a summary with references to documents used in the answer.
  • The scope of the retrieved documents and the chatbot responses is limited to the customers internal documents.

Business Impact

  • Speeding up information retrieval and summarizing key insights from a large amount of structured and unstructured data
  • On client demand, information can be extended to other public sources or increase the  internal sources of a company’s data

Insurance Contract Analytics

Insurance Contract Analytics
Customer

Swiss Insurance Company

Creating an Azure distributed cluster to analyze and assess risk exposure in insurance based on intelligence extracted from contracts

Challenge

  • High legal costs due to delayed understanding of contract content are a major cost factor
  • Millions of insurance contracts with different wording, exclusion and inclusion clauses
  • Difficult to categorize and quantify risk profile of grops of contracts

Solution

  • Natural Language Processing solution to analyze contracts
  • Contract corpus data lake implementing business rules for contract intelligence risk resolution
  • Backend system for underwriters to better formulate future contracts and reduce risk exposure

Business Impact

  • Client is able to quickly quantify risk exposure based on contract language
  • Underwriters following guidance system resulting in more profitable contracts.
  • Reduced legal and operational costs and improved process excellence

Analytics Maturity Assessment

Analytics Maturity Assessment
Customer

Major Swiss Insurance Company

Conducted a comprehensive maturity assessment of analytics capabilities, allowing for better future strategic planning and increased transparency

Challenge

  • A global insurance company was facing different levels of analytics maturity across its business units and had little visibility on the existing capabilities, tools, standards and project roadmaps

Solution

  • Co-developed and conducted a comprehensive analytics maturity assessment by means of a written questionnaire and follow-up interviews.
  • Many dimensions were considered, including analytics strategy, design and ethics

Business Impact

  • Substantial gains in transparency for the client on its existing capabilities
  • Results served as a baseline for future group-wide strategy initiatives regarding analytics, such as strategic workforce planning or analytics governance

Analytics Governance Framework

Analytics Governance Framework
Customer

Major Swiss Insurance Company

Developing a comprehensive governance framework combining findings from a maturity assessment, ISO standards and sector best practices

Challenge

  • No existing framework defining the ideal state and goal of the advanced analytics governance efforts
  • Several factors suggesting that a framework to oversee analytics model governance was needed
  1. Upcoming regulations
  2. Improve collaboration
  3. Operational and reputational risks

Solution

  • Co-designed a comprehensive ideal governance framework that set a target for the governance and analytics efforts in the organisation
  • Framework developed based on previous maturity assessment, ISO standards and external best practices

Business Impact

  • Mitigation of operational, financial, legal & reputational risks from analytics solutions through best-in class governance practices
  • Standardised and more efficient development practices

Reporting Automation

Reporting Automation
Customer

Swiss Insurance company

Creating automatic reporting tools through data centralisation, eliminating tedious and repetitive tasks anc increasing quality of reports

Challenge

  • An insurance company creates quarterly financial reports. They were manually extracting data, exchanging it via emails back and forth for aggregation in Excel and further validation

Solution

  • Ingestion of the source data to the data lake and implementation of the pipeline to validate and clean the data.
  • UI application was built to streamline the process reporting process by giving access to all parties and allowing modifications if necessary

Impact

  • Eliminated the repetitive and tedious manual process, reducing the amount of time needed to create reports
  • Improved the quality of reports by reducing the margin of human error

Live Contract Renewal Dashboard

Live Contract Renewal Dashboard
Customer

Swiss Insurance company

Creating a live contract renewal dashboard allowing underwriters and region directors to have a better understanding of trends and current contract status

Challenge

  • Create live dashboard and weekly report to track contract renewal progress

Solution

  • Built a big data pipeline to track contract status progress and calculate year-to-year metrics
  • Developed application to visualise live data
  • Created charts enabling easy visualisation of contract renewal status within the market

Impact

  • Underwriters are now able to see live data and adjust contract pricing
  • High-level automated reports allow region directors to have a better understanding of current trends and statuses of contracts

Analytics Maturity Assessment

Analytics Maturity Assessment
Customer

Swiss Insurance company

Conducting a comprehensive maturity assessment of analytics capabilities, allowing for better future strategic planning and increased transparency

Challenge

  • A global insurance company was facing different levels of analytics maturity across its business units and had little visibility on the existing capabilities, tools, standards and project roadmaps.

