The days of depending on banks and a limited number of high street forex brokers to carry out cross-border fund transfers are long gone. Now that this field is home to several FinTech players, sending money from one country to another is no longer as time consuming, complicated, or expensive as it was until a couple of decades ago. However, can using big data give FinTech alternatives a further edge?
It is possible that money transfer companies might not see the benefits of using big data to compile information of different kinds at this stage, given that aggregation of big data comes at a cost. This may be particularly true of companies that already have their fare share of repeat customers. However, a clear benefit of looking at big data in the right way is that companies can use the information they get to build better personal relationships with their customers.
Analyzing big data continually can also help overseas money transfer companies spot glitches and out-of-normal occurrences. Consider this example. U.S.-based Xoom relies on some of the top players in the big data world to analyze all the data related to its transactions. In 2011, the system detected an anomaly that might have missed the human eye. A criminal group was carrying out an exceptionally high number of New jersey-based Discover Card transactions to defraud the company, and they may well have passed off as being legitimate without big data analysis.
The Benefits are Far Reaching
Carrying out an international money transfer requires the exchange of information in different forms. Companies typically have access to the sender’s and recipient’s complete names, the countries and the currencies involved, the payment and transfer methods, as well as the transfer amount. Service providers, in all likelihood, also know the reasons behind most transfers.
Overseas money transfer companies can rely on the analysis of big data to formulate strategies by identifying underlying patterns. Businesses, for example, stand to benefit by learning why their customers favor one service over another, their frequency of transfers, how much money they send, and whether they transfer money to one or more recipients.
By aggregating big data, money transfer companies can also get insight into aspects such as timestamps, locations, and devices. They can, for instance, use the information to determine if customers prefer using their websites or apps.
M-Pesa is a mobile phone-based small-value money transfer company that is headquartered in Kenya. While originally only a money transfer company, it has now branched in into salary payments, purchase of goods and services, as well as micro-financing. Around 85% of Kenya’s households now use the services of this company in some form. By analyzing the big data it has access to, M-Pesa can get valuable insight into aspects such as disposable incomes and remittances.
Discerning the Useful From the Not
Big data brings with it information that is voluminous, to say the least. As a result, being able to sift through what’s important and what’s not is important. Ideally, money transfer companies should focus on specific points and aim to build personal connections with their customers. FinTech companies such as Azimo, TransferWise, OFX, and WorldRemit will benefit if they can manage to use their big data to identity and act on prevailing trends. For customers, having the ability to voice their needs will make them feel empowered.
Conclusion
The monetary benefits of analyzing big data might not be plainly visible to money transfer companies at the onset, but the potential the process holds gives businesses the ability to build long standing relationships with existing customers. Where there’s ongoing patronage, money follows.
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Singapore is quickly becoming Asia’s go-to hub for all things digital. The past couple years have seen a steep rise in the number of big data and AI start-ups from the city-state. Studies indicate that the data analytics industry contributes to nearly 1 billion Singaporean dollars to it’s economy each year. This is all thanks to Singapore’s Smart Nation vision, to be an economically competitive global city.
With this thriving new industry being facilitated by the government, it is not surprising that the start-up scene in Singapore is booming as well. And why not? Opportunities and talent are abundant. So, here is a list of big data analytics companies from Singapore who are thriving in this growing industry.
1. Aureus Analytics: First founded in 2013, Aureus Analytics is a Customer Intelligence and Experience company. The company helps insurers to provide superior customer experience leading to greater customer retention, loyalty and lifetime value. Their propriety products and platforms, Crux and Pulse, support the rapid enablement of big data analytics at the point of decisions. They are equipped with powerful analytical models, which are flexible enough to allow business users to plug and play their custom algorithms. Initially based in Singapore, Aureus Analytics have offices in Mumbai and New York as well.
2. Crayon Data: Crayon Data is a big data and AI start-up, with an ambitious vision to ‘simplify the world’s choices’. Crayon’s flagship product Maya™ is the world’s only choice engine, delivering digital personal experiences centred around taste. Powered by Crayon’s patented TasteGraph™, ChoiceAI and Lifestyle Marketplace, Maya makes it possible for any enterprise to compete in the ‘lifestyle economy’, by personalizing each customer’s experience. The platform enables enterprises to link their behaviour data to Crayon’s Tastegraph™ to create massive Personalised Taste FingerPrints for millions of their customers. Started in 2012, they have offices in both Singapore and India.
