For lenders and financial institutions, accuracy and predictability are key drivers of success. Being able to predict when a borrower will repay a loan or when it’s likely to be sent to a collector can mean the difference between running a profitable business and losing the shirt off your back. And at the heart of insights like these is data – big data, to be precise.

Exploring the Relationship Between Big Data and Lending

In a traditional scenario, a person goes to a lender and asks for a loan – say, for a new car. The lender presents an application, asks the borrower to fill out some information, sign some pages, and wait for an approval.

Over the course of a couple of days (depending on how busy the lender is), they review the application. But more important than the application, they pull up the borrower’s credit score. And in most cases, the credit score – combined with a little information on income and other existing debt – will determine whether the individual is approved for the loan.

In all honesty, the traditional loan approval process is shortsighted. This is why many lenders are now reaching beyond this restricted method and relying on more data to point them in the right direction.

“We don’t have a ‘minimum Fico score,’” says Brent Sergot, World Omni Financial Corp.’s group vice president. “We review the loan application holistically because we realized Fico score is just a small part of the application process.”

Sergot isn’t the only one. Big data is playing an increasingly important role in the auto finance industry, as well as in other areas – including home mortgages, business loans, and personal loans.

Take RISE Credit as an example. This company addresses a common pain point among consumers – long and cumbersome approvals – and speeds up the loan application process to just a few hours. They do so by using proprietary algorithms and advanced scoring methods that look past credit scores and acknowledge a borrower’s true risk and opportunities.

Big Data Scoring, a cloud-based credit decision engine, has developed one of the leading technologies and claims it’s working with some of the world’s biggest banks and insurance companies.

“We develop and deploy custom scoring models that combine a lender’s internal data with thousands of pieces of external data such as location based information, web search results, behavioural tracking, device technical details, mobile app data and much more,” Big Data Scoring explains. “This enables lenders to accurately predict borrower payment behaviour, helping then make informed and more profitable credit decisions in real time.”

Then there’s artificial intelligence (AI), which is always closely intertwined with big data. Many of these same lenders are using AI engines to learn from past lending decisions and gain a more accurate picture of who applicants are and how they may behave.

Some companies are even using AI to detect fraud by comparing the behavior of applicants with baseline data for normal customers. This helps them single out the outliers and avoid the headache of working with these scammers.

Lenders Enjoy Better Insights

We’re still far from a perfect system or model that’s 100 percent accurate – and we’ll likely never get there – but big data is getting us as close as we could ever hope for.

At the end of the day, it’s all about gaining better insights in an effort to make more accurate decisions that remove risk and bolster the bottom line. Big data is helping lenders do all of the above, which gives data scientists plenty of hope to believe that analytics, AI, and the technologies that accompany them will stick around for the long haul.

With an estimated 2.77 billion social network users around the globe, social networking platforms possess an unimaginable amount of data. The reach of social networks is expanding at an alarming rate around the globe in 2019. These figures will continue to grow. Social media provides a phenomenal amount of user-generated data. Due to the nature of data which is mainly unstructured, it is a herculean task to gauge actionable insights from this sea of information.

This is where the role of Artificial Intelligence (AI) comes into play. AI is an area of computer science that aims to decipher data from the natural world often using cognitive technologies designed to understand and complete tasks that humans have taken on in the past.

While many naysayers of AI suggest that this technology will eliminate jobs, it is actually meant to enhance intelligence and effectively analyze data in order to streamline processes and work in a highly effective and efficient manner.

Before we understand the use of AI in social media, it is important to debunk certain myths about AI:

Myth 1: AI Means Robots

This is one of the most widespread misconceptions about AI. It is not a fancy name for robots. It does not mean robot moving or talking just like humans. AI uses algorithms in computer programs to execute tasks which require intelligence of humans. Very often robots are controlled by a set of AI algorithms.

Myth 2: AI Can Run Entirely on Its Own

Due to robust programming, many people believe that AI can run, function and execute programs entirely on its own. However, AI requires the human touch.

When it comes to customer experience, several AI processes can be automated. However, critical decisions in healthcare or medical might require human assistance.

