The Global Pandemic due to Covid-19 around the world has set up a new level of e-commerce world for us and everything has shifted to “Digital” now. The transactions are digital to the maximum extent. Watching this dependence of the whole community over internet has also led to an extreme spike in internet frauds. One such type of fraud is called Synthetic Identity Fraud which we are going to discuss about in this topic today. For getting their hands over Synthetic Identity frauds, the fraudsters use a fusion of made up and real information of people which may include email addresses, social security numbers, their physical addresses and so on. They use this information with their made-up data for applying to loans, credit cards or to buy goods from any e-commerce website. What is a Synthetic Fraud? Unlike the bank frauds where a fraudster theft your real information so as to get financial benefits with fraudulent means, the Synthetic fraudsters not only steals your information, but also make up some fake or imaginary customer identities of people by merging their made-up data and the real data together. And, they do this for deceiving financial institutions and businesses. How does Synthetic Fraud work? As we know now, such type of frauds is performed by combining a number of fictional elements or by merging multiple identity elements of real people. For example, a combination of Social Security Number (stolen) with some real address that is generally a P.O. Box. Fraudsters steal the Social Security Number of either a child or of an elderly individual because these numbers are not taken in use as actively as other details. After this, that scammer will make their credit profile better by making small purchases over months or years. This improved credit score will now help them to make large purchases at a time. And then, they stop applying for credit or loans using this identity. Impact on the Merchants With the increasing number of such Synthetic Identity frauds, merchants get affected of course. And, all this can impact them in the following three ways: First of all, the merchants who offer credit accounts can get under a huge loss directly. Secondly, the sellers who sell high ticket products by working with third party can be obligated for such frauds depending on their agreement. Thirdly, such frauds increase the overall costing of business for anyone. And lastly, as such fraudsters steal some extent of the data for real information of individuals, so merchants or retailers should always ensure that the data of their system does not get breached. Thus, no one should disclose any kind of information about their customer to anyone asking for it or they should not let anyone sneak into their system anyhow. Combating the risk of Synthetic Identity Frauds With the continuously enhancing numbers of synthetic frauds in every type of e-commerce industry, businesses should always know that if the customers of their e-commerce business are exactly the person who they claim to be online. This becomes more important when someone is purchasing a quite large good from an e-commerce website. Howsoever, identity verification of anyone making a purchase is extremely crucial to know whether they are real person or are just claiming to be a real person. E-commerce sector should also go for Digital Verification Technology so as to know one’s authenticity as it can significantly help a business in identifying synthetic frauds. Locations, devices or individual behavioural patterns are very difficult to imitate. Hence, the key of interpreting such synthetic frauds lies in the ability to detect the digital footprints of a user and comparing these to known individuals with normal behaviours. Another protective layer for protecting the companies from frauds should include the process of sending a temporary password only on their verified mobile numbers which should be confirmed prior making a purchase. If not for every purchase, such processes should be included for risky or huge purchases or transactions. Effective models for detection of synthetic frauds include the specific analyzation of customer behaviours which can be done by uncovering the peculiarities and the questionable motif while opening accounts, or trading in all the e-commerce industries. Such suave and advanced technology is able to do the following: Detection of synthetic identities just while their origination, that is, before any lending decision. Removal of such synthetic identities from pre-qualification or prescreen programs. To decreases the amount of waste efforts regarding back-office collections, such technology can monitor the already registered accounts to disassociate the synthetic identities which already exist in your portfolio. Mollifying the effects of Synthetic identity frauds over populations which may include recent immigrants, new to credit customers or the people who have damaged credit. Tips and Learnings E-commerce frauds puts any online business into high risks which should be mollified by using and implementing an advanced system for identifying such identity frauds. Every business should find time and analyse the areas in which such identity frauds most likely occur and how they occur. Retailers should go through a detailed analyzation and testing of all the relevant transactions and also, they should monitor the controls well. A constant and timely monitoring schedule can improve a company’s hold on their customer’s authenticity and thus will decrease the frauds. This way they can immediately notice as well as fix the rules which are broken. Therefore, it is recommended that all the employees of a company should “dog-food” the system which will ultimately facilitate a better customer experience. As we already know how Covid-19 made such frauds relentless. However, the alternative approaches and changing schemes has complicated the detection of fraud even more. Considering any of the factor of this worldwide pandemic, which may include regulatory requirements, economic conditions, and IT source constraints; it becomes difficult to keep up. So, understanding all about the Synthetic Identity Fraud, you can reduce the risk by implying some prominent tactics discussed.