3. InfoTrie: With their headquarters in Singapore, InfoTrie is a News Analytics, Financial Engineering and Big Data company. Since being founded in 2012, they have since expanded to India and Europe. By leveraging big data technologies, they are changing the way unstructured data is consumed in the field of Finance. FinSentS, their flagship solution is a cutting-edge Sentiment Analysis and News Analytics engine. Along with their other APIs, they help financial institutions, analysts, traders and investors evaluate past performances and assess current financial positions of assets, topics and companies.
4. Lynx Analytics: Lynx Analytics is a product company founded in 2010 by a group of professors and students from INSEAD. This Singapore based start-up aims to solve complex business problems with big data graphs. Their propriety platform, Lynx Enterprise, enables scalable processing of large datasets, by visualizing and analysing the Web for invisible relationships in business and public data. Primarily serving the telecommunications and financial services industries, they operate in the United States, European Union, Hong Kong, Indonesia, Philippines and Malaysia.
5. Nugit: Based out of Singapore, Nugit is offers a Data Story-telling platform, which supplies online marketers and agencies with insights to help achieve ROI improvements and cost savings. It does so by making important stories hidden in data accessible in real-time. The platform uses artificial intelligence to fill gaps between dashboards and stories and creates smart campaign reports in an email-friendly format. Started in 2013, the company uses its platforms to put a human perspective to the changing world of the digital era.
6. Plunify: Founded in 2009 with the purpose of optimizing chip design performance, Plunify developed a cloud platform that enables semiconductor chip designers to shorten product time-to-market and reduce development costs. Their flagship software product, InTime, provides FPGA timing closure and optimization solutions using unique Machine Learning technologies. Originally from Singapore, the software company has operations in Malaysia, China and Japan as well.
7. Sift Analytics Group: Headquartered in Singapore Sift Analytics Group is one of the initial providers of enterprise software solutions. Having started in 1999, the organization is a veteran in the field of Big Data analytics. They help enterprises obtain clear, immediate and actionable insights into current performances. As well as the ability to predict future outcomes for effective planning. They provide solutions across a range of areas, including Predictive Analytics, Business Intelligence, Enterprise Planning and Budgeting, Enterprise Marketing Management, and Enterprise Content Management.
8. Sparkline: A software company founded in 2013, Sparkline aims to helps enterprises develop a practical, strategic and saleable approach to Digital Analytics. Through a range of customized consulting, education and in-house technology solutions, they enable companies to focus on a data-centric framework. Their Propriety Framework engages businesses across the data spectrum and interprets large digital data sets to provide insights into the behaviours of their customers. With their headquarters in Singapore, Sparkline specializes in Digital Data interpretation and optimization to achieve superior ROI.
9. Taiger: Taiger is a Singapore based company which develops artificial intelligence semantic software for finance, insurance and government sectors. They specialize in knowledge worker automation solutions, cutting edge AI technology and large scale digital transformation. The company offers several platform solutions and tools such as iConverse, iSearch and iMatch, which substantially and quantifiably increase operational efficiencies while reducing risk. Having been founded in 2015, they now have operations spread across the globe, including Madrid, San Francisco and Hong Kong.
10. Tookitaki: With a vision to emerge as the leader in machine learning powered regulatory compliance, Tookitaki is a machine learning forecasting platform for the banking industry. They are building an intelligent decision support system (DSS), which helps enterprises and business owners go beyond the barriers of existing statistical packages. Their flagship products Alerts Management Suites (AMS) and Reconciliation Management Suite (RMS) focus on anti-money laundering and reconciliation, respectively. The company was founded in 2014 and have offices in Singapore and India.
11. Vi Dimensions: Vi Dimensions was founded in 2015, with a simple idea in mind. Applying video analytics efficiently, with the help of data analysis and machine learning. They aim to build smart surveillance on a larger scale, by tapping into the vast network of cameras throughout a city. The Singapore start-up has developed an abnormality detection (AD) technology, which can identify abnormalities in countless variations of public behaviour, right from unusual crowd build-up to public brawls and unattended toddlers. Using their ground-breaking algorithms and Machine Learning techniques, their propriety software can sift through large amounts if video feed streaming in real-time and derive actionable in-sights accordingly.