Solution

  • Co-developed and conducted a comprehensive analytics maturity assessment by means of a written questionnaire and follow-up interviews.
  • Many dimensions were considered, including analytics strategy, design and ethics.

Impact

  • Substantial gains in transparency for the client on its existing capabilities.
  • Results served as a baseline for future group-wide strategy initiatives regarding analytics, such as strategic workforce planning or analytics governance.

Analytics Governance Framework

Analytics Governance Framework
Customer

Swiss Insurance company

Developing a comprehensive governance framework combining findings from a maturity assessment, ISO standards and sector best practices

Challenge

  • No existing framework defining the ideal state and goal of the advanced analytics governance efforts

Solution

  • Co-designed a comprehensive ideal governance framework that set a target for the governance and analytics efforts in the organisation
  • Framework developed based on previous maturity assessment, ISO standards and external best practices

Impact

  • Mitigation of operational, financial, legal & reputational risks from analytics solutions through best-in class governance practices
  • Standardised and more efficient development practices

Analytics Center of Excellence

Analytics Center of Excellence
Customer

Swiss Insurance company

Supporting a strategic initiative to migrate current pipelines and use cases to the Foundry platform

Challenge

  • Need to offer company-wide support in the transition from old systems to Foundry
  • Multiple teams without prior Foundry knowledge needed to move their pipeline and use cases on the platform

Solution

  • Multiple support processes depending on the needs
  • Support including: office hours, architecture reviews, pair programming, implementation & handover, code reviews, operational support, etc.

Impact

  • Supported strategic migration to Foundry, onboarding new users and setting up data foundations
  • Platform usage increased from 2’000 to 5’000 users
  • Provided support for 25+ projects
  • CoE team grew from 2 to 10+ people in 2 years

Claim risk scoring

Claim risk scoring
Customer

Leading Swiss insurance company

Detecting potential claim fraud among health insurance clients

Challenge

  • Undetected fraudulent insurance claims may cause a significant blow to insurance companies’ revenues

Solution

  • Implemented fraud scoring KPI’s together with visualisation
  • Enabled multiple insurance companies to use the API to validate claims of their customers
  • Ensured auditability and idempotency of the results

Impact

  • Automated the fraud-flagging process
  • Created tools allowing enhanced manual inspection of the most suspicious claims for multiple companies

Climate risk scoring

Climate risk scoring
Customer

Swiss Insurance company

Developing a climate risk scoring model scalable to the entire insurance portfolio and able to determine climate risk exposure in real time for any locations

Challenge

  • Current climate risk scoring model is limited
  • Scoring too time-consuming and inability to score for many locations at once
  • Model needs to be scaled to the whole insurance portfolio

Solution

  • Implemented new model in Big Data environment capable of ingesting high volumes of data
  • Used external weather model to predict climate risk score and estimate impact on insurance portfolio

Impact

  • High performance model now allowing to evaluate climate risk scores in real time
  • Ability to display climate risk scores for any of the more than 2B locations in the insurance portfolio

Financial health watchlist

Financial health watchlist
Customer

Swiss Financial Institution

Developing a centralised solvency and risk assessment model to create risk exposure reports automatically and improve data quality

Challenge

  • Difficulty to predict total exposure to financial losses resulting from companies at risk of becoming insolvent
  • Current risk reports are generated manually and data quality is not guaranteed

Solution

  • Central gathering and processing of the relevant partner data allowing for central risk modelling and data quality checks
  • Automatic creation of monthly risk reports based on the curated data

Impact

  • Improved risk management capabilities through information centralisation and standardisation
  • Improvement in data quality and report generation
  • Possibility to create reports dynamically to visualise more aspects than before

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