I had a few notions about Com Olho when I joined the startup understanding that it is a new enterprise with a small team but ever since I joined, I have no regrets. It has been a steep learning curve. Working here has been a voyage of self-discovery – a unique experience. A small team, extremely hard working people, flexible timings, multi-tasking and a vibrant work culture are some of the things that define this place. The best part here is they have a flatter, more open organisational structure, where every person is at the forefront of the business with every act of his/her making a difference to the company’s fortunes. I work as a Marketing Associate here. Before joining Com Olho, I hadn’t had any experience in marketing. I used to work as an Accounts Manager. The amount of faith put on me is unmatched. I have a large creative space – with no restrictions. I can literally come up with anything that makes sense and aligns with the business ideas. They offer an environment where every employee’s voice is heard and matters. I feel a sense of freedom and ownership working here. As if I don’t belong to Com Olho but Com Olho belongs to me. It’s something deeply personal and I will feel a special connection. And that’s what being in a start-up boils down to — more opportunity for ownership, for responsibility, and for growth. I believe there is a lot of scope within Com Olho to experiment. I am happy to be a part of a team that has a new product and the experience is teaching me to be independent, flexible, resilient and make the most out of the available resources. It is a new entity and the self-learning skills I have developed will always be valuable over the course of my career. Also the team has been really considerate in tough times like this. Ensuring colleagues' well-being and safety are their priorities. Our founder, Abhinav Bangia always says – ‘Stop watching too much Digital’ and this is something which brings a bit of sanity and comfort. A determined creator and marketer, I have a passion for crafting meaningful content. I’m always on the lookout for the next good story, idea or digital trend – meanwhile my very own story remains a perpetual work in progress. Connect with me on LinkedIn : Link

Advertising Fraud is a growing menace among advertisers globally. HP Enterprise in its Business of Hacking highlighted ad fraud as the most easiest and lucrative cybercrime. In a 2017 report Juniper Research estimates ad fraud to be worth US$19billion equivalent to $51 million per day. This figure, representing advertising on online and mobile devices, will continue to rise, reaching $44 billion by 2022. Fraud is generally defined in the law as intentional misrepresentation of information or material’s existing fact made by one or multiple people to another person with knowledge of its falsity and for inducing the other person to act, and upon which the other person can take on severe damages in terms of performance, reputation and finances. Goals for Assessment 1. Highlight the fraud focus points (High) where the performance of an audit may need to be adjusted. 2. Provide assurance that the risk of ad fraud is being effectively incorporated within the risk assessment. 3. Minimise the risk of overlooking fraud during assessment stages. 4. Build Reports for clients admissible in court for fraudulent traffic supply. Com Olho’s Risk Model A risk model maps and assess the advertiser’s vulnerability to identify ad fraud scenarios, with a scale defined as below : Fig 1.1 : Com Olho's Risk Model Tests 1. Deterministic Deep Tech based single test to find presence of fraudulent advertising traffic. 2. Non Traditional Deterministic Test for Organic Hijacking. 3. Non Traditional Deterministic Test for Bot Mixing. Results Upon investigation, depending on scale of campaigns, KPI of campaigns, advertiser awareness etc. Fraud impacts all forms of advertising budgets, even with the most strongest KPI's. Follow the table below to understand vulnerabilities percentages. Fig 1.1 : Vulnerabilities Percentages v/s KPI Want to learn more about the tests? Drop an email to abhinav@comolho.com

Digital twins are in reality the virtual repetition of physical tools that the data scientists and the IT devices make use of for running the simulations prior to the actual tools being built and deployed. Today, these digital twins are becoming more and more advanced and changing the way technologies like IoT, AI can be optimised. How will you describe digital twin technology? The Digital twin technology is moving higher from the manufacturing viewpoint and moving towards the merging of the Internet of Things (IoT), artificial intelligence, and data analytics. As more and more complex things start to become associated with the adaptability of producing information, having a digital friend raises the ability of the IT professionals and data scientists in optimising the deployments for better efficiency and creating imaginary scenarios. Describe the working of a digital twin technology A digital twin commences its life when it is built by specialists, more often by the experts in data science or in applied mathematics. These developers do proper research in the physics that define any physical thing or system being imitated and use the same for developing a mathematical model that boosts the real-world origin in the digital space life being built by specialists, often experts in data science or applied mathematics. The twin-magic: The twin is built so that it is able to receive the inputs from the sensors that collect the data from the real-world counterparts. This will empower the twin to boost the physical material in the real sense and time, in the procedure providing the insights of functionality and the potential difficulties. The twin can also be designed on the basis of the prototype of its physical aspects in this situation the twin is able to provide feedback as the product is refined. The twin can also serve like a prototype itself prior to any physical object or version being built. Some uses of Digital twin technology. There are two examples that state the use of digital twins: the car and a cargo vessel. Materials like an aircraft engine, train, offshore platform, and turbine can be easily designed and also tested digitally