Trending February 2024 # Exclusive Interview With Rohit Khetan, Head Of Marketing And Strategy At Ginesys # Suggested March 2024 # Top 9 Popular

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In addition to selling products in brick-and-mortar stores, many storefronts are now offering buy online pick up in-store (BOPIS) services, same-day delivery, and online shipping. Ginesys is a fast-growing complete retail tech company working with around 1200+ customers and 30,000+ users with a wide reach across India. Analytics Insight has engaged in an exclusive interview with Rohit Khetan, Head of Marketing and Strategy at

Kindly brief us about the company, its specialization, and the services that your company offers.

Ginesys is a fast-growing complete retail tech company working with around 1200+ customers and 30,000+ users with a wide reach across India. We are a technology solutions provider for retail businesses and have been powering retail businesses from startup to IPO for more than a decade now.  We have made our mark as a premier, ‘Made in India’ solution for ERP and POS, serving the needs of small and medium businesses, with a focus on the fashion industry. Now, we have a complete suite for omni retail from marketing to retention and from supply chain to POS and Ecommerce integrations including GST compliance.  

What is your biggest USP that differentiates the company from competitors?

Our USP is we are India’s only complete and well-integrated suite for omni (i.e. offline and online) retail. Our core is a cloud-based ERP that is retail-specific so it does not need to be customized heavily. We have integrated desktop POS, cloud POS, mobile POS software, Ecommerce Order management system, GST apps, BI, customer loyalty and lifecycle marketing to work together to cater to the new age retailer’s omnichannel demands. Additionally the solution enables you to manage your business anywhere as it is completely cloud based. Ginesys One goes beyond normal integrations to provide omni workflows like buy online and dispatch from any store or buy offline and get rewards for shopping online. The biggest pain point we found that retailers and brands have is having disparate systems means wasted time and effort in integrating and chasing down bugs and support tickets.  

What are your growth plans for the next 12 months?

We aim for 100% growth through new customer acquisition and incremental revenues from the existing base.  

What are the sources and uses of customer data in retail?

The value of data in generating sales insights and consumer intelligence has long been acknowledged by retailers. However, there is still a long way to go because most retailers just stop at post-purchase analysis and retargeting.  

How do you plan to revolutionize the Indian Retail market?

A retailer in today’s marketplace comes across many challenges, with competition being one of the biggest one. To get ahead in a competitive environment, integrations in the retail technology ecosystem are a requirement. The speed with which consumer behaviour is changing has made it more crucial than ever to ensure omnichannel experiences. Single-channel and multi-channel retail are slowly fading away. Moreover, many retailers stated they planned to boost their investment in omnichannel commerce in the future. Ginesys retail POS and OMS software aid to get the processes in place promptly and helps brands focus on one’s own business. Ginesys simplifies aspects by curtailing the ambit of customizations with standard APIs for POS and OMS. Our new end-to-end omni retailing suite -Ginesys One suite aims to future proof a retailer’s business and helps them navigate the ever-changing world of retail. Right from the get-go, Ginesys One is expected to save integration time, effort, and cost while achieving various omni use cases in a seamless manner. This covers inventory management, billing software, b2b order to cash, customer loyalty, BI, omnichannel, and GST.  

How is AI evolving today in the retail industry as a whole?

AI in retail has entrusted businesses with high-level data and information that is leveraged into preferable retail operations and new business opportunities. Customers are attuned to innovations and their expectations are evolving swiftly, prompting retailers and technology providers to remain on their toes at all times. Currently, the major demand trends include cloud, AI, machine learning, improved speed and efficiency, and data/analytics. Artificial intelligence has become one of the biggest technological developments in business in recent years, with its ability to help turn large volumes of data sets into enriched information centers to help improve speed, cost, and flexibility across the value chain. We at Ginesys have recently invested in Casa CRM and marketing platform, to strengthen customer data management and rewards capability based on AI. We believe we have just started as an industry to look at this and there is tremendous scope for more development on this topic.  

