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Fintech’s Future: AI and Digital Assets in Financial Institutions

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The banking industry is beginning to embrace AI and digital assets in an effort to put in place cutting-edge detection and to reduce human workload.

This is not your father’s bank. Today’s financial institutions have evolved so much over the past decade that they offer a completely different experience than the old bricks-and-mortar banks did.


To keep up with the pace of business and the security threats in today’s environment, financial institutions were compelled to improve efficiency and develop innovative safeguards to manage risk. Fintech made that possible, and its adoption by users has accelerated tremendously as a result of the pandemic.

The Growth of Fintech

“Fintech is the biggest disruptor of our time for financial institutions,” declared KPMG.

In 2020 the estimated global market for the AI component fintech 7.91 billion USD, on track to hit $26.67 billion by 2026. That’s due to the compounded annual growth rate of 23.17% estimated for the next five years.

“If you look at digital lenders that have manufactured fintech products for at least a decade, they’re doing quite a bit with AI. The idea of underwriting someone’s credit sits very well with an AI approach.” That’s the observation that Lex Sokolin, Global Director of Fintech Strategy and Partner at Autonomous Research made in Cardrates.

What Drives Fintech Adoption

In 2021, Dmitry Dolgorukov, Co-Founder and a CRO of HES FinTech and CEO at GiniMachine estimated that the breakdown of AI and ML for business use cases as follows:

  • 38 percent – Reducing costs

  • 37 percent – Customer insights

  • 34 percent – Customer experience

  • 30 percent – Internal process automation

  • 27 percent – Fraud detection

  • 26 percent – Customer satisfaction

The advanced power of digital automation combined with customer expectations for access and service shaped by their adoption of mobile technology and experience in online platforms is what has pushed even the most conservative of banks to adapt and deliver. Failing to do so gives their competition an advantage that would cost their business. (Read also: Top 12 AI Use Cases: Artificial Intelligence in Fintech.)

Meeting Customer Expectations

KPMG pointed out that over the past decade, customer expectations for financial institutions changed. They now demand the same level of convenience and accessibility they have come to enjoy on the retail front:

”In an era where retail products can be ordered and delivered in the same day, it’s no surprise that people want their financial transactions to also occur in real-time — and for decisions related to their mortgages, insurance coverage or other financial needs to be made in moments rather than days or even weeks.”

Accordingly, we see an increase in online and mobile banking, marketplace lending, new options for digital payments, and automated solutions to expedite processes. One of the uses of AI and ML is applying automation to underwriting to expedite the creditworthiness of applicants for loans and arrive at approval decisions faster.

VCAs (Virtual Customer Assistants)

Scaling up responsiveness to customers with AI has led to offering service via a virtual assistant. Bank of America introduced its version called Erica in 2018. It has grown from 6.3 million users in 2019 to 19.5 million in 2021. Interactions on the app nearly quadrupled in just a year, jumping from 27.8 million to 105.6 million.

Erica would be only one among many, according to the trend identified by Gartner. It anticipates that “70% of customer interactions will involve emerging technologies such as machine learning (ML) applications, chatbots and mobile messaging” by 2022. That represents a significant increase from the mere 15% that was handled through such tech in 2018. (Read also: 6 Trends in Customer Relationship Management.)

Reality may show even higher percentages as digital solutions were more widely adopted by the public due to the pandemic. Digital wallets and mobile payment options were also more widely adopted in 2020 due to the pandemic, breaking the habits of a lifetime for some people within just a few months.

This is good news for banks that have been trying for years to get customers to use automated services to cut costs. They still had to keep the traditional bank services open to accommodate customers who were used to doing things “the old-fashioned way.” However, when many banks closed their physical locations or severely curtailed their hours during the lockdown, people had to adapt.

Robots and Automation

Banks are also already making use of robotic process automation (RPA). Among them is BNY Mellon, which began deploying bots as a way of capitalizing on AI capabilities to reduce costs and improve operational efficiency.

The cost savings are significant. In 2017 Reuters reported that the bank estimated an annual savings of $300,000 as a result of the shift from manual processes done by people to the automation enabled by bots.

That level of savings is just the tip of the iceberg for the industry. An Autonomous NEXT report found that AI could potentially reduce operating costs in the financial industry by 22%. By 2030, it predicts the savings could total $1 trillion. Part of the reason for that growth is the increase in the functionality of robotics in the financial sector.

Dolgorukov explains that “Robo-advisors have seen advancements from online questionnaires to dedicated fund and portfolio management to algorithm-based rebalancing and proposals.”

He predicted that this year, we’ll be seeing “a refinement of systems and more fully-automated, self-learning algorithms to aid investors.”

These AI algorithms are able to take into account a range of personal considerations, including clients’ financial goals, budget and risk tolerance. As they get more sophisticated, these “advisors” are also able to predict market trends and even determine when and how to rebalance portfolios.

ML offers a solution to security that eliminates a lot of tedious tasks to make manual checks with algorithms that will identify patterns of behavior to flag deviations.The combination of predictive analytics and real-time data integration makes it possible to detect financial fraud threats as they happen.

The Role of Blockchain

Blockchain is one of the tools being adopted by fintech to improve security. Its distributed ledger makes it possible to store and transfer assets or equity with the benefit of cryptography for security and transparency for the transactions. Blockchain is what makes a ledger truly immutable because its data cannot be overwritten, altered, or deleted. It also keeps everything traceable and accessible. It also is the technology that underlies cryptocurrency like bitcoin and ethereum, tokenization, and digital assets.

These forms of digital value are expected to rise tremendously over the next few years. According to IBM , “Tokenization alone is expected to be worth USD 24 trillion by 2027, a figure that represents 10 percent of global GDP.” It adds that major names in the financial sector, including, J.P Morgan, Citigroup, Wells Fargo, and PNC, are now “adopting blockchain to enable their infrastructure to support a variety of digital assets”.

In addition to the benefit of security, a blockchain makes it possible to set up smart contracts. Such contracts not only define but “also enforce the agreed-upon obligations automatically” thanks to the code embedded in the blockchain. (Read also: How Blockchain is Changing the Way We Do Business.)


Just as our models for shopping have shifted from traveling into a store to see what they have to search onlinelikely on our phonesto buy what we want, the paradigm shifted for banking. Today’s generation thinks of banking as something that you do online and expects to be able to use their phones for all information and transactions. That’s why today’s financial institutions have no choice but to adopt fintech and adapt to digital demands for payments, services, and security.


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Ariella Brown
Ariella Brown

Ariella Brown has written about technology and marketing, covering everything from analytics to virtual reality since 2010. Before that she earned a PhD in English, taught college level writing and launched and published a magazine in both print and digital format.Now she is a full-time writer, editor, and marketing consultant.Links to her blogs, favorite quotes, and photos can be found here at Write Way Pro. Her portfolio is at