Aug 16, 2017

Aug 16, 2017

Click-Ins continues combating insurance fraud by launching new Car Damage Image Matching and Cost Assessment platform

Our company Click-Ins Ltd., a Netanya, Israel-based technology firm was founded in 2014 with a very precise mission of helping insurance carriers detect and predict fraud. Click-Ins Ltd.  is a privately-held firm that has attracted capital from both angel investors and VC such as Jerusalem Venture Partners.

Click-Ins, through its revolutionary product - getmeins™, concentrates its efforts at helping carriers predict fraud at point of sale as well as point of claim using a holistic approach that leverages military-grade intelligence techniques. These techniques include link analysis, open source intelligence, text analytics, signal and image processing. Click-Ins believes that carriers struggle to catch fraudulent activity through their existing legacy systems because these systems are usually policy-centric and separated from each other. Click-Ins contends that applying these techniques to an existing set of data with emphasis on unstructured data, the DNA of Insurance Company, can help carriers unlock insights contained within.

Our global vision is reduction of loss ratio by combating insurance fraud at both point of sale and point of claim by using comprehensive approach.

As a hard proof of our unique technology stack getmeins™ was nominated as a second runner up at the most prestigious competition - Luxembourg Fintech Awards held by KPMG. Previously, in February 2017, Click-Ins was was nominated the winner of first Israel Insurtech Competition held by AXA and Jerusalem Venture Partners.

As a part of our G2M strategy we're launching our first product - Car Damage Matching and Assessment. The product detects insurance fraud by matching mobile and digital camera pictures of the damages using photogrammetry, computer vision and remote sensing as well as provides assessment of estimated repair cost.

By processing new and historical damage pictures we generate unique signature (fingerprint style) and match it to the database to detect multiple use of the same damaged parts as well as exaggerated claims.

The process is fully automated by using a combination of proprietary photogrammetry algorithms, Computer Vision analysis and Deep Learning.

The product is cloud-based and it also can be deployed on-premise.

Business model: SaaS (cost per claim).

In the future, as a part of our global vision, the company intends to extend the product to other types of insurance.

Dec 1, 2016

Dec 1, 2016

Is Lemonade Really the Future of Insurance?

Insurance startup Lemonade opened for business in New York in September this year to great fanfare. If you haven’t heard, Lemonade is heralded as a mobile-first, legacy-system-free, peer-to-peer insurance carrier that is poised to usher in a new era of personal insurance.

When I saw Lemonade co-founder Daniel Schreiber at InsureTech Connect 2016 I was finally able to confirm the rumors—Schreiber is a genius.

But the reason why he’s a genius is bigger than Lemonade itself. With a background rooted in tech, Schreiber has been able to establish himself on the front lines of insurance and build an audience for his innovative approach to a legacy-laden industry.

Lemonade introduces a whole new vision of selling insurance. Time will tell if it really revolutionizes the industry, but one thing is clear—there are still many questions to answer before we get ahead of ourselves.

Lemonade Distribution—Is It Really Peer-to-Peer?

When you look at Lemonade on the surface, it’s clear that the user experience is amazing. Having a mobile-first approach to selling insurance will help the industry align itself with the broader scope of digital transformation that is sweeping businesses in all sectors.

It’s not that Lemonade is the only insurtech application out there—it’s just that Lemonade simply has the best user interface.

Once you look deeper than the user experience, the peer-to-peer model becomes interesting. Lemonade’s peer-to-peer insurance model is based on the insurance carrier model (Lemonade is a licensed carrier in New York) where policy holders form small groups online and part of their insurance premiums flow into a group fund for paying claims.

Essentially, Lemonade’s business model calls for users to divide risk amongst themselves. However, if you look a little closer, it seems unclear whether Lemonade is actually offering a peer-to-peer approach to insurance or if it’s a virtual/mobile-first version of a regular insurance company.

Lemonade has dramatically cut the typical insurance industry debt ratio by eliminating offices and agents. But Lemonade’s reinsurance through Lloyd’s of London makes it tough to really understand this peer-to-peer model.

The distribution model will become clearer over time, but the bigger question is profitability in this new vision of insurance sales.