How is your company helping customers deliver relevant business outcomes through the adoption of the company’s technology innovations?

Technology is changing the nature of sales and shopping throughout the market. At a time when consumers are empowered with choice, and market conditions are increasingly volatile, new technologies like cloud retail software and POS software for retail, AI-based marketing automation and ecommerce and GST integrations, can help brands and retailers drive valuable business efficiencies and customer experience. Retailers can go live on the system 50% faster than other custom integrated products as the system is retail-ready. The commercials for the suite are on an affordable subscription basis and thus the entire suite has a 70% faster time to return on investment compared to global peers.  

How have you been powering the retail business from a tech standpoint? What do you mean by retail management software?

At

Can you elaborate on the Modern tech capabilities in apparel retail software that can boost a brand’s competitive edge?

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Exclusive Interview With Julius Černiauskas, Ceo Of Oxylabs

Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. Analytics Insight has engaged in an exclusive interview with Julius Černiauskas, CEO of

Kindly brief us about the company, its specialization, and the services that your company offers.

Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. In simple terms, we provide all the necessary tools and solutions for businesses looking to extract publicly available data on a large scale. A significant part of our daily processes is to support web scraping. Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Our product portfolio includes both complete out-of-the-box solutions such as the Scraper APIs and supporting infrastructure such as proxies. With the former, our clients only have to send requests to our endpoints, and they get the data sent back to them. With proxies, they have to develop automation software themselves as we only provide the know-how and the supporting blocks.  

Kindly mention some of the major challenges the company has faced till now.

Providing web scraping solutions is always fraught with challenges. One part of the equation is that the industry is relatively new. Being a pioneer is an amazing feeling, but it makes challenges so much more difficult as no one can help you out. You have to figure out how to solve issues all on your own. Being a front-runner means creating the pace and practices. It means a lot of other companies are looking up to us and following the models we create. Another part is the technical complexity of the process. We pride ourselves on helping clients achieve an uninterrupted flow of data. Maintaining infrastructure, creating scraping code, and everything else is extremely resource-intensive. With the added novelty of the industry, we are always facing avant-garde challenges. Finally, web scraping hasn’t established itself in the public consciousness yet. There’s scarcely any legislation across the world and the overall perception can be seen as somewhat negative.  While our legal team has been doing tremendous work keeping us on the right side of the law, they can’t change global perception. Yet, at the same time, web scraping is becoming an essential part of digital businesses.  

How do you see the company and the industry in the future ahead?

Another aspect of not being established in the public consciousness is that there’s little awareness of the possibilities. As we are the leader of ethical solutions and tools in the industry, we are working towards bringing ethical web scraping out of the darkness and turning it into something that is used for the common good. We have developed partnerships with universities, NGOs, and other organizations by giving them access to our solutions or

How is your company helping customers deliver relevant business outcomes through the adoption of the company’s technology innovations?

Innovation is an essential part of Oxylabs. We invest heavily in R&D, primarily in the field of artificial intelligence and machine learning, which sets us apart from our competitors. As I’ve mentioned before, web scraping is a technically complicated process, involving many different parts that can be optimized almost to no end. A part of such optimizations is parsing. Generally, when you retrieve data from the web, it’s messy and unreadable. Parsers, and other automated software, make the same documents easier to understand and process. Unfortunately, writing them is extremely costly and time-consuming. We have invested a lot of time in innovating our field through machine learning and now we have an industry-leading Adaptive Parser. It removes the requirement of writing parsers for eCommerce product pages, allowing us to significantly cut costs and provide higher quality data to our clients.  

AI is projected to be the next market. How is AI contributing to the making of your products and services?

