Open banking allows banks to share client data with FinTech companies via secure APIs. Reports estimate that 63.8 million people will use open banking by 2024. Banks might share sensitive financial information with other institutions.

1. The Latest Technology Used by Fintech
Industry
Innovation and technological progress are the two pillars of fintech development.
They will continue to drive disruptive business models for financial services.
These technologies will be key to the future of business models and the financial
industry’s competitive landscape in the next ten years.
Technology trends: Open Banking
Open banking allows banks to share client data with FinTech companies via
secure APIs. Reports estimate that 63.8 million people will use open banking by
2024. Banks might share sensitive financial information with other institutions.
Banks can share their financial data to remain competitive, offer security and
transparency, and provide personalized finance management.

2. Open banking benefits are not only for the users but also for financial institutions.
Finance lenders can obtain information about the risks associated with lending to
clients and tailor the loan interest rates to each client’s needs. FinTech companies
can offer open banking to their customers, allowing them to send, receive and
save money from their bank accounts. A single application can enable users to
access multiple bank accounts.
Buy Now, Pay Later (BNPL)
Business Insider reports that BNPL is one of the fastest-growing trends by Fintech
App Development company. Customers can defer payment through BNPL for
goods or services purchased online or in-store
According to the report, the global BNPL market is expected to grow from $24
Billion in 2020 to $67 Billion by 2025.
BNPL is gaining popularity because of a variety of
reasons.
Customers can use it to manage their finances simply. It can help businesses
increase their sales and customer loyalty. Third, BNPL companies may offer
attractive interest rates or payment terms.
Blockchain
Digital Ledger Technology, also known as “Blockchain,” is a similar ledger to any
other. However, it is digital, immutable, and can chronologically record all
transactions made in real-time. This new technology, which brings transparency,

3. efficiency, and security to banking transactions, is still in its infancy. Blockchain is
a decentralized network, which means no one in the system can trust or know
anyone. This allows for fraud protection.
Blockchain stores transaction information in “blocks” linked to each other. This
creates chains that can be accessed from a timeline that cannot change or
altered. Peer–to–Peer lending is one of the most rapid adopters of blockchain.
This ensures efficiency and transparency. Blockchain isn’t just about safety. It can
also reduce costs by eliminating the need to use intermediaries. This technology is
transforming the banking and payments industry in India. Nearly 56 percent of
Indian companies are now using it.
Massive value creation will be possible with artificial
intelligence
Artificial intelligence (AI) can add up to $1 trillion annually to the global banking
sector. As a result, banks and other financial institutions will adopt an AI-first
mindset to better prepare themselves to resist technology firms expanding onto
their territory.
Automatic factor discovery in financial services will increase. This is the machine-
based identification and classification of elements that drive out performance.
It will help to improve financial modeling across the sector.
Knowledge graphs and graph computing, key applications of AI semantic
representation, will play an even more significant role. In the coming years, their
ability to identify patterns and build associations across complex financial
networks using disparate data sources will have profound implications.

4. Analytics that include enhanced privacy protections will encourage minimal data
usage.
For example, only the most relevant, necessary, and appropriately sanitized
information is used in financial model training. Federated learning is a type of
decentralized machine learning that reduces the privacy risk associated with
centralizing data by connecting the computational power to the data and not vice
versa.
Advanced encryption, secure multiparty computing, zero-knowledge proofs, and
other privacy-aware data analytics tools will create a new frontier in consumer
protection.
People will use AI applications to penetrate all aspects of the financial industry,
from front to back, middle and back offices.
Customers-facing applications include customized products, personal user
experience, analytics services, intelligent service bots, and chat interfaces. Some
examples are market trackers, automated transactions, robo-advisors, and
market trackers. Other credit ratings can also be based on financial data.
Facial recognition authentication is another option. Some middle-and-back-office
applications include intelligent processes, enhanced knowledge representation
tools (epitomized with knowledge graphs), and natural language processing to
detect fraud.

5. Many financial institutions still only use AI in a scattered and sporadic manner.
They often limit their use to specific verticals or use cases. Bank industry leaders
are changing their ways by deploying AI throughout their entire digital operation
lifecycle. The financial industry recognizes that algorithms are only as good as the
data they use.
The focus is now on gaining a competitive advantage through previously
untapped customer behavior data collected via traditional operations. This will
allow ecosystem-based financing to unlock its potential. In this model, banks,
insurers, and other financial service firms work with non-financial partners to
provide seamless customer experiences in areas beyond their traditional remit.
Banks will be more efficient if they are “AI-first.” This is achieved by automating
manual tasks to an extreme level (a “zero operations” mindset) and replacing or
augmenting human decisions with advanced diagnostics. The broad application of
cutting-edge and traditional AI technologies, such as facial recognition and
machine learning, will result in improved operational performance.
This includes the (near-) real-time analysis and interpretation of large, complex
customer data sets. The future “AI-first banks” will be able to adopt the same
speed and agility as digital native companies and users.
They will be able to innovate quickly, releasing new features in days or weeks
rather than months and years. Non-bank partners will be a part of the bank’s
collaboration to provide unique value propositions that can be integrated across
all journeys, technology platforms, data sets, and other areas.

6. Just Visit for Mobile App Development Company UAE
Voice Payments
Reports predict that voice assistants will surpass humans by 2025 (8.4 billion),
according to some reports. Connected devices have been popular for people who
want to use them for everyday activities like searching for information, listening,
and shopping online. Voice biometrics can provide reliable protection for the
user’s data.
App users can check their account balance and make payments using voice
biometrics. Voice technologies will replace manual data entry, making financial
services more accessible, especially for those with disabilities.
Conclusion
The inevitable changes due to the rapid growth of technology and the ever-
changing needs of the financial markets make Fintech more relevant each year.
Companies’ success is determined by how these trends are integrated into their
businesses. Combining RegTech with Artificial Intelligence, and Internet of Things,
and Machine Learning with Blockchain and Conversational Banking will be a key
part of attracting customers to financial institutions and improving efficiency.
Banks do not have to be proficient in these technologies at once. This would
require huge investments and technical expertise. Get yourself help by any mobile
app development company and can see the desired results if they implement
several of these innovations in their daily operations.

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