Claims Analytics

(Insurance Industry)

ROI: Return of $900K per annum (19X ROI) for a group of 100 claims consultants.

The aim of Hyper Anna is to empower claims managers to identify issues themselves, with self-serviced insights, based on insights from many different dimensions across a number of different business lines, without having to wait on ad-hoc reports being built by the business.

Problems we were tasked to solve and audience

The facts:

  • Claims managers need timely information about the operational performance of their claims teams, including the volume of claims processed, time to settlement as well information about claims costs, including recoveries and case estimates.
  • The company has observed that the lack of sufficient regular reporting on key risk indicators and performance of claims teams has amounted to significantly higher costs due to not being able to identify effectively fraudulent claims, delays in the claims management process or the trend in claims costs.
  • Hyper Anna was engaged to help a claims team of a multinational organisation understand the types of claims by different segments to enable them to maintain an edge in a competitive and rapidly changing environment.

    The aim of Hyper Anna is to empower claims managers to identify issues themselves, with self-serviced insights, based on insights from many different dimensions across a number of different business lines, without having to wait on ad-hoc reports being built by the business.

    Frequently used terms:

  • Insurance Claims
  • Cause / Nature of loss
  • Operational efficiency
  • Claims processing
  • Audience

  • Management
  • Claims Managers / Consultants
  • Data

  • The data is from January 2016 and onwards as the data is automatically updated
  • The data includes rich financial information as well as claim numbers, enabling the claims managers to compare performance across dimensions including
  • ASSOCIATED CLAIM IDS (eg.claim number, policy number)
  • TIME & DATES (eg.loss date, lodgement date)
  • CLAIM PROCESSING INFORMATION (eg. claim decision status, claim status)
  • LODGEMENT TIMING INFORMATION (eg. time between lodgement and expiry, time between inception and lodgement)
  • LOSS CATEGORIES (eg. nature of loss, cause of loss)
  • BRAND SEGMENT (eg. policy brand)
  • PRODUCT INFORMATION (eg. product type, policy type)
  • BUSINESS SEGMENT (eg. line of business)
  • CLAIM TEAM INFORMATION (eg. claim lodgement consultant, claim team manager)
  • LOCATION (eg. risk postcode, loss state)
  • NUMERICAL MEASURES (eg. claim incurred, claim payment)
  • Existing Process

  • Current ‘regular’ reporting is performed on an ad-hoc basis, which is provided by the business. There is a lack of sufficient regular reporting, which has contributed to significantly higher costs for the department.
  • In addition, there is a lot of ad-hoc reporting required stemming from identifying specific issues and needing to drill down further to investigate. Although these reports are extremely important for decision makers and needed timely, these reports can take several weeks to produce.
  • Result delivered (sample questions)

    Sample Questions

    Anna allows the claims team to self-service insights through Anna, with the ability to break claims insights down by:

  • Different brands, lines of business and state
  • Trend of claim volume by brand
  • Mix of claim volume by line of business
  • Mix of claim volume by claim status and brand
  • Teams and consultants
  • Top 10 teams by number of claims
  • Top 10 consultants by number of claims
  • Trend of claim volume by policy type for Tim Smith
  • Motor, or property
  • Average claim cost trend for Motor
  • trend of average claim cost by nature of loss for property
  • Top suburb for theft or burglary by claim volume in NSW for property
  • Cause of loss
  • Mix of cause of loss for motor by claim volume
  • Mix of nature of loss for home by claim volume
  • Duration
  • Trend of claim volume by finalisation delay band
  • Trend of claim volume by time between inception and lodgment
  • Ex gratia payments
  • Number of ex gratia payments by policy type
  • Not only did the Hyper Anna solution give management and claims managers the ability to ask Anna a question and get a response in real time, but Anna is also proactive, in that she continuously analyses their data to help draw attention to new insights that they may not have discovered, had they not asked the question.

    Summary of value


    Business performance and insights teams produce analysis packs in response to ad hoc analytical queries from the business - namely, claims managers and consultants. Before Anna, the process of gathering the required data and insights was estimated to take an average of 5 business days (40 hours) to respond to a single brief, with a large team being the size of approximately 10 people supporting the business to service such requests.

    After the implementation of Anna - this was reduced to 15 minutes - namely, the claims consultant being able to directly access data and insights, satisfying his/her own insights request, instead of waiting for a week for a prioritised brief to be actioned. Across a team of 100 claims consultants & managers, this equated to a time-saving worth over $900K per annum (19X ROI).

    Summary of value

    Hyper Anna empowered management and claims managers to self-served analytics, this allowed them to identify issues themselves without having to wait on ad-hoc reports being built by the business, saving time, improving efficiency and reducing costs.

    Management and claims managers were able to get insights from many different dimensions across a number of different business lines giving them the ability to

  • Monitor trends and drivers to claims costs, allowing them to respond accordingly to maintain profitability
  • Quickly identify issues in claims operations, enabling them to investigate further and pursue remediation strategies
  • Monitor performance of their claims teams, ensuring that claims are being processed efficiently through adequate levels of staff
  • Identify early issues, which will reduce operational costs by allowing them to address the problem before it deteriorates
  • Screenshots

    Pro-active insights

    Tasks such as creating your own reports or dashboards require the knowledge of where to navigate through your data for insights, but this has been proven difficult and time consuming.

    Using the power of AI, Hyper Anna executes millions of hypotheses to discover complex patterns in datasets. The most practical and relevant insights are then pro-actively delivered to your inbox. In contrast to large teams of analysts finding answers from data, Hyper Anna will single- handily do it in a matter of hours.

    In this example below, Hyper Anna automatically suggests a manager to look at categories that are underperforming significantly.

    Ask anything

    Getting insights from data is now as simple as asking a question.

  • Surpass the “create vs. consume” dichotomy of reports and dashboards by giving all users access to a self serve platform
  • Govern your data centrally but democratise access to all
  • In this example below, a manager has asked Anna to analyse the store performance by department.

    Hear it from our customers