AI is at the forefront of our innovation push. We have established an AI/ML Advisory Board with 5 leading business (e.g., from Stripe) and academia (e.g. from MIT, NASA) experts with whom we maintain constant collaboration. They help us in driving the progress of AI in web scraping further than we could do ourselves. We believe AI will play a significant role in the coming years by making parts of web scraping more accessible than ever before. Web scraping can be split into two large chunks: the discovery phase and the collection phase. The discovery phase is accepting a task from an interested party. A business may be interested in the prices of specific countries within a set region. I see AI aiding significantly in the discovery phase by either allowing vague queries to be easily acted upon or by enabling better finding processes. Secondly, the collection phase is, as we already see, greatly enhanced by the development of machine learning models. We can take out the most costly processes and completely automate them through the use of artificial intelligence. While there may be doubts about AI helping the discovery phase, I have a resolute belief that it will tremendously change the face of data collection.  

How can businesses efficiently extract the value from data, without increasing cost and complexity?

A large part of optimizing data practices is narrowing down collection practices. There’s enough data to fulfill any goal and to support any hypothesis, and it’s surprisingly easy to over-collect information. Most of the software we use in daily operations such as tracking tools, CRMs, etc., provide some sort of data collection feature. As a result, there’s plenty of data to go around at all times. What businesses should do is create clear goals for the data they already hold. I prefer to think of data as something that should have intention. Asking oneself “why are we collecting that data” is a surefire way to get down to all the necessary details. If you have to find a complicated or long-winded explanation on why it is necessary, maybe it isn’t all that after all.  

What are some of the challenges faced by the industry today?

Web scraping remains a process employed by a select few while it can be of tremendous benefit to all. At Oxylabs, we’re pushing for ethical web scraping to be recognized as a common good and aim to make it accessible to non-developers.

Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. Analytics Insight has engaged in an exclusive interview with Julius Černiauskas, CEO of Oxylabs Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. In simple terms, we provide all the necessary tools and solutions for businesses looking to extract publicly available data on a large scale. A significant part of our daily processes is to support web scraping. Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Our product portfolio includes both complete out-of-the-box solutions such as the Scraper APIs and supporting infrastructure such as proxies. With the former, our clients only have to send requests to our endpoints, and they get the data sent back to them. With proxies, they have to develop automation software themselves as we only provide the know-how and the supporting blocks.Providing web scraping solutions is always fraught with challenges. One part of the equation is that the industry is relatively new. Being a pioneer is an amazing feeling, but it makes challenges so much more difficult as no one can help you out. You have to figure out how to solve issues all on your own. Being a front-runner means creating the pace and practices. It means a lot of other companies are looking up to us and following the models we create. Another part is the technical complexity of the process. We pride ourselves on helping clients achieve an uninterrupted flow of data. Maintaining infrastructure, creating scraping code, and everything else is extremely resource-intensive. With the added novelty of the industry, we are always facing avant-garde challenges. Finally, web scraping hasn’t established itself in the public consciousness yet. There’s scarcely any legislation across the world and the overall perception can be seen as somewhat negative. While our legal team has been doing tremendous work keeping us on the right side of the law, they can’t change global perception. Yet, at the same time, web scraping is becoming an essential part of digital businesses.Another aspect of not being established in the public consciousness is that there’s little awareness of the possibilities. As we are the leader of ethical solutions and tools in the industry, we are working towards bringing ethical web scraping out of the darkness and turning it into something that is used for the common good. We have developed partnerships with universities, NGOs, and other organizations by giving them access to our solutions or otherwise supporting their goals . We help them by providing tools, sharing technical expertise, creating tools to tackle specific problems, and much more regularly. One of our most successful projects has been developing an AI-driven scraper that identifies harmful and illegal content on the internet, aiding the Lithuanian government institutions in their work. We see web scraping becoming something not only businesses use to further profit incentives, but something that works for the common good of all. We’ve been working on other initiatives that would push web scraping further into the public consciousness. Oxylabs hosts an annual conference, OxyCon, and we do a lot to share our knowledge on the legal and technical side of things with the outside world.Innovation is an essential part of Oxylabs. We invest heavily in R&D, primarily in the field of artificial intelligence and machine learning, which sets us apart from our competitors. As I’ve mentioned before, web scraping is a technically complicated process, involving many different parts that can be optimized almost to no end. A part of such optimizations is parsing. Generally, when you retrieve data from the web, it’s messy and unreadable. Parsers, and other automated software, make the same documents easier to understand and process. Unfortunately, writing them is extremely costly and time-consuming. We have invested a lot of time in innovating our field through machine learning and now we have an industry-leading Adaptive Parser. It removes the requirement of writing parsers for eCommerce product pages, allowing us to significantly cut costs and provide higher quality data to our chúng tôi is at the forefront of our innovation push. We have established an AI/ML Advisory Board with 5 leading business (e.g., from Stripe) and academia (e.g. from MIT, NASA) experts with whom we maintain constant collaboration. They help us in driving the progress of AI in web scraping further than we could do ourselves. We believe AI will play a significant role in the coming years by making parts of web scraping more accessible than ever before. Web scraping can be split into two large chunks: the discovery phase and the collection phase. The discovery phase is accepting a task from an interested party. A business may be interested in the prices of specific countries within a set region. I see AI aiding significantly in the discovery phase by either allowing vague queries to be easily acted upon or by enabling better finding processes. Secondly, the collection phase is, as we already see, greatly enhanced by the development of machine learning models. We can take out the most costly processes and completely automate them through the use of artificial intelligence. While there may be doubts about AI helping the discovery phase, I have a resolute belief that it will tremendously change the face of data collection.A large part of optimizing data practices is narrowing down collection practices. There’s enough data to fulfill any goal and to support any hypothesis, and it’s surprisingly easy to over-collect information. Most of the software we use in daily operations such as tracking tools, CRMs, etc., provide some sort of data collection feature. As a result, there’s plenty of data to go around at all times. What businesses should do is create clear goals for the data they already hold. I prefer to think of data as something that should have intention. Asking oneself “why are we collecting that data” is a surefire way to get down to all the necessary details. If you have to find a complicated or long-winded explanation on why it is necessary, maybe it isn’t all that after chúng tôi scraping remains a process employed by a select few while it can be of tremendous benefit to all. At Oxylabs, we’re pushing for ethical web scraping to be recognized as a common good and aim to make it accessible to non-developers. As such, the two challenges I see most pressing is public legitimacy and accessibility. Legitimacy has been fully achieved in the business world, but it has to spread further as web scraping can do much greater things. I believe complete public legitimacy will be achieved over time through developing partnerships with government institutions and academia. Accessibility is on us – we strive to innovate in making web scraping easier to use and more intuitive.

Exclusive Interview With Brett Hurt, Ceo, And Co

Building data assets to derive actionable insights has become an essential part of business planning. Having a huge amount of data oftentimes turns it into a liability for there is ample chance for data scientists to lose sight of a critical insight when the big data is organized haphazardly. On the other hand, a data catalog can help businesses discover data assets that were lying dormant. Data.world is a cloud-native enterprise data catalog company known for the best data practices in the industry, delivering result-centric insights. Analytics Insight has engaged in an exclusive interview with Brett Hurt, CEO, and Co-Founder at data.world.

1.  Kindly brief us about the company, its specialization, and the services that your company offers.

Enterprises are facing a trillion-dollar data problem. A recent study from NewVantage Partners found that 99% of Fortune 1000 companies planned to invest in big data and AI initiatives last year, but only 24% of respondents believe their companies are actually data-driven. My co-founders and I saw this first-hand in the market as well when we founded data.world in 2024 – for all the talk about data being critical for businesses, the most important data and analyses were typically buried in silos.