Myth 3: AI Will Eliminate Jobs

AI will replace humans. Well, not exactly. Artificial intelligence is actually meant to collaborate and work with humans, transforming several job categories and creating new roles. The main purpose of AI would be to help people focus on core activities while using the technology for research.

The growth of AI will drive formation of business models and inculcate new skills in the workforce. It will bring together decision makers, businesses and communities to ensure business processes are managed in a seamless manner.

The Role of AI in Social Media

It is an era of social media. Whether it is about reaching out to new clients or nurturing existing business relationships, social media has become an integral part of interacting with businesses, influencers or customers.

Effective social media management helps enhance brand’s strength and increase social media conversations. It is an efficient way of engaging millions of social media users. AI helps analyze voluminous data to identify trending topics, hashtags and patterns to understand user behavior.

AI algorithms can monitor millions of unstructured user comments to understand crisis situations or trends to provide a personalized experience. With effective segmentation, AI can help provide content based on online activity and demographics. Many social networking sites have acquired AI businesses to move to the next level.

A variety of companies that offer online marketing services are exploring new ways to use social media with AI as well. They have started using AI to identify new demographics to target based on previous conversions. These AI tools rely on predictive analytics algorithms, which can extropolate information on all known users in a given social network.

AI-based Image Recognition

In the era of social media, images are the effective tools to engage people and can help identify consumer behavior patterns. AI-empowered software recognition tools can help gather actionable insights to understand shift in user patterns through millions of images posted on social media.

With the sheer amount of images being posted every minute, it would be very difficult for a person to notice an opportunity like this today on social media without the help of AI.

The year 2018 will witness AI becoming intelligent enough to recognize different promotional opportunities across different platforms and potential marketing opportunities to present insights in an accurate manner.

Evolution of Chatbots

AI is allowing businesses to build a highly personalized and intuitive user experience through tools such as chatbots and virtual assistants. Chatbots are becoming increasingly sophisticated, making interactions between users and brands seamless. With the help Facebook Messenger, users can easily hail an Uber with a chatbot in the app. The initiative lets users to book cab rides by starting a conversation with the chatbot. While chatbots will not make human interference entirely obsolete in social media, it will definitely help AI facilitate social media requests.

Influencer Marketing and Artificial Intelligence

AI-powered influencer marketing will be able to predict what incentive to offer an influencer to encourage them to take a certain action as well as predict influencer performance based on a brand’s objective—including the level of engagement on social media posts and conversions.

Future of Artificial Intelligence

Several social networking giants such as Facebook, LinkedIn and Twitter have started using artificial intelligence techniques to enhance deep learning capabilities. The use of artificial intelligence has helped drive innovation in several connected fields. AI is quickly transforming the way social big data is used for insights.

Startups are experimenting with Artificial Intelligence, and technology giants are investing heavily in Artificial Intelligence as well as acquiring AI companies to enhance their portfolio of products and services.

Facebook

With more than two billion monthly users, Facebook is using artificial intelligence to flag posts automatically that show expressions of suicidal thoughts for human moderators to review. Facebook has enhanced its program to allow human moderators to review 20 times more suicidal posts, and Facebook is sending its suicide prevention materials to twice as many people. Although in nascent stage, the company is deploying updated systems in different languages to improve suicide prevention on Instagram.

LinkedIn

LinkedIn uses Machine learning and Artificial Intelligence for almost all its products. With almost seven million open candidates, LinkedIn offers biggest pool of candidates for a recruiter to contact and connect with highest response rate. LinkedIn uses algorithms with the capability to predict users who are possibly the best fit for the role. Using AI algorithms, LinkedIn can highlight candidates who are most likely to respond or seeking new opportunities.

LinkedIn drastically changed its job-matching algorithms to improve performance. To be precise, it leads users to two million more (job) applications than before.

Twitter

Twitter recently launched an update to its service using Artificial Intelligence that crops an image using face detection or creating a thumbnail from an entire image. With neural networks, Twitter can decipher which part of the image user would be interested in. The neural crop system is applicable for faces where the crop could cut out faces in portrait shots, whereas the AI-based image recognizes important part of faces and puts that in the preview.

Artificial intelligence in social media is gaining prominence. While AI can never replace human interaction between brands and customers, it is helping create a bond. It is now up to marketers to create conversions and reach out to maximum social media users with AI.