prior to being produced physically. These twins can also be used for maintenance work. For instance, technicians may use a digital twin for testing about a proposed affix to the physical twin. Digital-twin business operation can be found in numerous sectors:- Manufacturing is one of those sectors where advancements of digital twins are possibly the farthest ones, along with factories that are already making use of digital twins for boosting their performances, as per several types of research from many industries and companies. Automotive digital twins are built more likely because of the fact that many cars are already fitted with mensuration sensors, but the refining of the technology is becoming more vital because of the increasing number of autonomous vehicles hitting the roads. Healthcare is that sector that will produce the digital twins of the people we've been talking about. Band-aid sized sensors will send the health data back to the digital twin which will further be used to monitor and in examining the patient's well-being and conditions. Understanding the relation between Digital twins and the Internet of Things Clearly, we can say the IoT sensors today are a big part of what makes the digital twins more likely. And as IoT devices are refined, the digital twin cases will comprise smaller and lower difficult materials, which will give extra advantages to the industries. Digital twins are more generally used for predicting many outcomes that are based on variable information. This is the same as running the stimulation case which is often seen in science fiction and films, where any digital scene is proven with the help of the digital environment. Along with the extra software and data analytics, digital twins are able to optimise an IoT disposal for maximum productivity, as well as will help the designers in figuring out where things must be going or the way they should operate prior to being physically disposed. In A Nutshell The more that a digital twin can imitate the physical material, the more possible chances are there that the efficiencies and other advantages can be seen. For example, in the manufacturing sector, where there are more instrumental tools, the more precise digital twins might be boosted to see how the devices are performing over time, which will help in making estimates of future functionality and chances of failure.

It’s 2021 and who doesn’t know about the existence of kickbacks in our advertising industry. A practice that is prevalent for ages in the marketing industry and still the agencies are happily performing it to earn more money. Advertisers are not very open to talking about the practices of kickbacks in the advertising industry, but still do perform it. It's kind of a legal form of bribe but it's still very controversial. What are kickbacks and what are their forms? Well, a kickback seems more of an illicit payment made in exchange for special benefits or some other form of shady service rendered. Cash, a reward, payment, or something of value may be used as a kickback. Kickbacks are a bribery activity that disrupts an employee's or public official's ability to make objective decisions. It's usually considered as a form of an illegitimate bribe. Why do kickbacks even exist? The answer lies in the highly ‘money-making’ intention of the industry where everyone wants to get filthy rich, by hook or crook. The issue of kickbacks is more of cultural practice in the industry where trust, ethics, and transparency are murdered. It’s all about hiding things better, the better you hide the better you can extract the money. Although there are several different types of kickbacks, they all involve collaboration between two parties. Example: For instance, a private or government company's business manager can accept a product invoice despite the fact that the bill is inaccurate. And the product seller may then pay the business manager a portion of the profit (or some other kind of reward). The detection and investigation of kickback schemes are one of the most complex forms of fraud. Let's look at among the most popular red flags of kickback. These might not always indicate that if something sinister is happening, but the more of these are present, the more likely a kickback scheme is taking on. Clients are overly pleased with vendors. Organisation compels workers to use a single vendor. There will be no open tender procedure (or lower bids are ignored) The seller has usually a history of legal or regulatory issues Organisations tend to use suppliers who deliver substandard goods or services. There's always a delay in delivery dates Mostly during the buying process, there is a lack of sufficient monitoring. Rates for products or services are higher than usual rates So, Do clients also take profit from kickbacks? To say, YES, to some extent, they can. There really is no doubt that a publisher would be willing to offer a rebate to high-spending customers. Rebates are provided by advertisers to guarantee that a larger portion of the inventory is purchased at a better price rather than being marketed at different prices through an ad exchange. However, a kickback can also help a client get a better inventory rate if it's in the company's or publisher's best interests to provide a lower value at the time to assure that the media purchase happens. This may be affected by how close an organisation is to achieve a kickback agreement and also how important the kickback is towards the business overall. How can the clients be more cautious dealing with kickbacks? To deal with kickbacks and lack of transparency, the client must ask certain questions to self and based on those should take further actions. Some of the basic and necessary questions that he or she should take into considerations are:- Is it possible to meet my target audience via other digital platforms? If that's the case, which platform is the most cost-effective? Can I recognise the difference between the expected and real rate that the publisher and my agency are supplying? Why aren't my inventory rates or estimates changing from reporting period to reporting period or campaign to campaign? (a clear sign that the department is accepting bribes) Are commercial marketplace agreements helping me achieve my promotional