At data.world, we believe that business leaders need to view their data supply chain like their actual supply chain – incredibly valuable and essential to the operation of their business. Implementing this mindset across a business requires the right technologies. We offer a data catalog for the modern data stack, enabling both data producers and consumers to easily structure, govern, and analyze the data that powers their business. We’re also unique in the space because we have been a Certified B Corporation ever since our launch and are committed to building the most meaningful, collaborative, and abundant data resource in the world to help maximize data’s societal problem-solving utility. 

2. Tell us how your company is contributing to the IoT/AI/Big Data Analytics/Cloud Computing industry of the nation and how the company is benefiting clients.

More traditional data catalogs allow enterprises to centralize all their data into one place, creating a single point of reference for those using it. But for today’s modern data stack – and the pace of innovation surrounding it – the traditional model doesn’t go far enough. Many enterprises are wasting money on their data initiatives because they use outdated ways of thinking about data. Companies that utilize artificial intelligence and big data analytics – from those in the Fortune 500 to startups – require agile data governance, where data is easily accessible, understandable, and usable for everyone within a company. Our company data.world gives enterprises this edge. By providing fast data access, a clear context for the data, and a single platform to enhance data analysis, our customers can multiply the value of their data and use it to drive their products.

3. Kindly share your point of view on the current scenario of Big Data Analytics and its future.

Recessions, while painful for businesses and the society at large, can be powerful engines for creating more efficient businesses. I have written recently about my belief that big data analytics will play a major part in that trend as we see increasing inflation and recession indicators.

4. How can C-suite executives leverage data to deliver business value to their organizations?

When thinking about the realities of leveraging data to deliver real value for your enterprise, looking to who I call the “knowledge superheroes” can help. Take, for example, Airbnb’s founder and CEO Brian Chesky, who turned his company’s pandemic challenges into a better business model, driven by data. He turned a company with revenues falling 80 percent overnight into one of 2023’s biggest IPOs months later. 

Data catalogs and knowledge graphs can create the same type of transformative change for all companies, and every executive needs to start by getting their data house in order and equipping themselves with the right tools for their modern data stack to get that done. Doing so is critical for building a successful business model today both because of how fast technology is evolving and renewed economic uncertainty. In my recently published book, The Entrepreneur’s Essentials, I outline the five critical ingredients for building startups into big companies, and their business model is #1. In today’s market, that means investing in the modern data stack that helps your data producers and consumers in the short- and long-term.

5. The industry is seeing the rising importance of Big Data Analytics and AI. How do you see these emerging technologies impact the business sector?

Companies are rightly looking to big data analytics to drive a new wave of business efficiency and resilience by empowering teams to find, understand, trust, and use data needed to address critical business questions. This information can be used to answer questions like, “Where in my organization can I make cuts or reallocate?” and “What projects can I postpone for six months?” 

For example, over the next few months, you might need to put a critical program on hold or unfortunately let go of a percentage of your workforce. If you are leveraging a knowledge graph-powered data catalog, all information associated with the project, including team members, their skill sets, and their relationship to the project and respective data, can be cataloged and understood. Institutional knowledge is retained and connected to the business, so that it can be easily accessed when it’s time to rehire, retrain, retrench, or shift back into growth mode. We saw this happen with one of our earliest customers a few years ago when many people turned over. They were easily able to keep their data and analysis work going due to how well it had already been centralized and documented.

6. Where are we going from here?

We’re sitting in a much different economic environment than we were even a month or two ago, and businesses across industries need to be preparing proactively for the inflationary and recessionary pressures that are here now and lie ahead. Having led two prior businesses through the dot-com bubble and the Great Recession, I’m optimistic that this time will be different for two reasons: data literacy and agile governance. Since the last recession, the ability to confidently use data to inform problem-solving has improved dramatically. Now, when enterprises have the right tools and processes in place, they can have a much higher level of trust and confidence in the outcome of data-backed decision-making.

