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Time to Change the Game of Online Lending With AI and Big Data

Time to Change the Game of Online Lending With AI and Big Data

As digitization grows in size and width, more and more companies are seeking ways to modify their digital lending services. It would be effective as well as profitable for both borrowers and lenders. And as a topping on the cake, companies resort to Artificial Intelligence and Big Data as they believe they are the future powerhouse of loans.

Originally banks being the lenders make the lending decision based on a loan applicant’s credit score – which is a 3-digit number collected from renowned credit bureaus, like Equifax and Experian. Credit scores are obtained from large piles of data, such as credit history length, payment history and credit line amounts, and are used to decide whether the applicants would be able to repay their debts. They are also good to determine the interest rate of loans.

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Low credit score is an indication that you are a risky borrower, which may end up in rejection of your loan application or else you have to pay excessively higher interest rate.

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Artificial Intelligence: What the Future Holds for India, Next to US – @Dexlabanalytics.

However, according to digital lending platforms, this kind of information isn’t enough – they fail to draw the actual picture of the loan applicant’s credit worthiness. Rather, it is advisable to include hundred other data points in the scrutiny process, and they don’t have to be based on financial interactions alone. Include educational certifications, employment documents, and even you can take help from minor information, like your nap time, website browsing preferences, chatting habits and so on.

The mechanism of Peer-To-Peer Lending

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At times, the concept of Big Data is downright challenging – it creates more confusion than clearing things out. Even Artificial Intelligence is included in this, though marketing teams of countless companies are relying on this advanced technology to enhance profitability and efficiency in operations – pundits from the online lending industry believes AI can actually change the way fintech companies perform.

Artificial Intelligence: Let’s Crack the Myths and Unfold the Future to You – @Dexlabanalytics.

Leveraging AI

For example, Upstart, a California-based Peer-to-Peer online lending company uses the power of AI to process loans. It implements machine learning algorithms to perform underwriting decisions. Machine Learning possesses the ability to analyze and coordinate large chunks of customer data to draw patterns that would remain unnoticed if done manually through human analysts.

According to Upstart, this process eventually works out well for people with limited credit history, lower income level and young borrowers. The company has also initiated an automation of 25% of its less risky loans to keep future prospects in mind.

Another Chicago-based startup Avant is harnessing machine learning to identify fraud – by comparing customer behavior with the initial available data belonging to normal customers, while singling out outliers. They are now planning to extend their services to brick-and-mortar banking structures that are planning to set their foot in the online lending business.

5 Hottest Online Applications Inspired by Artificial Intelligence – @Dexlabanalytics.

Today, digital lending is witnessing a steady growth worldwide, and India is not lagging behind. The perks of introducing machine learning and analytics are evident everywhere, so get yourself charged up and ride on the road of analytics. DexLab Analytics offers excellent big data hadoop certification in delhi ncr. Get enrolled today to experience the best!!

 

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Facebook and Microsoft Introduces ONNX: A New Open Ecosystem to Boost AI Innovation

It’s time to move beyond Artificial Intelligence frameworks. Recently, a joined effort from the Digital giants Microsoft and Facebook has paved the pathway for developers to move beyond traditional AI frameworks. The Open Neural Network Exchange (ONNX) format announced the other day that Facebook and Microsoft are on a lookout to boost AI interoperability and innovation. This piece of information was published in their own blog posts, and from there it got viral.

 
Facebook and Microsoft Introduces ONNX: A New Open Ecosystem to Boost AI Innovation
 

In Facebook’s blog post, the Social Media behemoth clearly defined its new effort is “toward an open ecosystem where AI developers can easily move between state-of-the-art tools and choose the combination that is best for them.”

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Why Ethereum Is the Next Big Thing for Today’s Netizens?

Why Ethereum Is the Next Big Thing for Today’s Netizens?

 

Today, Pelle Braendgaard writes distributed applications, or “DApps,” for Ethereum—a cryptography-based technology that is waiting to make an impact. It’s similar to the green field of 1990’s web, providing similar opportunities as then.

The birth of DApps

If people at all know about Ethereum, it is as Bitcoin’s first cousin that stands for everything experimental and of course Braendgaard, who is widely acclaimed as the old-guard programmer. The price of Ether, the coin underlying Ethereum, has spiked up by over a factor of 20 in the last 6 months. Unfortunately, on the zest to become rich quickly, many of us have overlooked Ethereum’s prominent significance. More than just being a new type of digital currency, Ethereum has developed into a new breed of distributed computer, which no one can control but can see inside out. Through this computer, a new creed of applications is launched -“DApps”.