objectives? Who is creating the investment decisions, and why are they being made? Are there any extra data or custom innovations included in the package? If so, how can these contribute to my campaign's goals? Why is there so much delay in the supply? Should I do some more research about the agency? Why is there a shortage of communication? Conclusion Kickbacks in the media industry may come in the form of rebates or false charging for products that do not exist. Clients spend a value in the form of higher prices or a poorer quality of service than they would usually expect for their money. Agency fees are shrinking, and a difficult-to-understand digital marketplace is delivering the encouragement and shield for such behaviour. And as already said, it’s still one of the most complex forms of white-collar crimes that can be detected. Author : Auhsini Das About Her : With a Data Science degree from IIT Madras, Aushini enrich audience with her high quality tech articles. Having +5 years of experience in content writing, She work passionately to create copy that converts, with a focus on maintaining your authentic brand voice.

After our first year as Com Olho, we reflect on where we came from and where we're headed! The last 365 days have been filled with passion, excitement, hard work and a lot of fun. As we turn 1, we are looking back and celebrating our milestones and memories that happened along the way. On our very first day of the company, our first task was to just setup the chair and table. We din't have a website, a product or any kind of sales collateral. But we managed it all. "Com Olho" is a Portuguese word meaning "With Eyes". We found the name unique, high on brand-ability and most importantly it wasn't taken. We started up with a very simple vision, take a problem statement and solve it using advance technology, and today we have 3000 lines of committed code, 6 product update version releases and double digit sales collaterals. Hopefully thats enough reasons to take advantage of our birthday promotion.

As an aerospace engineer, I'd like to draw an analogy from airplane takeoff for digital transformation. In case of airplanes taxiing for takeoff, acceleration, which is the rate of change of speed, is directly related to the distance rolled on the runway. The slower the acceleration, the longer the distance needed before the aircraft achieves takeoff speed. If the aircraft never achieves the required acceleration, it cannot take off on the given runway. That's not too dissimilar to digital transformations. Acceleration, or rather the lack of it, can become a challenge. The initial experiments take so long that both stakeholders and organizations never see momentum develop. The disruption never takes off. Organizations are rapidly trying to evolve to survive the next industrial revolution. The rapid pace of change in the technology means that each digital idea has shorter-than-usual shelf life, which gives digital transformation much shorter runways to work with. Speed and iterative execution complement each other to dramatically reduce risk of failure of digital transformations. We would recommend that organizations on the path of digital transformations adopt speed (or in particular "innovation velocity") as a key metric. Speed (Innovation Velocity) as a Metric Innovation Velocity- the pace of innovation- is a key metric in many forward thinking organizations. Given the shorter runway for digital transformations, evaluating a large funnel of idea, each executed at low cost and high speed, is the best bet for hitting a few successes. This focus on speed is an even bigger challenge in larger, more stable organizations that aren't usually known for rapid or low-cost iterations. Successful tech companies like Amazon, Netflix and Alphabet have build this expectations of fast iterations into their cultures. Start-ups on the other hand, tend to work on one big idea but are excellent at low-cost and high speed iterations. The motivation system in a startup helps with agility. When money runs out, the game is over, and you need to find a new job. This obviously doesn't quite work well with larger organizations, given their cultures of job security and stability. Why More Organizations Don't Drive Speed ( and What Can be Done About it) Most leaders are already aware that speed if an important driver for success of digital transformation. We strongly believe that the reason most organizations are not able to drive transformation at speed is related to structural issues. There are 2 main reasons for this. We call the first the "clock speed" issue. A "clock speed" of operation is the normal pace at which decisions and operational change happens at the organization. Measuring each of the stages in the operational change can help you drive faster innovation. You should measure landscape assessment, design, hypothesis testing, field testing, and roll out. Each of these stages can be measured by time goal and can have maximum time allowed in each stage. This would help you fix the clock speed issues, and would act not just as measuring metric for your digital transformation ideas, but would also act as a great motivation for your team. We call the second as the "two-worlds" issue. This issue arises because the organizations have become inherently slow due to checks and balances introduced over the years to manage risks. There are legal- and procurement-related boxes to be checked, IT policy and technology standards to be met, HR policies and global work processes to be kept in mind, while executing any new thing inside the organization. This restrict new ideas to disrupt the old practices, thus leading to the two world issues. A innovation index must be set to protect transformative ideas in early stages of development, to shield the innovative work from the normal brunt of corporate processes. The specific translation of the enterprise's business goals into digital transformation strategies- both one-time and ongoing- must be led at the top (i.e CEO, business owner, leader etc). The context of this write up was inspired by work done by Mr. Tony Saldanha at P&G to help it take off the digital transformation journey. Also thanks to Mr. Salim Ismail to inspire us from his write up in exponential organizations.