My main recommendation to enterprises is to think about data as simply the facts of your business – your customers, your partners, your staff, and your supply chain. Mastery of those facts and the analysis we can pull from them has the potential to shield companies from the worst of the bumpy economic landscape that may lie just around the corner. This time around, tech and business leaders alike have the opportunity to optimize our businesses in a way that was not even possible during the last recession.

Exclusive Interview With Arvinder Pal Singh, Ceo And Co

Digital transformation has been changing the landscape of many companies across the globe with the help of disruptive technologies. These technologies are enabling companies to obtain a significant foothold in the existing industries which is essential for generating new business models and services. Here is an exclusive interview with Arvinder Pal Singh, who is the CEO and Co-Founder of Enquero, which is one of the Genpact Companies to elaborate more on this front.  

What are the key trends driving the growth in data analytics?

As we are seeing massive jumps these days with regard to customer expectations, tech innovations, and the way business models are evolving, we can only expect to keep up with these changes provided we are able to focus on building connectivity of relevant data. Exploring avenues of connecting KPIs from various departments, such as marketing, sales, supply chain, and finance will help in addressing customer needs better. Sharing and interlinking of insights across departments within an organization can help transform lagging indicators into leading ones. This upcoming trend of connected data to connected analytics for generating connected insights will set the tone for identifying and evaluating the success parameters of our businesses in the days to come.  

How does your company’s strategy facilitate the transformation of an enterprise? The industry is seeing the rising importance of big data analytics and AI. How do you see these emerging technologies impacting the business sector?

Basically, I feel that both big data analytics and AI can together present opportunities for business innovation and growth. And the benefits of it include a better understanding of market dynamics, identification of new revenue channels, customer-tailored products, and enhancing operational efficiencies. With deeper insights and accurate predictions from AI-driven systems, businesses would be ready to manage and respond to upcoming challenges.  

How are disruptive technologies like the cloud impacting today’s innovation?

With rapid cloud adoption, businesses are experiencing improvement in time-to-market, and process efficiencies, while the reduction in operational costs, IT spending, and maintenance costs.  Cloud enables anywhere, anytime app deployment with standardized functionalities and easy options for scaling, quality control, and improved security.  

How do C-suite executives leverage data to deliver business value to their organizations?

I believe data is that one common language that brings everybody in an organization to a common point of agreement and makes consensus building much more objective-driven rather than being forced upon. Leaders of today must evaluate what problems to address with the power of data for structuring a sustainable future. Data will help business strategists decide how to measure success and respond to unprecedented situations. Connected data-driven insights will help management identify gap drivers, link strategy-process-system intelligently, and deliver well-rounded decisions to enable corporate direction within and outside a business ecosystem.  

What is your biggest USP that differentiates the company from competitors? What are some of the challenges faced by the industry today?

I think the biggest challenge the industry is facing today is the lack of the right talent. The rate at which technology is evolving is immense. Adapting to this change is nearly impossible if today’s talent models continue to focus on just training and not working towards enabling self-learning and development techniques. The entire academia-employee-employer value chain needs reimagining to shape the workforce of tomorrow.  

Where are we going from here into the future with these digital technologies?

Exclusive Interview With Kamaljeet Rastogi, Ceo Of Manipal Business Solutions

Identify fraud and how it affects anti-money laundering

It is a fact that both offline and online transactions have their share of breaches and trust issues. Crimes are not limited to physical structures as they are possible through the internet. However, in online transactions, identity violations, data breaches, theft, among other irregularities, are referred to as cybercrimes while the perpetrator is known as a cybercriminal. It is a statement of the fact that data breach is synonymous with identity theft and fraud. While identity theft is a compromise or unauthorized access to users’ identities, identity fraud uses the details obtained to perform unauthorized transactions. By implication, the perpetrators, hackers breach data to steal as much identity they want. To protect online users, specific laws and regulations became necessary. These laws are referred to as anti-money laundering laws; in some jurisdictions like India, they are called the Prevention of Money-Laundering Act (PMLA). This article addresses how identity fraud affects money laundering.  

