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A different approach:
We predict your next fraud case

~$1 trillion

Annual net written premiums in the United States


Yearly fraud estimation for USA only


Average cumulative Loss Ratio in 10 years for top 10 countries


Additional profit to insurance companies in top 10 countries due to 1% Loss Ratio reduction
  • The
  • As an insurance carrier, proper risk evaluation is vital to your business.Yet cases of fraud continue to rise, with deceptive claims being caught- only in retrospect.

    In fact, Insurance companies in 10 leading countries show a 75% cumulative loss-ratio during a 5 years period , and above 100% in 10 years.

    It seems that the old fashioned styles of insurance quotation can no longer keep up with the true user’s behavior, and with fraudulent claims becoming more and more sophisticated, your data just isn’t enough.

    Time for a new approach.

  • The
  • Introducing getmeIns.

    A life changing solution, getmeIns™ is a mobile first platform that incorporates user behavior analytics and link analysis to prevent insurance fraud at point of sale and significantly reduce Loss Ratio.

    By using behavioral analytics, link analysis, machine learning, and advanced visual algorithms, getmeIns™ specializes in generating a stream of valuable alerts and fraud predictions for insurance providers around the globe.

  • Our
  • Mobile first platform that uses behavioral analytics technology to promote more personalized insurance products and to detect potential fraud at point of sale (vs. at claim).


    comprehensive solution allows insurance providers to reduce Loss Ratio and gain additional profit on their main business.

How we do it.
1 Profiling
Profiling process starts with learning a real user behavior with integrated IoT mobile first platform. We generate unique user profiles based on personal activities, habits and lifestyle. Further we use open data sources as well as insurance carrier provided data sources to extract general sentiment and identify potential risk factors.
2 Analyzing
getmeIns™ platform is designed to process huge amounts of structured and unstructured data. Our analytical engine employs up-to-date graph database technologies to perform link analysis and identify possible fraud rings. We combine multiple database technologies both relational and No-SQL to perform data fusion. Specifically crafted photogrammetry algorithms allow us to process car damage photos taken with cell phone cameras without using special expensive equipment.
3 Scoring
Adaptive learning is used to create meaningful user profiles. getmeIns™ analytical engine generates risk score by combining user profile with OSINT (Open Source Intelligence) data and link analysis. The score is generated at point of sale when user purchases its first insurance product and it is constantly evaluated when new data arrives.
4 Alerts & Reports
Possible fraud signals such as behavior anomalies, participation in fraud ring, sentiment change and other alerts generated at point of sale are automatically streamed to the insurance carrier in real-time to defeat potential fraud.
5 Smart Quotes
Behavioral analytics in conjunction with our fraud prevention framework allows us to build smart quotes that truly reflect real user behavior. With our "Pay as you Live" philosophy we empower the users to customize their insurance coverage at the tap of a button and purchase insurance products according to their daily needs and changing lifestyles at most convenient price.

Complex Solution

With getmeIns™ you can easily turn on and off different insurance coverages on demand, track your insurance expenses and simplify claim management process.


With getmeIns™ insurance providers can access vital information ahead of time, preventing fraud, significantly reducing loss ratio, and building quotations that truly reflect their user’s behavior.

Unique fraud score

Insurance fraud is always conducted by a group of people. The more human factor is involved in procedure of getting a quote, underwriting, purchasing and claiming insurance, there is more place for fraud. By combining link analysis with sentiment we evaluate potential fraud rings.

Identifying fraud rings

Today most of insurance carriers are still using assumptions in quote generation. In comprehensive car insurance 50 years old safe driver with over-weight and arrhythmia would be traditionally considered by insurance carriers to represent less risk than 19 years old new driver, while our thesis is opposite.

From assumptions to real user behavior

We apply innovative photogrammetric algorithms to pictures taken by smart-phone cameras without using expensive hardware. Pictures are automatically matched against our database to prevent possible reuse of damaged parts in subsequent claims.

Image processing

We use text analytics software to process unstructured data, perform entity extraction and text classification.

Text Analytics


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A different approach:
We predict your next fraud case
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