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How to Devise a Big Data Architecture – Get Started

How to Devise a Big Data Architecture – Get Started
 

Designing Big Data architecture is no mean feat; rather it is a very challenging task, considering the variety, volume and velocity of data in today’s world. Coupled with the speed of technological innovations and drawing out competitive strategies, the job profile of a Big Data architect demands him to take the bull by the horns.

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Keep Pace with Automation: Emerging Data Science Jobs in India

Indian IT market is not yet doomed. In fact, if you look at the larger picture, you will find India is expected to face a shortage of 200000 data scientists by 2020. Where traditional IT jobs are going through a rough patch, new age jobs are surfacing up, according to market reports. Big Data, Artificial Intelligence, the Internet of Things, Cloud Computing, and Cybersecurity are new digital domains that are replacing the old school jobs, like data entry and server maintenance, which are expected to reduce more over the next five years.
The next decade is going to witness most vacancies in these job posts:

However, just because there is a wide array of openings for a web services consultant doesn’t make it the most lucrative job position. Big Data architect job openings are much less in number, but offer handsome pays, according to reports.

A median salary of a web services consultant is Rs 9.27 lakh ($14,461) annually

A median salary of a big data architect is Rs 20.67 lakh ($32,234) annually

Now, tell me, which is better?

As technologies evolve so drastically, it becomes an absolute imperative for the techies to update their skills through short learning programs and crash courses. Data analyst courses will help them to sync in with the latest technological developments, which happens every day, something or the other. Moreover, it’s like a constant process, where they have to learn something every year to succeed in this rat race of technological superiority. Every employee needs to make some time, as well as the companies. The companies also need to facilitate these newer technologies in their systems to keep moving ahead of their tailing rivals.

Re-skill or perish – is the new slogan going around. The urgency to re-skill is creating a spur among employees with mid-level experience. If you check the surveys, you will find around 57% of the 7000 IT professionals looking forward to enroll for a short time learning course have at least 4 to 10 years of work experience. Meanwhile, a mere 11% of those who are under 4 years of experience are looking out for such online courses. It happens because, primary-stage employees are mostly fresh graduates, who receives in-house training from their respective companies, hence they don’t feel the urge to scrounge through myriad learning resources, unlike their experienced counterparts.

 

 

Today, all big companies across sectors are focusing their attention on data science and analytics, triggering major reinventions in the job profile of a data analyst. Owing to technology updates, “The role of a data analyst is itself undergoing a sea change, primarily because better technology is available now to aid in decision-making,” said Sumit Mitra, head of group human resources and corporate services at GILAC. To draw a closure, data science is the new kid in the block, and IT professionals are imbibing related skills to shine bright in this domain. Contact DexLab Analytics for data analyst course in Delhi. They offer high-in demand data analyst certification courses at the most affordable prices.

 

4 Ways Airlines Industry Can Use Big Data for Better Customer Satisfaction

4Ways Airlines Industry Can Use Big Data for Better Customer Satisfaction

While waiting to board your plane, the last thing you would want to hear is – we regret to inform, your flight has been delayed or worse cancelled, leaving you exasperated at the very hour. Even though your flight takes off on time, while waiting in front of the baggage carousel, you may face some moments of anxiety before your bag arrives on time. Luckily, these distresses are now becoming a thing from the past.

Things are changing, and technology world is evolving drastically. By leveraging Big Data and technology upgrades, aircraft industry has been able to improve their operations and work more smoothly and accurately. In addition, the air travel industry is witnessing several benefits, in terms of revenue and consumer satisfaction.

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Here are the ways in which airlines have been using data to derive maximum operational gains everyday:

Smart Maintenance

Wear and tear is common, even the most advanced airplane models equipped with superior technology require time to time maintenance. Owing to this, travelers may experience delays – as per 2014 survey data, mechanical glitches were the second most reason for the majority of flight cancellations and delays. Maintenance takes its toll on airlines potential as the planes need to be grounded for repairing.

With Big Data, airlines can easily track their planes, predict crucial repairs to be done, and provide advice about which parts need to be bought ahead of time and which to keep in reserve on hand for last minute technical issues.