12. ViSenze: Born out of a lab in the National University of Singapore, the founders of ViSenze delivers intelligent image recognition solutions that shorten the path to action as consumers search and discover on the visual web. Built on deep learning and computer vision, they power visual commerce with artificial intelligence at scale for retailers, brands and publishers. Using breakthrough technology to turn any image and video into engagement opportunity, by simplifying search experiences and uplifting conversion rates. Having started in 2012, the company now has offices in the U.S., the U.K., India and China, besides Singapore.
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Big Data and analytical skills are becoming an important part of the IT industry worldwide. Hence, there is a growing demand for people who possess the required skills and above all, are competent to work in these core sectors.
However, acquiring big data and analytical skills is not as difficult as one tends to believe. Generally, there are many other online courses that are available for free, while you can take paid, specialized courses to improve your skills.
Here we list nine top free online courses to boost the Big Data and Analytical Skills.
Basics of Big Data
For starters, the Basics of Big Data is a very important course. It helps you understand what Big Data is all about. Free online courses are available from Udemy. It includes online tutorials on Hadoop, Hive, MapReduce, Spark, and Pigs. This course provides you with essential information related to Big Data and provides an in-depth understanding of various technologies that are currently in use. Udemy’s free online course also gives you real-world success stories to help you better understand what Big Data is all about. Take this course as launch-pad for your career in Big Data.
Spark for Starters
Databricks, the parent organization of Spark provides several online courses free. The best among these for Big Data and Analytical Skills is the introduction to Spark. You can also learn Apache Spark, which is vital for you to build a career in companies that look at complex analysis from real-time data acquired through multiple sources, Databricks’ other free online courses help you develop more skills.
R-Basics
Also available free from Udemy, R-Basics allows you to learn about open statistical program language- R. The course covers everything from downloading and installing R as well as its support packages, simple steps on utilizing the program and various code lines. This free course includes videos and self-assessment tests.
Python for Starters
Offered by Python Software Foundation this free online course is vital for Big Data and Analytics. “Python is an interpreted, interactive, object-oriented programming language. It incorporates modules, exceptions, dynamic typing, very high-level dynamic data types, and classes. Python combines remarkable power with very clear syntax. Python is portable: it runs on many Unix variants, on the Mac, and on Windows 2000 and later,” says it’s providers. You can read the free beginner’s guide and take online tutorials for using this software.
Basics of Machine Learning
Available from Udacity, this course for beginners is free. However, you need to know basics of Python and use of statistics. Other than Udacity, there are various other online free tutorials that help you get insights into machine learning. These basic and free courses enable you to choose a machine learning course that can help make a career in this field.
Level Probability and Statistics Guide
You can avail a free, self-learning course on Level Probability and Statistics from the Stanford University. However, this is only an introduction to the subject. You will need to further develop your skills in Level Probability and Statistics use by hands-on training or through a paid course.
Free Artificial Intelligence Basics for Beginners
Udacity also offers a free course on Artificial Intelligence Basics for beginners. This self-paced and self-learning course is aimed at creating a better understanding about AI and its uses, future projections and practical uses in Big Data and Analysis.
Data Management with R
Data Management with R course to boost your Big Data and Analytical Skills is available free from a variety of sources. It teaches you how to use R for data analysis, statistical computing, and reading graphics. The course is available from Microsoft for free but you have to pay for the certification.
Hadoop for Starters
For those with Linux and Java skills, Hadoop Starter Kit is an excellent free online course for beginners. “The objective of this course is to walk you through step by step of all the core components in Hadoop but more importantly make Hadoop learning experience easy and fun. By enrolling in this course you can also get free access to our multi-node Hadoop training cluster so you can try out what you learn right away in a real multi-node distributed environment,” states website of Udemy, its provider.
In Conclusion
It is vital to remember, these free courses usually serve as an introduction to the complex field of Big Data and Analysis. You may wish to opt for paid courses that are available from various reputed providers, to acquire additional skills for making a career.
In general, there are online courses that are free; others charge a fee for the exams and certification- which is worth the money. Learning about Big Data and Analytics from any of the above mentioned courses is advisable. Considering the high salaries, a profession in Big Data and Analytics fetches. Exam fees and certifications usually cost between US$ 25 and US$ 100, depending upon the free course. Charges vary according to your country of residence.
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There is little doubt in anyone’s mind that big data is the key to business growth and success these days. This is exactly why over half of businesses have incorporated the futuristic technology into their daily practices.
However, to SMBs, big data analytics still seems like a game for the big time players with huge budgets. Limited budgets and an overall misunderstanding of its practicality is what’s holding many business owners back from embracing the technology, of which could make all the difference in their success.