Fraud and Insurance Profitability—What’s the Lemonade Approach?

At the end of the day, it doesn’t matter how much an insurance company collects in premiums—it only matters how much of that money is staying in your pocket.

Traditional insurance companies consistently post combined loss ratios above 100%, so there is an obvious concern for increasing profitability. Lemonade has said this led incumbent insurers to put $0.40 on the dollar of their premiums toward expense ratios. As Dan Ariely, Lemonade’s Chief Behavioral Officer, puts it:

In the very structure of the old insurance industry, every dollar your insurer pays you is a dollar less for their profits. So when something bad happens to you, their interests are directly conflicted with yours. You’re fighting over the same coin. Basically if you tried to create a system to bring out the worst in people, you would end up with one that looks a lot like the current insurance industry.

This contention between insurers and their customers has led to 25% of Americans believing that it’s okay to embellish claims, according to Lemonade. Fraud is a real problem that new insurtech players must contend with, and Lemonade is no exception.

Lemonade has worked to restructure the insurance model in a way that aligns with behavioral economics and game theory. According to the company, the current insurance model breeds fraudulent activity because consumers feel slighted by insurers and their distrust leads to fraud. In response, Lemonade looks to signal to consumers that they can be trusted by being transparent about the 20% management fee and giving all unclaimed money to charity.

Lemonade believes that if consumers see that fraud is slighting charity rather than slighting an insurer, they won’t be pushed to commit fraud. It’s a little troubling that Lemonade’s Giveback program is an expression of intent, not a contractual obligation to policyholders nor their selected charities. But aside from this point, there are still inconsistencies in the overarching Giveback theory.

The problem with this signaling theory is rooted in Schreiber’s explanation of the Prisoner’s Dilemma. He says that when playing the Prisoner’s Dilemma, neither party trusts the other which leads to bad results for both. However, when you look at real-world results of the Repeated Prisoner’s Dilemma, an initial defect response will force punishment that inevitably leads to a cooperate response later. A defect/defect response is a Nash Equilibrium, but in the long run the optimal solution and best strategy is cooperate/cooperate. This isn’t necessarily consistent with Lemonade’s explanation of consumer/insurer distrust.

This inconsistency complicates the signaling behavior that Lemonade’s model aims for. The 20% management fee and charity policy are Lemonade’s signals to the other party that the insurer won’t change its strategy no matter what happens. If we employ Lemonade’s logic, the other party has no choice but to defect—but we expect the exact opposite. If a policyholder signals to an insurance company that he/she won’t commit fraud (per behavior data and shared privacy), the insurance company has no choice but to pay claims. This isn’t consistent with the current state of insurance as companies lose money and consumers don’t trust the industry.

As Lemonade matures, we’ll see if this plan works out. It’s just hard to imagine that Lemonade doesn’t have a backup plan for insurance fraud (or, maybe we just aren’t getting a complete picture of the business model just yet).

Lemonade Success Spells Success for all Insurtech Entrpreneurs

The growth of Lemonade and the insurtech space seems poised to put an end to the idea that insurance companies can only make money by not paying claims. Insurtech entrepreneurs are rooting for Lemonade’s success. But keep in mind that insurance innovation will only take us so far—we have to address fraud to ensure we’re profitable.

Despite the rise of these “disruptors,” we can be sure that insurance companies aren’t going anywhere. As Chairman of InsureTech Connect Caribou Honig says, “Many entrepreneurs overestimate changes that will be in 2 years and underestimate changes that will be in 10 years.”

Insurtech is on the rise and Lemonade is certainly poised for success, but the insurance industry as a whole must buckle down and solve the problem of fraudulent claims before we can succeed in the digital future.

Oct 13, 2016

Oct 13, 2016

What Intelligence Is Not

Photo Credit:
Images related to investigations seem to catch our eyes more than ever now— on our social media timelines and feeds (“Proof of ‘Real Housewives’ star’s fiancé cheating!”), in our guilty-pleasure tv binges (almost every other shot in “Mob Wives” or in case files on “Law & Order”), and in the news (convenience store footage of robberies). From a gumshoe’s grainy black and white image taken from a cafe or hotel balcony, to sophisticated satellite images with timestamps and coordinates, these images evoke a sense of spying, while fueling our fears that every camera lens (public and obscured) is recording our every move… and that the pictures can and will be used against us.

