Go to the list of all blogs
Sergey Savastiouk's Avatar
published in Blogs
Apr 02, 2023
How Artificial Intelligence Can Improve Fintech

How Artificial Intelligence Can Improve Fintech

The inherent compatibility between Artificial Intelligence (AI) and fintech has become increasingly apparent as both sectors have matured. Recent growth and successes have brought new ideas about how these two can work together. AI has the ability to analyze information at far greater quantities and speed than any human, making it a natural fit to help fintech firms streamline and automate processes to benefit customers and businesses alike.

Fintech has brought a revolution of convenience to the finance world, allowing for seamless payments and providing tools for online banking. However, this technology also opens up opportunities for costly fraud. AI offers a way for fintech companies to develop stronger security protocols by analyzing the reams of data they collect. By using insights generated by AI, fintech firms can build powerful tools to protect against potential threats. The result is smarter tools with more accurate decision-making, leading to less fraud.

AI also presents the opportunity to further automate customer interactions. Chatbots, if trained properly, can perform useful functions 24/7, offering financial advice, carrying out transactions, and helping customers select a plan or service based on the information they provide. This AI-driven tool creates a positive customer experience, decreases labor costs for companies, and minimizes or eliminates human error.

Intelligent process automation, an outgrowth of robotic process automation, is an especially intriguing option for further growth. This technology can analyze and glean insight from structured and unstructured data, allowing it to continue learning and refining its processes with each piece of new data. The AI can make decisions based on that information, growing more and more accurate over time. This allows for further automation of numerous tasks at high speeds and with minimal error.

Fintech companies have harnessed the power of technology to change the financial landscape. AI gives them an additional tool to streamline and automate processes with unprecedented speed and accuracy, improve the customer experience, and increase revenue opportunities. It's clear that this partnership is here to stay.

Are You Wondering When A.I. Will Start Making Market Predictions?

Well, wonder no more. Artificial Intelligence is already making waves in the investment world. Hedge funds and large institutional investors have been utilizing A.I. to analyze vast amounts of data and uncover potential investment opportunities. By examining charts and identifying patterns and trends, A.I. can scan numerous individual securities and cryptocurrencies to generate trade ideas based on its findings. Until recently, the use of A.I. has given hedge funds a significant edge over retail investors.

But now, Tickeron has launched a cutting-edge investment platform that gives retail investors access to sophisticated A.I. capabilities. With Tickeron, investors can now:

  • Find stock patterns and trends in the market
  • Test and diversify their portfolios
  • Back-test statistics to analyze the results of different stock patterns
  • Predict future price movements with A.I. Rank and a confidence level in the trade

And much more. No longer is A.I. just the domain of the biggest hedge funds in the world. Everyday investors can now tap into the power of A.I. by visiting Tickeron.com. Learn how to make the most of this innovative technology today.


Contributor

Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.


AI Screener 4
Interact to see
Advertisement
AtlasClear Holdings (ATCH) shares fell roughly 25.5% over the last 30 days, declining from $0.1881 on October 2 to $0.1401 on October 30. The pullback extended a longer downtrend that has kept the stock trading well below the $1.00 NYSE American minimum, keeping continued listing-compliance risk in focus.
The central target of $1,620 is the arithmetic mean of verified, current analyst price targets, rounded to a clean level; it is not a single firm's forecast or a guarantee. At a recent price of about $690 , reaching $1,620 would require a gain of roughly 135% , a very large move by any standard.
NVDA fell -2.10% to $216.66 during regular trading, down from a prior close of $221.30. Primary catalyst: hotter-than-expected September CPI data reignited Fed rate-hike fears, raising borrowing costs for AI infrastructure buildouts.
XRPN fell -9.70% in early regular-session trading on Tuesday, sliding from Monday's $10.41 close to $9.40. The decline follows a November 9 SEC prospectus disclosing a committed equity facility with Cantor to sell up to 5.2 million new Class A shares at 97% of the volume-weighted average price, implying up to roughly 16.7% potential dilution.
The $1.14 central target is not an analyst consensus; it is the all-cash merger consideration in GoPro, Inc. (GPRO) 's pending deal with Starman Optical, agreed in September 2026. With the stock trading near $0.88, reaching $1.14 would require a move of roughly 29.5%.
How Artificial Intelligence Can Improve Fintech