Big data integration does not have to be an enormous undertaking, nor does it have to be used in every single aspect of the business. For SMBs that are just testing the waters, there are three key areas that stand to benefit greatly from big data support. Let’s discuss.
Understanding Customer Intentions
Providing your customers with the best CX possible is a huge challenge for big and small enterprises alike. But the key to unlocking a great experience for each consumer is understanding what they want and what they like. Sadly, just over 20% of companies design their CX around analytical data, meaning that 80% of businesses are essentially guessing or basing their strategies on limited experiences.
Big data can help to demystify the question of what your customers want by analyzing their past actions. For example, data collected from POS systems can be used to track purchase frequency and common product bundles for better shopping suggestions and personalized reminders for past customers.
Additionally, intense research and data analyzation from customer searches and trending keywords can make it crystal clear what exactly your audience is looking for. Keyword tracking systems like SEMrush record and analyze web traffic data, which you can use to form strategies that align with the goals of your customers. By identifying the pressing questions through this type of research, your brand can provide the exact answer that your audience wants.
Small businesses need to know that understanding your customers is much more than just creating profiles that breakdown the age, sex, and location of your audience.
Hire Better Talent
Bringing in the best talent is essential for any business to grow. But, making one bad hiring decision can set small companies way back. 75% of companies report that they have made a poor choice when hiring someone, which resulted in a $17,000 loss in profits due to lower quality work, or the time lost looking for a replacement.
People analytics can help HR departments make their entire recruiting process more precise and data-driven from start to finish. Systems like Predictive Index use people analytics to gauge each applicant’s aptitude and qualifications to predict their likelihood of success with the company.
Every candidate completes personalized assessments that measure their potential, giving recruiters the exact data that they need to make a more informed final decision. Furthermore, Predictive Index uses AI technology to record applicant behavioral patterns and create reference profiles for better recruiting strategies in the future.
By using “people analytics” throughout the recruiting process, SMBs can discover better talent and understand the qualities that signal better output for the job. Many companies and HR departments have turned to data-backed recruiting tools to automate much of the hiring process, such as qualifying resumes and scheduling initial interviews. This can save HR teams all kinds of precious time that can be used to focus on more important matters.
Plan for a Big Future
Finally, one of the most common – and possibly most effective – uses for big data is predictive analytics for business planning. This is an application of data mining technology that breaks down the numbers to make accurate business forecasts for all sorts of industries.
Walmart has been using big data for predicting sales trends and executing smarter inventory management for years; proving that retail companies can improve their demand and supply cycles with this kind of technology, even if it is on a smaller scale.
Many SMBs have several concerns when it comes to using this kind of technology, especially in terms of cost and complexity. However, the cost of integrating predictive analytics may be insignificant when compared to the potential losses from failing to foresee shifts in the market. Businesses that use predictive analytic technology have reported that it has made significant improvements in their lead generations and sales numbers by providing the insight they need to stay one step ahead.
Software tools like InsightSquared make it easy for small companies to analyze data and plan accordingly. InsightSquared collects previous data from CRM systems to create reports and accurate forecasts for more targeted marketing and sales strategies. These reports also answer key questions like the current status of conversion rates or whether teams are on track to hit their sales quotas for the quarter.
While some changes are impossible to foresee, using predictive analytics is a smart way for smaller businesses to make sure that they are ready and able to handle whatever comes their way.
In Conclusion
Big data is not just for big businesses these days. Every company can stand to benefit from the power of number-driven insights, and thanks to modern software systems, integrating these valuable datasets is simpler and more accessible than ever for SMBs.
There is no point to resisting this massive shift in the business world. The longer you wait to adopt big data, the further behind you are falling.
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Chatbots have become a significant part of our everyday lives. Judging by the market situation today, it seems like chatbots are here to stay. Although chatbots aren’t being used to their full potential, the new millennium has brought a change for the better. Chatbots are finding their place in marketplaces worldwide, and recent results stand behind scientific assumptions that the artificial intelligence is slowly ‘conquering the world’.
Information technology is moving a lot faster than other industries nowadays. As a result, budget-retailers like Nordstrom Rack rely on chatbots to provide assistance to their customers, and so does TJ Maxx. The number of online stores embracing chatbots goes on and on, and their influence is becoming larger by the day while also extending to various industries. Consequently, it seems that soon enough, chatbots will become the most effective marketing tool of the millennium.