There is a continuing great and valid debate about citizens’ rights to privacy regarding cameras in public, their usefulness, and what is done with the hours of footage and millions of pixels from images of everyday people going about their daily lives. We hold varying levels of trust (or mistrust, as the case may be) in whose eyes are behind the lenses, where the images are stored and secured, and “how it looks” to someone else when they see us on film.

While concerns may rise about Big Brother watching our every move, we have also become a bit numb in certain societies to ever-watchful eyes. Those of us who live in big cities around the world are especially desensitized to cameras all around, but ask any man on the street, and he will most likely tell you that he believes data is being collected about all of us, all of the time. People believe it’s the way of the world we live in, so we should just be ready for our close-ups.

The images on our computer, television, and movie theater screens reinforce the belief that nefarious people, whether they claim to be on our side or not, are sitting in dank rooms, pouring over footage and phone records of any and every body. Some people actually believe that the National Security Agency is “just getting intel on all of us,” making intel a buzzword and intelligence a part of our vernacular.

Without delving into the debate about right to privacy, we can say definitively that this view is all wrong.

It’s Not All About You (Specifically)

Persistent Surveillance Systems, a private technology company, has been in the news[1] because it came to light that their plane-mounted cameras were employed by the city of Baltimore in early 2016 to record images spanning over 25 square miles for up to 10 hours a day… without the taxpaying citizens being aware of it.[2] As Compton (California) Mayor Aja Brown has stated, “There is nothing worse than believing you are being observed by a third party unnecessarily.” The outcry of Baltimoreans was that their own government was spying and collecting intelligence on its residents and visitors.

But it was not.
Persistent Surveillance Systems’ images have been used in cities to solve crimes for several years
Photo Credit: Persistent Surveillance Systems)

It is important that we have a clear understanding of a few important points: First, images from the planes’ altitude reduce people on the street to mere pixels, rendering faces indistinguishable. And the cameras also do not operate 24 hours a day. Furthermore, as we discussed in a previous blog post on intelligence methodology, the cameras themselves provide only the optics— intelligence has to have a goal; the data cannot exist solely for its own sake (or the machinations of others), and the methodologies of science and law are checks and balances that protect us from who collects the data and how that data is used.

But the main thing we need to have a clear understanding of is the fact that this is not intelligence.

Intelligence Is A Step Further

What laymen often refer to as “intel” is actually surveillance.
“Surveillance is used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or for the investigation of crime.”[3] The differentiator is that surveillance - the camera images from above, from CCTV, and even from hidden agents’ pen cameras - is an active part of data collection for intelligence, but it is not intelligence itself.

Surveillance and its legality (in whole or in part) is the primary issue with which people take umbrage in regard to the NSA, FBI, and The Patriot Act in the United States. People simply and justifiably do not want to have their internet search histories, phone calls, and whereabouts tracked and recorded without clear cause and notification. We fear that all of this data is used to compile some type of intelligence file that could be used against us, all without our knowledge or consent.

“Intelligence differs from surveillance in that it constitutes a further step in the process of managing the information obtained: monitoring aims to search for and obtain the most relevant information for our environment interests, while Intelligence emphasizes the analysis and evaluation of the results obtained from the monitoring based on different "indicators" or analysis types. This is presented in the form of reports aimed at facilitating decision-making.”

Surveillance alone does not stop criminal activity (although the presence of visible cameras may thwart it), nor does it bring the bad guys to justice. That’s intelligence. The data from surveillance, combined with intelligence methodology, are what aid investigators and agents to get the complete picture, so to speak, and figure out the details and truths to keep us safe. To break it down further, consider surveillance data versus information— you can collect data, but you can not glean any valuable information from it. Intelligence is actually getting information out of data.

In the famous case of the Boston Marathon Bombing of 2013, scores of cameras from the city, as well as pictures and video clips from attendees’ smartphones and digital cameras, were scoured and studied to lead to the suspects of the horrific crime. The images were the surveillance, but the technology used to identify faces, the questions the agents asked, and the information checks— these aspects were all a part of intelligence. Surveillance is not a collection discipline; it is but a part of the methodology.

