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What is Fin-Tech?

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The Investopedia Definition

[By staff reporters]

Fintech is a portmanteau of financial technology that describes an emerging financial services sector in the 21st century.

Originally, the term applied to technology applied to the back-end of established consumer and trade financial institutions. Since the end of the first decade of the 21st century, the term has expanded to include any technological innovation in the financial sector, including innovations in financial literacy and education, retail banking, investment and even crypto-currencies like bitcoin.

BREAKING DOWN ‘Fintech’

The term financial technology can apply to any innovation in how people transact business, from the invention of money to double-entry bookkeeping. Since the internet revolution and the mobile internet revolution, however, financial technology has grown explosively, and fintech, which originally referred to computer technology applied to the back office of banks or trading firms, now describes a broad variety of technological interventions into personal and commercial finance.

Fintech’s Expanding Horizons

Already technological innovation has up-ended 20th century ways of trading and banking. The mobile-only stock trading app Robinhood charges no fees for trades, and peer-to-peer lending sites like Prosper and Lending Club promise to reduce rates by opening up competition for loans to broad market forces. Technologies being designed that should reach fruition by 2020 include mobile banking, mobile trading on commodities exchanges, digital wallets (like Apple (AAPL) and Google’s (GOOG) developing mobile wallet systems), financial advisory and robo-advisor sites like LearnVest and Betterment, and all-in-one money management tools like Mint and Level.

***

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***

New Tech in Fintech

In the olden days, individuals and institutions used the invisible hand of the market – represented by the signaling function of price – to make financial decisions. New technologies, like machine learning, predictive behavioral analytics and data-driven marketing, will take the guess work and hocus pocus out of financial decisions. “Learning” apps will not only learn the habits of users, often hidden to themselves, but will engage users in learning games to make their automatic, unconscious spending and saving decisions better. On the back end, improved data analytics will help institutional clients further refine their investment decisions and open new opportunities for financial innovation.

Fintech Users

Who uses fintech? There are four broad categories: 1) B2B for banks and 2) their business clients; and 3) B2C for small businesses and 4) consumers. Trends toward mobile banking, increased information, data and more accurate analytics and decentralization of access will create opportunities for all four groups to interact in heretofore unprecedented ways.

Conclusion

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Speaker: If you need a moderator or speaker for an upcoming event, Dr. David E. Marcinko; MBA – Publisher-in-Chief of the Medical Executive-Post – is available for seminar or speaking engagements. Contact: MarcinkoAdvisors@msn.com

OUR OTHER PRINT BOOKS AND RELATED INFORMATION SOURCES:

Risk Management, Liability Insurance, and Asset Protection Strategies for Doctors and Advisors: Best Practices from Leading Consultants and Certified Medical Planners™8Comprehensive Financial Planning Strategies for Doctors and Advisors: Best Practices from Leading Consultants and Certified Medical Planners™

***

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3 Responses

  1. Bitcoin Fin-Tech Update

    New York’s bitcoin hub dreams fade with licensing backlog.

    http://www.msn.com/en-us/money/markets/new-yorks-bitcoin-hub-dreams-fade-with-licensing-backlog/ar-AAjD0hA?li=BBnb7Kz&ocid=U348DHP

    Petros

    Like

  2. AI

    Thank you for reaching out regarding our Wall Street Artificial Intelligence.

    We have spent 20 years building the most advanced AI on the street. While others (Ray Dalio and Steve Cohen) are only recently starting to employ AI techniques, we have been “training” our algorithms on individual stocks since 1998. Using a combination of IBM Deep Blue and IBM Watson, our 5 datacenter supercomputer has spent 24 hours per day, 7 days per week, for 18 years straight “learning” what key factors, catalysts and events drive individual stocks up and down. The result is 11 categories of strategies and 16 prioritizing and ranking filters that are generating significantly higher returns than even the best hedge funds. We have been tracked for the last 10 years and won the Marketocracy Gold Medal award for beating all other money managers in the 10 year time frame.

    We would like to demonstrate the technology to you by sending you our predictive research for 30 days. Each report is worth $15,000 and we will send you 10 per day for 20 trading days. That is $3 million worth of free research. Put the trades on for yourself and your clients. You will make money and so will they. Once you are convinced that our AI successfully and consistently predicts the near future (3-6 weeks) on individual stock selections, we will show you how to scale it up and provide the most advanced institutional trading technology to your client base.

    Just send me the email address you would like us to provide the research to starting today. The file sizes exceed 10MB so be sure to check your spam folder in the 1st half hour of trading each day in case our email is there. Good luck and good profits.

    James Goldberg
    [VP / Strategy]
    WOPR

    Like

  3. Robots are working for Sweden’s banking industry

    The only Swedish bank that cut costs last quarter is investing heavily in automation.
    The robots are coming: Casper von Koskull, the CEO of Sweden based Nordea Bank, predicts that the banking industry will slice its workforce in half over the next 10 years. Last year, Koskull announced the company would cut 6,000 jobs in favor of automation. So far, it has cut employee numbers by 2,500. Roles cut include asset management and customer service.

    The results: That’s been enough for Nordea to see huge monetary benefits so far. According to second quarter results, the bank cut costs 11 percent year over year, and increased profits by 31 percent, which made Nordea the top performer among Sweden’s major banks.

    Why it matters: Nordea’s experiment is motivating other regional banks to automate more quickly. The company’s proof of concept could speed up the adoption of AI and automation in banking and, if success continues, serve as a benchmark in the finance industry.

    https://www.bloomberg.com/news/articles/2017-10-26/nordea-ceo-defends-shocking-job-cuts-as-bank-analysts-complain

    Dr. David E. Marcinko MBA

    Like

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