Identity Fraud and Anti-Money Laundering Act.

If the hacker goes further to use the user’s details, say a credit card or wallet address of digital assets for economic gain, it becomes an identity fraud. To help protect the user’s account, as in the case of the recent Twitter bitcoin scam where prominent persons, exchanges, and some corporate accounts were hacked including Coindesk, Binance, Apple, Elon Musk, etc. a set of cryptographers, researchers, or programmers set to track the destinations of the funds. Although researchers applied cryptography and cybersecurity countermeasures to track the destination of funds, the identity and even the funds weren’t recovered. Likewise, a hacker with a bank customer’s sensitive data may defraud the victim using a few details like a biometric verification number. However, before and during Twitter development, the network has some regulatory guidelines to meet to mitigate identity fraud in the future. Most cybercrimes are an attempt to launder money, evade tax, sanctions, etc., hence, making the state concerned with maintaining normalcy. The states and their associated institutions try to restore normalcy by enacting laws and regulations that will guide digital identities because once identity is compromised, there will be fraudulent transactions. For identity fraud to occur, there must be identity theft, synthetic identity, or account takeover. It happens through Phishing, malware, blackmailing, among others. Identity fraud can come in credit card fraud, loan or lease fraud, phone or utility fraud, and government-issued documents or benefits fraud, etc. Below are broad classifications of identity theft:

Synthetic Identities: when a hacker or a cybercriminal combines a real and fake identity to create a new account, it is called synthetic identities.

Account Takeover (ATO): there are many fake accounts, rewritten by hackers to defraud people. Consequently, the hacker goes a long way to perform fraudulent transactions with the victim’s identity. Simply put, an account takeover happens when a cybercriminal steals and rewrites an account of their victim. For instance, in financial services, hackers can clone accounts to receive or solicit support on behalf of the victim.

Effects of Identity Fraud on AML Measures

In online research conducted by The Harris Poll on behalf of NortonLifeLock among 10,063 adults (aged 18+) in 10 countries, including India, 4 out of 10 respondents are identity theft victims. Identity fraud effect AML acts in several ways, as listed below:  

Difficulty in Onboarding Clients KYC

Know Your Customer, often called KYC is an AML compliant measure that helps compliant teams and regulators file and onboard users’ identities on their network. Because of the complexities of identity fraud, the process becomes slow and ambiguous. According to the Thomson Reuters survey in 2023, it takes financial institutions up to 2-4 weeks to onboard new customers. The delay is because the KYC team is taking due diligence to reduce identity fraud. For instance, many channels, including ransomware, and malware programs, make fake identities difficult to detect. The dark web comprises hackers and cybercriminals who falsify and sell identities. Consequently, dark webs and other ransomware and malware are frustrating KYC processing.  

The Increasing Cost of AML Acts

The time they say is money. If a simple KYC process that should take a few minutes takes weeks, the cost becomes high. In a commissioned Forrester report on the Total Economic Impact (TEI) of Regulatory Onboarding, it costs an average of $6,000 to onboard new customers, considering factors like risk rate, country regulations, etc.  

Possible Solutions

Updating AML acts: New fintech solutions are evolving, for instance, Openfinance. Therefore, AML acts should include the emerging Fintech evolutions to enable an all-encompassing law that will include an Open finance network. That way, cybercriminals will not exploit the weak regulations to launder money.

Technology: Using big data, blockchain, and other emerging technologies could further improve anti-money laundering acts. For instance, applying blockchain will secure identity in a timestamp and transparent manner. Hence, improving AML compliance.

Exclusive Interview With A Dev Team Member

First of all congrats for the job you did so far, but I think you already know that half of the world is supporting you!

