Analytics and insight services that help you understand your customers from every angle

Get actionable insight and grow your organization with our full spectrum of insurance analytics and insights services.

Scoring and Rating

Flexibility and collaboration are key to a smooth, data and analytics journey. IMS offers full flexibility and complete openness in scoring and rating. Precisely assess risk for each policyholder and encourage safe driving behaviors while generating actionable intelligence for your entire book of business.

Flexible, Collaborative Solutions for your Business Needs

IMS Scoring and Rating Options

Not all insurers are alike. IMS recognizes that there is not a “one size fits all” approach to scoring. IMS provides flexible options to meet your program and business objectives.

  • Option A

    Direct access to IMS’ proven scoring models in addition to IMS' internal analytics team to develop or refine your unique scoring and rating system.

  • Option B

    Your insurance actuarial models refined with the benefit of IMS' expertise and available internal analytics team.

  • Option C

    Work with one of IMS’ analytics partners.

Driving Behavior Insights – for Scoring

IMS analyzes the most number of driving insights for your scoring consideration. These insights are delivered to policyholders as coaching and feedback and to insurers as components to be used in generating a driving score. Insurers choose the driving insights most relevant to their program objectives.

Distracted Driving Insights – for Scoring

Insurers can detect distracted behaviors, including time, duration and even severity level of smartphone usage while driving.

Distracted driving insights are measured and provided back to the driver for coaching and driving behavior improvements. Insurers are also able to take these insights and formulate a distracted driving score or include them in an overall behavioral assessment score based on program requirements.

Why Choose IMS for Scoring and Rating?

  • Complete transparency and collaboration in our modeling, providing insurers with a tailored scoring experience that meets the unique product, market and/or program goals.
  • Differentiation created through a Differentiated Rating System and leverage of IMS’ experience in Scoring UX to display scores in a meaningful, easy-to-understand experience for policyholders that results in positive improvements in driving behavior.
  • Experience based on over 5 trillion collected data points and combinations of machine learning and AI techniques instilled over the last decade – and growing exponentially.
  • A more accurate representation of driving behavior given that, unlike other scoring models, IMS’ scoring goes beyond discrete events.
  • Experience working with a multitude of data sources, due to the data source agnostic approach of the DriveSync® platform – preventing scoring biases that may be caused by data sources.
  • Scoring solutions that automatically take into account the difference between passenger and driver as well as mode of transportation.

FNOL Automatic Incident Detection

Immediately begin assisting the policyholder with the best course of action

When an incident takes place, the involved vehicles are frequently towed and taken to a storage lot. This not only delays the repair and adds to the claims cost, but during this time, the owner also loses visibility on where his/her car is located and its status. IMS’ Automatic Incident Detection service leverages IMS’ advanced analytics capabilities to inform your First-Notice-of-Loss (FNOL) process and accurately identify collision incidents. In doing so, it reduces inefficient claims expenditure due to avoidable secondary towing and storage charges.

Automatic Incident Detection for the FNOL insurance process can provide auto insurers with rapid notification of a claims incident, allowing insurers to immediately begin assisting the policyholder and processing the claim, while directing the towing service to the policyholder’s desired service center. It does so by leveraging available device sensors (e.g. accelerometer, gyroscope), collected driving data (e.g. speed), and contextual data sources (e.g. road segment data) to detect crashes with high confidence. This enables IMS’ Automatic Incident Detection capabilities, including intelligent delivery of crash notifications, to program participants, and their emergency contacts, as needed.

IMS' Automatic Incident Detection Service

What's Included:

  • Data cleansing

  • Geo-spatial reconstruction and contextual analysis and reconstruction

  • Incident vehicle dynamics profile analysis

At the point of incident detection using IMS’ Incident Detection service, insurance agents can immediately:

  • Determine the state of the driver and offer to contact emergency services.
  • Confirm whether the vehicle requires towing.
  • Confirm the driver’s consent to initiate a claim/FNOL event with his/her insurer.
  • Extend valuable and convenient services such as arranging for a car rental or hotel in accordance with the driver’s policy.


  • Reduce and manage claims costs with real-time collision and location information for incident assessment purposes – helping to avoid unnecessary towing and storage charges.
  • Improve response times with detailed reconstructions of incidents and associated driving behaviors.
  • Minimize the latency between each incident and the resolution of the incident claim.
  • Mitigate risk of excessive, non-reimbursable claims costs to the policyholder.
  • Improved peace of mind for drivers – knowing their incident is being helped efficiently, carefully and with their interests also in mind.