People are so curious to figure out how they will look 40 years from now. That's not it, they are trying these filters to share a picture of them with friends on social media. Back in time, someone wise said, not a thing in this world is for free, if you have been offered free services, you should indeed look again and around. That's what FaceApp is, it's for free. Then how does one derive revenue out of this data collection? Advertising, Digital Advertising : There are plenty of ways by which publishers (people/companies who have lot of engaged users using their website or application) make use of consumers data to make revenue. 1. They show Ad's on their platform : One of the most easy and legit way to monetize their user base, is to show relevant ad's to the mobile app user. The app can be used to show ad's from direct advertiser(people/companies who want to acquire new users for using their services) or can be apart of various ad tech supply chain for monetization. 2. They sell GAID/IDFA/Device ID's : Other quick way to monetize on data collected, is to sell advertiser ID's across ad tech networks, this would empower the ad networks to target your device for ad placements across google display, affiliates and 3rd party apps. This can even trigger fake APK drops, malware targeting and even jeopardize your mobile phone to become a botnet for supplying fake impressions and clicks. 3. Delivering ML based face trained model to intelligence agencies, governments and other 3rd party users : While you clicked on that upload image button to have a look at what you would look like 40 years from now. You not only gave access to who you are, where you work, what do you search upon, and you got all of that tagged to an unique identifier, your face and trained for next 40 year versions of you. So next time you walk by a CCTV camera or any autonomous cameras around you, you are being judged. You are now being tagged with where you go, what you do, whom do you talk to etc etc. Remember, your privacy is your top concern. Today advertisers lose USD 100M a day to advertising fraud, financial institutions are facing a high tide of digital fraud all across the world, and intentional data thefts are benefiting only a few. With rising cyberspace, we need to constantly work towards creating safer and beneficial digital environment.

Understanding Linear Programming Linear programming (LP) is a method for engineers or data scientists to find the best outcome of a business problem i.e maximum profit, minimum cost in a linear mathematical model. Each of the LP problem consist of following components : 1. Objective Function : Purpose behind LP i.e maximize profit, minimize loss , 2. Decision Variables : These are the controllable variables that influence the objective function, 3. Constraints : These are linear restrictions on decisions variables. Case Example : XYZ Pharmaceuticals XYZ Pharmaceuticals manufacturers two types of medicine with same salt : A and B. The manufacturer wants to maximize their weekly operational profit. $1 of profit per medicine A. $1.5 of profit per medicine B. Medicine A requires 1 hour of manufacturing labor and 2 hours of packaging labor. Medicine B requires 2 hours of manufacturing labor and 1 hour of packaging labor. Each week, XYZ has only 100 hours of manufacturing labor and 100 hours of packaging labor available. Lets Build the Objective Function, Decision Variables and Constraints Let x be the of medicine A produced and y be the medicine B product in the week Objective Function : Max(z) = 1x + 1.5y Decision Variables (Subject to) 1x + 2y <= 100 (Available Manufacturing Hours) 2x + 1y <=100 ( Available Packaging Hours) Constraints : x >= 0 & y >= 0 Loading & Solving the Problem Statement in PuLP Discussing Solution We see that the optimal solution for production of Medicine A & B to return maximum profit is 33.33 units weekly for both A & B to maximize the profit up to 83.33 units. We can even plot the illustrative graph using matplotlib library in python. There are many commercial optimizer tools, but having hands-on experience with a programmatic way of doing optimization is invaluable.