Thanks! Me and my wife read your blog, and after you wrote about the Dev Team, we thought it would be a good idea to find you. Your blog is the first hungarian language blog or newsportal we communicate to directly.

Special thanks for that. Let’s start with who the members of the Dev Team (no names of course) are, and how you organize your work since you are living in different countries, continents.

Members of the Dev Team are software, electronics and cryptographics professionals from all over the world. The members of the team – or much more, the core – are from Hungary, France, Belgium, England, Russia, Israel, Ukraine and the USA. We work in a way, that we distribute our work files among us, and with team work, we put the ideas together. The average age is about 30 years old. Most of us don’t know each others name and never met each other.

How many are you?

Everyone has a full time job – and of course this has influence on the Dev Team’s work, but usually there are 15 active members working on the job at the same time.

How do you organize, where does the idea come from to hack the iPhone, and why did you set it up?

We are high tech enthusiasts and hackers… hackers in a good way. We like to crack things and see how they work. Most of us have worked with UNIX and OS X for a long time. Few of us knew the others from there, and other professionals have joined later, those whose work we appreciate a lot.

Do you get any threats or “feedback” from Apple? Did you have any contact with the company?

Apple never made contact with us. We make sure we never break the law when we release a new software. PwnageTool and QuickPwn are very complicated, because these softwares remove the necessary parts from Apple’s firmware. We NEVER release pirated softwares.

How much time do you spend on the crack, and other iPhone-related works?

We are working on it 24 hours a day. While one of us are working on it, others are sleeping, and we continually switch. IRC is running in the background all the time, even when we are working onour private jobs, so we have worked on the iPhone thousands of hours. I have to mention, that we spend a lot of money on special hardware and reverse engineering softwares, also from our own money.

Do you get any donation, do you make any profit out of the huge work you made anyway?

We finance everything with our own money. Most of the team has a good job that pays good money in the IT field. The Dev Team is our hobby and although it is very time consuming, yet it still is a hobby. We didn’t take money from anyone!

How many people cracked their iPhones with your program? Do you have any idea how much iPhone users freed their phones?

We have more than hundred thousand recurrent PwnageTool and QuickPwn users. It is hard to estimate how many exactly, but a lot.

Why it is so hard to unlock the iPhone 3G? What is the main difference between 2G and 3G that has prevented the unlock so far?

Apple and Infineon made a very serious work and made almost impossible to unlock the iPhone 3G. They learned from what we did with 2G and made the 3G much more safer.

How far are you from suceeding with the unlock?

This is secret of course.

How deep was the 2.2 baseband update? If you want to make a sim-unlock on this as well, do you have to start the job from scratch? So, if someone accidently updated the baseband, does he have to give up, or does he still have a chance to unlock his phone?

At the moment the exploits we used to run our codes on 2.1 and older basebands has been removed from 2.2. 2.2 closed the security breach we used to control the baseband as we wanted and at the moment 2.2 baseband is bad.

What do you mean “bad”?

In 2.2 baseband there is no such an exploit we can use, so it is bad :-).

What do you think about the sofware and hardware of the iPhone 3G compared to other smartphones?

The iPhone OS is based on UNIX/Mach operating system, and both UNIX and Mach is a result of many years of developement. G1 is using Linux, which has a similar story. Fortunately nowadays mobile processors are powerful enough to use UNIX.

What kind of deficiency does the iPhone OS have, and in which direction would you develop it, if it depended on you?

It would need to be more open.

Why and for who do you do your work?

First of all for myself, for us, and for the people who prefer an unlocked phone. We bought a flat in Budapest with my wife, and the agent does not come to our home every week to check if we had painted the walls red, does he? The situation is similar with the IPhone and other devices we buy as well.

What do you do on week days?

We work and play. We have a very special Hungarian Vizsla (deerhound), he keeps us busy all the time.

Why did you choose a pineapple as your logo?

Apple/Pinapple, Pwn/Own, PwnApple (Pwning Apple)

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