Shift Your Thinking About Intelligence

Whether it is a government entity using cameras to get images within its borders, a telecomm company keeping a list of all phone calls and text messages, an ISP keeping details on computers’ ISP addresses and internet usage, or the monitoring of phone calls by the NSA, remember that this is surveillance, which is to serve a greater purpose in intelligence, which is to maintain safety and to catch the true bad guys. It’s how the information gathered from surveillance is used that truly matters, and despite what the headlines tell you, it is mostly for good over bad.

The growth and popularity of Internet of Things and Machine Learning have us encounter uses and processes of the surveillance and intelligence world in our everyday lives in much smaller ways to enhance and to protect our persons and possessions— a smart watch can monitor stats that can be studied and interpreted to help you stave off an impending health issue; cookies and tracking mechanisms on our computers and digital devices can help us use an app to locate them if they are lost or stolen; satellites, apps, and algorithms can detect traffic patterns and prevent accidents or congestion on the roadways. The science of surveillance can be used in ways great and small for our benefit.

Surveillance is nothing without intelligence: Agents analyze audio data on “The Wire”

Regarding the proverbial Big Brother who is watching us from the skies and is tapped into our communications lines, remember this important point from the hit show, “The Wire” (whose very name is about wiretap surveillance): “All the pieces matter.” Intelligence isn’t simply one step in the process, it should not be confused with the step of surveillance, and all of the pieces in the methodology and all of the players are tantamount.

Ready for more? Be sure to bookmark and follow us for our next blog post in this series to learn more about intelligence.

Aug 30, 2016

Aug 30, 2016

Intelligence Methodology: The Way Big Brother Is Actually Looking Out For You

Having to give your Social Security or National ID number. Typing your PIN in public at the ATM. Posting your personal information on social media sites. Submitting your email address to register for a website. Entering your credit card information to buy a book from Amazon. Seeing your house on Google Maps Street View.

All of these actions have made our hearts pound a bit harder and faster at one time or another, as we hold the thought in the backs of our minds: “Who gets this information and what are they really doing with it?”

The public consensus is that we just have to trust the sales rep on the other end of the telephone who now has our address, credit card CVV number, and our mother’s maiden name (for identification purposes, of course), but as an episode of “Law & Order” or “Catfish” will remind us, that trust is easily, and often broken.

Now that hard drives hold more data, cookies track our every online move, computers in cars record not only when to deploy an airbag but also where we went and how fast we drove to get there, it’s hard not to hold tight to the fear that Big Brother is not only watching, but is saving, downloading, and backing up every aspect of our lives.

But in the midst of googols of Googles (more data than we can count, in layman’s terms), there is a method to the (perceived) madness. There is a system of principles and rules to regulate intelligence, and it ensures that intelligence works for us instead of against us.

Intelligence And Our Greatest Fears

A survey was conducted in 2015 of the Top 10 Fears of Americans. Did snakes make the list? No. How about wrongful incarceration? No, again. Illness and death didn’t even crack the top ten. What Americans seem to be most afraid of, of all of the bad things in the world— five of the ten relate to ways their lives can be turned upside-down by someone having the right (or wrong) intelligence in their hands:

      Corporate tracking of personal information
      Government tracking of personal information
      Identity theft
      Credit card fraud

Top 10 Fears of 2015
Photo Credit: Chapman University
We are so fearful of losing our autonomy, of having our right to privacy trampled upon, of the disruption to our lives if someone pretends to be us or wants to destroy us, and yet, we so easily to write down passwords where they can be found, save our documents to a cloud we can’t define or explain, share photos of our children on the internet, carry RFID cards in our wallets, tag our locations in real time on social media, and rely on our smartphones to organize and keep “our whole lives” in the palms of our hands.

