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10 Ways AI Is Going To Improve Fintech In 2020

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Bottom Line: AI & machine learning will improve Fintech in 2020 by increasing the accuracy and personalization of payment, lending, and insurance services while also helping to discover new borrower pools. Zest.ai's 2020 Predictions For AI In Credit And Lending captures the gradual improvements I've also been seeing across Fintech, especially at the tech stack level. Fintech startups, enterprise software providers, and the investors backing them believe cloud-based payments, lending, and insurance apps are must-haves to drive future growth. Combined with Internet & public cloud infrastructure and mobile apps, Fintech is evolving into a fourth platform that provides embedded financial services to any business needing to subscribe to them, as Matt Harris of Bain Capital Ventures writes in Fintech: The Fourth Platform - Part Two. Embedded Fintech has the potential to deliver $3.6 trillion in market value, according to Bain's estimates, surpassing the $3 trillion in value created by cloud and mobile platforms.


Importance of Artificial Intelligence in making lending easier and profitable - CIOL

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Over the year, evolution in global technologies has made people move forward from fixed phones to mobile phones. Today, every sector is readily and rapidly adapting the Artificial Intelligence (AI). With the fast-paced modern industries, AI is becoming an integral part of business operations. AI is not limited trend-based forecasting in marketing but its presence is getting indispensable in every vertical of the company. AI is much more efficient in analysing data patterns, based on these patterns companies acquire in-depth knowledge about their potential customers, their requirements and their behaviour.


Ai bankability: 10 ways artificial intelligence is transforming banking

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With plenty of post-recession anti-banking sentiment still lingering, it's common to see fintech and traditional banks framed in oppositional terms. There's some truth to that, especially with disruption-minded digital-only banks, but technological innovations have transformed banking of all stripes -- and nowhere is that clearer than with artificial intelligence. AI has impacted every banking "office" -- front, middle and back. That means even if you know nothing about the way your financial institution uses, say, complex machine learning to fend off money launderers or sift through mountains of data for fraud-related anomalies, you've probably at least interacted with its customer service chatbot, which runs on AI. Read on to learn how else AI is transforming the way banks operate, from investment assistance and consumer lending to credit scoring, smart contracts and more.


Where is this online lender using AI? Everywhere

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The online lender Enova, which has been using artificial intelligence to make credit decisions for years, has lately been expanding its use of AI to handle additional tasks: spotting fraud, determining who should receive product offers, and projecting possible losses once a loan is booked. Most recently, it has also been been having AI scour paper documents to uncover false information, verify income and employment, and conduct know-your-customer checks. It also sponsored a survey, conducted by Harvard Business Review and set to be released Thursday, that benchmarks how businesses are using AI. Generally speaking, it finds companies are adopting AI slowly: though 68% of executives say AI will be a competitive differentiator within the next year and 64% are investigating or piloting AI projects, only 15% of organizations have AI-powered analytics in place due to technical and cultural challenges. In its back office, Enova has been training AI engines to review documents such as bank statements and pay stubs and automating decisions based on the information in those documents.


The Politics of Artificial Intelligence in Financial Markets

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Technology is and has always been a crucial part of finance. From the first promissory notes (banknotes) in the Netherlands and China, there was a race with counterfeiters that parasitically undermined trust. As in political communication, technology is the message, rather than merely "a tool": when it comes to money, trust is not just instrumental, it is fundamental. With cashless payments being the norm and social media platforms weαving an additional layer of involvement in our social data web – Amazon, Google, Facebook, Apple – Artificial Intelligence (AI) is already in our wallets, business, and financial affairs. In a non-western setting, one may refer to the Chinese "social rating" system, which allows the state to value and evaluate social behaviour patterns, creating a link to individual credit rating.


AI bankability: 10 ways artificial intelligence is transforming banking

#artificialintelligence

With plenty of post-recession anti-banking sentiment still lingering, it's common to see fintech and traditional banks framed in oppositional terms. There's some truth to that, especially with disruption-minded digital-only banks, but technological innovations have transformed banking of all stripes -- and nowhere is that clearer than with artificial intelligence. AI has impacted every banking "office" -- front, middle and back. That means even if you know nothing about the way your financial institution uses, say, complex machine learning to fend off money launderers or sift through mountains of data for fraud-related anomalies, you've probably at least interacted with its customer service chatbot, which runs on AI. Read on to learn how else AI is transforming the way banks operate, from investment assistance and consumer lending to credit scoring, smart contracts and more.


AI and the bottom line: 15 examples of artificial intelligence in finance

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Artificial intelligence has given the world of banking and the financial industry as a whole a way to meet the demands of customers who want smarter, more convenient, safer ways to access, spend, save and invest their money. We've put together a rundown of how AI is being used in finance and the companies leading the way. A recent study found 77% of consumers preferred paying with a debit or credit card compared to only 12% who favored cash. But easier payment options isn't the only reason the availability of credit is important to consumers. Having good credit aids in receiving favorable financing options, landing jobs and renting an apartment, to name a few examples.


UBank launches world's first digital home loan adviser - Fintech News

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Last week, Kenneth Hayne QC handed down his royal commission final report that recommended banning banks from paying trail commissions to mortgage brokers from mid-next year. Instead, the borrower will likely be required to pay an upfront fee for the service. UBank, a subsidiary of NAB, doesn't pay mortgage brokers, but its new robot-like home loan aid gives a glimpse into how the service could be provided in the future. Many commentators are speculating only the wealthy will be able to afford a broker, while regular Aussies will have to rely on an automated service. The artificial loan aid, named Mia (My Interactive Assistant) and powered by AI start-up FaceMe, will speak directly to customers through a desktop or smartphone advising on questions such as what's a variable rate to what classifies as an expense, the bank says.


Artificial Intelligence (AI) in FinTech MyTechMag

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One of the early adopters of relational databases and mainframe computers have been the financial firms who have been a pioneer at adopting the latest in technology. Artificial Intelligence (AI) has taken the FinTech industry by storm which has been assisting financial institutions in solving redundant issues and increased operational efficiency. In the last two decades, FinTech companies have revolutionized themselves by adopting technologies like AI, Machine Learning, Neural Networks, Big Data Analytics, evolutionary algorithms, to name a few that have allowed computers to crunch and process an immense variety of diverse and deep datasets than ever before. There are a few important areas where AI is impacting in a game-changing manner for the FinTech industry. Importantly, one of the most significant requirement of AI in the FinTech arena would be producing ideas that can precisely predict customer behavior.


Piecing together the puzzle of property prices with peer-to-peer lending data

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Data science provides a venue that exercises the inquisitive mind. The opportunity to investigate new datasets and understand their value for a theory or model never ceases to fascinate and enthrall. That inquisitive nature -- the mission to understand what drives value in the commercial real estate (CRE) market -- runs at the core of what we do here at GeoPhy. It leads to the exploration and analysis of a wide variety of data. This variety and the unprecedented volume of data now available provide two of the conventional "V's" of big data [1], and make this quest both a compelling and complicated one -- like fitting together pieces of a puzzle.