No matter how much times change, direct communication will always be the best way to sell products. Be that as it may, technological advancement has brought a new way of communication – the interaction between robots and humans.
One thing is indisputable – the future belongs to chatbots. However, it’s still unclear how much and in which direction will this technology continue to grow. Namely, futurist Ray Kurzweil claims that chatbots will become indistinguishable from humans by 2029. Moreover, we already know that the beginnings of chatbots date back to 1950. That being said, if the chatbot can grow to be indistinguishable from humans in nearly 8 decades, it’s hard to imagine the distances it will reach by the end of this century. Check out the infographic below which outlines more predictions of the sort as well as more mind-blowing data.
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The world has become increasingly saturated with millions of options available to consumers. So, it has become extremely important for enterprises to limit the choices they offer their customers. The best way to do this is to provide customized and catered offers which are specific to individuals. Personalization engines make that process easier for enterprises. Organizations in this niche provide technological solutions that help create customized digital experiences for individual consumers.
Moreover, by collecting and analyzing customer information, personalization engines also help in communicating with individual consumers. Thus, any form of communication, be it messages, emails, or newsletters, can all be personalized to an extent for specific customers. Thereby provoking an open dialogue and subsequently ensuring customer loyalty.
Organizations today are successfully expanding this niche field. With evolving innovation and expertise in the field of Big Data, AI and Machin Learning, they have made it easier for enterprises to provide customized services for to their consumers. And while most them are from North American or European soil, the personalization bug has spread to the other side of the world too. In fact, study reports have revealed that APAC marketers and consumers are more inclined to personalized marketing than their Western counterparts.
Adobe and Econsultancy released a joint report earlier this year, the “Digital Intelligence Briefing: 2018 Digital Trends.” It mentions that APAC marketers are more open to digital personalization and are willing to invest in the skills and technology required for it. About 34% of marketers from APAC are ready to utilize personalization engines for better customer engagement. On the other hand, only about 16% of North American marketers feel the same way.
Quite obviously, there is a lot of potential for personalization engine platforms to grow in the APAC region. With many MNCs and newer start-ups investing in the power of digital personalization, it no longer seems like a niche field.
Below are five key-players in the APAC region, who are changing the way enterprises interact with their consumers. By the looks of how things are going, the playing field will only get bigger.
(The organizations are listed in alphabetical order.)
1. Crayon Data: Based in Singapore, Crayon Data is a big data and AI startup, with an ambitious vision to ‘simplify the world’s choices’. Crayon’s flagship product MayaTM is the world’s only choice engine, delivering digital personal experiences centred around taste. Maya enables enterprises to link their behaviour data to Crayon’s Tastegraph to create massive Personalised Taste FingerPrints for millions of their customers. Crayon currently works with leading banks, card issuers, Airlines and Hotels in APAC, India, ME and the US.
2. Dynamic Yield: Dynamic Yield is an American MNC, whose omnichannel personalization technology stack helps marketers increase revenue by automatically personalizing each consumer interaction across digital devices. It uses an advanced machine learning engine to build actionable customer segments in real-time, enabling marketers to take instant action via personalization, recommendations, automatic optimization & real-time messaging – in a single platform. The company has more than 100 customers, primarily in ecommerce and media.
3. Flytxt: Flytxt is an independent market leader in intelligent customer engagement technology. Their flagship product NEON-dX allows enterprises to drive personalized and contextual customer engagement across digital touch points using analytics and artificial intelligence. Headquartered in Amsterdam, the company has since expanded to West Asia, with offices in Singapore and India.
4. IgnitionOne: IgnitionOne is a global leader in cloud-based digital marketing technology. The IgnitionOne Marketing Platform is built on a data-driven foundation that delivers the tools marketers need to build audiences, score individuals within those audiences while optimizing results across paid and owned channels and different devices. IgnitionOne currently scores over 300 million users monthly in 75 countries and powers more than $60 billion in revenue each year for leading brands and advertising agencies. They have offices around the world, including India and Sri Lanka
5. Infosys AssistEdge: One of India’s biggest MNCs, Infosys launched AssistEdge a couple of years back. It is an “Enterprise Ready” Robotic Process Automation (RPA) product. Using the power of RPA, AssistEdge now has over 50,000 live bots in 50+ countries. Being a customer service platform, it enhances customer experience and boosts contact center agent productivity by providing an intuitive dashboard.
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