Incident Analysis / Crash Forensics

Reduce claim cycles with vital crash data information

Vehicle collisions are the most common way that people or collision details are falsified, but unfortunately, some car accidents are staged on purpose. In fact, accident fraud is one of the more prominent types of auto insurance fraud costing approximately over $8 billion in lost revenue for the insurance industry.

When a vehicle collision occurs, it’s important for insurers to piece together a clear picture of what happened during a car accident in order to accurately evaluate liability. IMS telematics crash data provides unbiased forensic evidence that can enhance crash analysis activities and help insurers make more informed settlement decisions.

IMS crash forensic data examine a myriad of evidence including:

At the Time of the Event

  • Day of week (Monday-Sunday), location, date, time, of the crash
  • Trip distance and duration
  • Vehicle Identification Number (VIN)
  • Normalized 3-axis accelerometer data profile before and after the crash (g-force)
  • Angle/direction of impact
  • Speed profile before and after the crash
  • Vehicle roll-over information
  • Crash detection confidence (a score between 0-100)

Post-Crash Forensics

  • Vehicle towing (i.e. Was the vehicle towed after the crash? If so, how far?)
  • First trip after crash (i.e. did the vehicle drive out of a body repair shop next?)
  • Time delay between crash and next trip
  • Potential diagnostic issues or device disconnects

Auto Insurance Premium Leakage Reports

Rapidly detect, investigate and prevent insurance fraud

Inconsistent underwriting data and policyholder misinformation continue to negatively impact the underwriting process affecting the insurer’s ability to accurately classify risk and apply the correct premium and conditions of an insurance policy to protect both the policyholder and the insurer. Recent studies have shown the auto industry is facing over $28 billion in premium leakage. IMS Auto Insurance Premium Leakage Reports help forward-thinking insurers not only detect underwriting fraud but to prevent it as well.

IMS Premium Leakage Reports examines a myriad of evidence including:


Insurers can now improve efficiency and minimize the risks associated with vehicle garaging fraud and radius of vehicle travel information provided by policyholders misreporting garaging addresses. Garaging Location Analysis allows carriers to validate policyholders address, secondary garaging locations, and insight into a more granular breakdown of the radius of vehicle travel.

Reporting and Analysis

  • Automatically determine home and work locations based on travel patterns
  • Monthly report providing estimated home and work locations at a suitable level of abstraction (i.e. zip code) with % of time spent at each location and measures of confidence
  • Exceptions highlighted to characterize individuals that changed jobs, moved, or went through a lifestyle change

Key Benefits and Value

  • Provides actual (not reported) garaging location for risk assessment
  • Enables analytics based on time spent at work (or at home)
  • Enables proactive change of address processes (automatic coverage reassessment)
  • Can be used to deliver tailored transport incentives

Mileage Verification

Miles driven is a primary predictor of driver risk. Some policyholders underestimate annual miles driven to help reduce their premium. Mileage Verification allows insurers to receive verified data without impacting driver privacy and characterizes participants using commute distances derived from actual observations, and estimated annual mileage based on historical driving patterns (i.e. total exposure).

Reporting and Analysis

  • Monthly report providing commute distance derived using actual travel patterns, participant commute route diversity, and extrapolated annual mileage
  • Notable changes highlighted for individuals that changed commute patterns or route diversity

Key Benefits and Value

  • Provides actual (not reported) commute distance for analytics purposes
  • Can be used to incentivize route diversity and combat repetitive route fatigue

Undisclosed Drivers

Policyholders sometimes fail to update and disclose any driver(s) that have regular or frequent use of their vehicle(s). These undisclosed drivers are estimated to cost the insurance industry over $2.7 billion in lost annual premiums. Undisclosed Driver Reports provide insight and estimates of total drivers sharing each vehicle, and associate individual trips with each driver mapped by their the unique “fingerprint” driving pattern.

Reporting and Analysis

  • Monthly report providing the number of drivers and percent of shared trips completed by each driver
  • Identify and highlight additional drivers based on evident changes to unique driving patterns

Key Benefits and Value

  • Provides the actual vs reported number of drivers for a vehicle to help identify undisclosed drivers and prevent fraud
  • Provides more accurate risk perception insight to help identify inadequate risk profile of policyholders

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