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Reducing Jet Fuel Use

It is impossible to predict how much fuel is used onboard for any given route, historically. But Big Data analytics and cloud data storage has made the impossible possible – you can now track how much fuel is being consumed by each airplane, while taking all the factors into consideration. This paves the way for airlines to draw predictions about the amount of fuel required for a trip to how many number of passengers can board at once.

Taking the Boarding Decisions

Remember, airlines lose if they fly with empty seats, so it’s in their best interest to get everyone onboard. With the help of real-time data, airlines can now easily decide whether to wait for a passenger or leave on time so as not to harass other passengers who might catch connecting flights. Smart boarding is now the key, gone are the days when decisions used to be based on instincts. It’s time to enhance efficiency and performance.

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Tracking Bags

Travelers who travelled before had to be hopeful about their luggage making it back to them. But now, Big Data revolution and tracking technology has changed a lot of things. Nowadays, airlines ensure its travelers the peace of mind that they will surely receive their luggage as promised.  Delta is the first airline that offered tracking data facility for its passengers, using an app format. Customers can easily monitor their bag, reducing the uncertainty revolving luggage arrival.

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Flight operations, crew operations, marketing and air cargo are some areas in airlines industry that boast of rich opportunities for Big Data solutions implementation. In our modern economy, competition is at its peak. To make your airfare rates cheaper and save big on jet fuel, shaking hands with Big Data technology is imperative.

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Top 10 Nifty Tools to Manage Big Marketing Data for Companies

Big Data is the latest buzz. It has to be effectively analyzed to formulate brilliant marketing and sales strategies. It’s of immense importance, as it includes humongous amount of information accumulated about customers from numerous sources like email marketing schemes and web analytics.

 
Top 10 Nifty Tools to Manage Big Marketing Data for Companies
 

However, due to the vast magnitude of information available, it may get quite difficult for marketers to analyze and evaluate all the data in an efficient way. Fortunately, plenty of tools are available in the market that can manage mammoth marketing data and here are few of them:

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Are you taking care of your digital self?

Whether you like the idea or not, we all have a digital self, a facade that we put on to engage and participate in the technological world! As per psychoanalysts and physicians, a theory proposed by them says that there is a ‘true self’ that is the instinctive core of our personality, it must be realized and nurtured. And there is also a ‘false self’ that is built to protect this true self. From what you ask? From the dangers of insults and vulnerabilities!

Dexlab blog for 12th Oct

Our true selves are usually complex and fragile but it ultimately remains to be our essence. In trying to share that self with the world, we send out our decoy selves to take on the day-to-day vulnerabilities, challenges, and anxieties that come forth.

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Big Data Hacks: 5 Amazing Free Data Sources

Big data hacks: 5 amazing free data sources

With the data explosion revealing a continuum of numbers and facts and figures across the web and across businesses, it is of no doubt that data is omnipresent. But as the saying goes, sometimes it is hard to see the forest due to all the trees.  A big myth among several companies is that they need to hire data analysts to look for their own data for analysis and to reap the benefits from Big Data analytics. But you must realize that this is far from the truth.

There are more than hundreds in fact even thousands of free data sets available for analysis and use for those who are smart enough to know where to look for them. Here is a list of 5 most popular free data set sources that are widely used globally. There are several more out there for those who are keen enough to look for them.

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  • Data.gov: in compliance to the promise made by the US government last year all the government data is available for free on the internet in this site. The site is a useful source of information on everything starting from numbers in association to crime to climate change and much more.
  • Socrata: another great place to get scoop on the latest government related data along with some useful visualization tools that come built into the web portal.
  • org another place to access government data for free. One can get access to government data from the US, Canada, EU, CKAN and more.
  • World Health Organization data portal: a place to access all the statistics of hunger, health and disease of the world can be accessed here.
  • FaceBook Graph: FaceBook over the past few years has tightened their security and privacy settings. But there are still some amounts of data open to eyes without any privacy. And FaceBook provides information and access to all this data with their Graph API. While users may not be happy to share them with the world, they probably have not yet figured out how to hide them.

A bonus free data source that could also be fun to explore.

Face.com: get face recognition data with this fascinating tool and analyze possibilities like the creator.

These days a lot of forward thinking companies are trying to data driven, but they may not have ample resources to get their own data right away. So, it may be a good idea to begin with these publicly available free data sources. The best tip for data scientists is to learn to ask the right questions to get the right answers.

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