When was the last time you updated to secure passwords for all of the websites and apps you use? Have you committed to memory a difficult to decipher alarm code, or have you stuck with 1-2-3-4 or the last 4 digits of your birth year? Chances are, you haven’t made these security changes, or you may have invested in an application or program that securely stores your passwords for you. No matter your method, it’s worth nothing that we live in contradictions— we worry about intelligence gathering methods and what will be done with the information gathered about us, but we depend on technologies and methodologies that use machine intelligence (deep learning, augmented reality, artificial intelligence, security codes and patches) to live our lives without the fears stopping us.

Intelligence Gets A Bad Rap

Almost weekly, there are headlines about privacy breeches that send Citizen Average Joe into a frantic frenzy. Take for example this summer’s hottest social digital game, Pokémon GO. Within days of its release, online media flooded our timelines and inboxes with stories not for the faint of heart about coordinated muggings, break-ins, and even discoveries of dead bodies[1], instead of focusing more on tales of friendships forged in parks or how use of the app helped people explore cities and towns in a new, vibrant way.

Or turn on your television and watch the white-knuckling series, “Mr. Robot,” which depicts hactivists for fsociety who use cyber intelligence to try to cancel the world’s consumer debt by bringing down the largest corporation on the planet. (While most of us wouldn’t mind having our credit card debts erased, the implications of this story are incredibly scary, nonetheless).

Photo credit:

The fields of intelligence get a bad rap— cyber intelligence is depicted as hacking by terrorists who will shut down the airlines and power grids. Forensic intelligence is usually tied into criminal intelligence, and shoddy work at crime scenes or with DNA analysis harkening mention of either the O.J. Simpson or the Steven Avery (“Making A Murderer”) cases. The words “signals intelligence” conjure images of RADAR and SONAR involving either a traffic ticket someone feels they were targeted for or profiled to receive, or of finding submarines and espionage like in a Hollywood blockbuster. And of course, human intelligence evokes images of a spy in a trench coat, sharing International secrets in whispers while sitting on a park bench, just before someone’s car blows ups.

The movie, television, and book publishing industries fuel our fears surrounding intelligence, and it’s mainly because they go for the entertainment value by hyping fantasy and imagination with few truths (or by exaggerating really true stories). Not to mention the media with their 24-hour news cycles and online publications giving you stories at your fingertips which sensationalize factual incidents in the intelligence world simply by nature of their repeated cycles and easy access.

As any psychologist or therapist can tell you, it’s not only important to examine what you fear, but what planted the seed of fear in you to begin with.

Protection All Around You

So, do we really have just cause to be so mystified by who we think is watching and tracking us?
As it turns out, intelligence methodology actually provides protection all around you, often in ways that you take for granted.

Let’s look at these examples:

Gmail activity report


When you check your email, your IP address and location are being tracked. This isn’t to make it easy for someone working in a plush Google office to be able to track your whereabouts, but to give you, the user, more power in maintaining the security of your account. View your last account activity details to verify that no one else is poking around there. Google, as well as other applications, services, and websites, uses 2-step verification, whereby the user registers with a phone number connected to the account and will receive a message in the event of suspicious activity (like a log in from another device).


For every channel airing niche programming on our televisions, satellites also beam unfathomable types and amounts of data back to Earth, and it’s all so mysterious because we don’t much know about any of it. We can imagine how the use of such data is useful to nations and their militaries, but consider this: images from satellites can help predict poverty by viewing areas up close.[2]  Such intelligence will not only help aid workers, but will save money and other resources which can be redirected to helping people who need them the most.

-Closed Circuit Television (CCTV):

Quite popular (plentiful) in the United Kingdom, CCTVs are the epitome of the negative image of Big Brother spying on you. However, a 2009 analysis titled "Public Area CCTV and Crime Prevention: An Updated Systematic Review and Meta-Analysis[3]," examined 44 studies that surveyed areas from the United Kingdom to large U.S. cities, and reported significant decreases in different crimes. CCTVs gather intelligence and “are effective at deterring and solving crime, and that appropriate regulation and legal restrictions on surveillance of public spaces can provide sufficient protections”[4]

And while already developed, the future of identification lies in technological advancements paired with intelligence: retinal scans to gain access to your safe deposit box, fingerprint pads to unlock doors and even firearms for safety.

However, these ways of protecting people and property were not developed solely as technological advancements; again, they were conceived, developed, implemented, and tested through the employ of intelligence methods; more specifically, scientific ones.

“We must revisit the idea that science is a methodology and not an ontology.”
Intelligence is a science[5], and the Scientific Methods helps intelligence analysts arrive at better conclusions in terms of using that intelligence to keep people safe.

As we may remember from school, the Scientific Method is an ongoing process with these steps:

   Make observations
   Think of interesting questions
   Formulate hypothesis
   Develop testable predictions
   Gather data to test predictions
   Refine, alter, expand or reject hypothesis
   Develop general theories

“Intelligence analysts need to make sense of seemingly chaotic data, to see patterns in behavior and events, and to ascertain possible relationships by observing connections among things that might otherwise seem disconnected.”[6]The Scientific Method is the gold standard regarding intelligence methodology.

To Serve And Protect: The Law As A Methodology

In our blog post, “What Is Intelligence?” we pointed out that “Information obtained from intelligence should not exist just for data’s sake; it needs to meet a goal.”

In addition to all of the technological advances in place and on the horizon to protect us from our fears of identity theft and cyber terrorism, we have another, more familiar intelligence methodology— the “old school” regulatory system of the law. After the science comes regulation and compliance for meeting the goal of intelligence. A legal basis for the intelligence work must be present from the onset.

In the United States, there are roughly 20 national privacy and data security laws, with hundreds more in individual states to assuage those top fears of Americans. Analysts must comply by rules, seek warrants when needed for access to private information, and safeguards must be in place and utilized to secure data.

A snapshot of privacy laws in the USA relating to intelligence gathering of private information:

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The large range of companies regulated by the Federal Trade Commission (‘FTC’) are subject to enforcement if they engage in materially unfair or deceptive trade practices. The FTC has used this authority to pursue companies that fail to implement reasonable minimal data security measures, fail to live up to promises in privacy policies, or frustrate consumer choices about processing or disclosure of personal data.
US privacy laws and self regulatory principles vary widely, but generally require pre collection notice and an opt out for use and disclosure of regulated personal information.
Opt‑in rules apply in special cases involving information that is considered sensitive under US law, such as for health information, use of credit reports, student data, personal information collected online from children under 13 (see below for the scope of this requirement), video viewing choices, precise geolocation data, and telecommunication usage information. The FTC interprets as a "deceptive trade practice" failing to obtain opt in consent if a company engages in materially different uses or discloses personal information not disclosed in the privacy policy under which personal information was collected. It has, for example, sued to prevent disclosure of personal data as apart of several bankruptcy proceedings.

States impose a wide range of specific requirements, particularly in the employee privacy area. For example, a significant number of states have enacted employee social media privacy laws, and, in 2014 and 2015, a disparate array of education privacy laws.
The US also regulates marketing communications extensively, including telemarketing, text message marketing, fax marketing and email marketing (which is discussed below). The first three types of marketing are frequent targets of class action lawsuits for significant statutory damages.
Violations are generally enforced by the FTC, State Attorneys General, or the regulator for the industry sector in question. Civil penalties are generally significant. In addition, some privacy laws (for example, credit reporting privacy laws, electronic communications privacy laws, video privacy laws, call recording laws, cable communications privacy laws) are enforced through class action lawsuits for significant statutory damages and attorney’s fees.  Defendants can also be sued for actual damages for negligence in securing personal information such as payment card data, and for surprising and inadequately disclosed tracking of consumers.
-Data Protection Laws Around The World

While what we see and hear about cyber, human, criminal, and visual intelligence (to name a few) may frighten us, it’s important to lift the veil and see that it’s not magical, it’s methodological. Take stock of all of the safety and security mechanisms in place in your life and remember how they came to be— via intelligence methodology— and rest easier and assured that Big Brother isn’t looking at you; he’s looking out for you.

Intrigued? Be sure to follow us to learn more in our series on Intelligence.
You can also learn more about the data protection laws of the world at

[2] Using the methodology of inductive reasoning, in this case, involves synthesizing a sufficient number of intelligence indicators to arrive at a reasonable conclusion or hypothesis that the enemy unit will attack.


[6] James Bruce, Analyzing Intelligence: Origins, Obstacles, and Innovations.