Use Cases of Artificial Intelligence in Fintech


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Artificial Intelligence (AI) has led the way for the inception and growth of the global FinTech industry.

Due to the increasing levels of digital transformation and process automation of financial services, there are various use cases in the finance industry, from personalized financial advice to secured digital transactions. Metaphorically, Fintech and artificial Intelligence are new peanut butter and jelly.

According to McKinsey’s report, The state of AI in 2021, 56% of companies utilize AI in one business function at least. AI technology helps FinTech companies and related institutions to be in touch with customers, improve fraud detection, automate customer support, and simplify decision-making with predictive analysis and data.

Artificial Intelligence has revolutionized the FinTech industry, and its application has a variety of use cases. These use cases show the necessity of AI in the finance Industry.

Then, AI in Fintech Market – Growth, Trends, Covid-19 Impact, And Forecasts (2023 – 2028), by Modor Intelligence, says that the market size for AI in Fintech is expected to reach USD 26.67 billion by 2026. And it will maintain a CAGR of 23.17% till 2026.

In the financial technology sector, AI has significantly improved data security. Many FinTech companies and banks provide various client services using chatbots powered by Artificial Intelligence. These Artificial Models can give several ways to improve security, including resetting lost passwords and allowing many other additional access.

Artificial Intelligence also boosts financial security through facial, speech, and fingerprint identification. It is harder for hackers to exploit this added layer of security than a standard password. Although these processes are still being refined, various Artificial Intelligence powered solutions may eventually replace usernames and passwords.

Cybersecurity becomes increasingly crucial as the world grows more online and less personal. As banks, Fintech, and financial institutions handle billions of dollars daily, they are the most vulnerable. Keeping up with Artificial Intelligence ensures your organization has the best security available.

Top use cases of AI in Fintech

Fraud Detection

Deceptive financial behavior has increased recently, ranging from loan applications to credit card scams to illegal wire transfers and bogus insurance claims. Apart from cash losses, forms must also deal with potential reputational damage and unpleasant customer experiences.

In the banking industry, Much of the AI venture funding is used to target cybersecurity and fraud. Analyzing each transaction for potentially suspicious or erroneous activities is practically impossible, as many financial transactions happen daily.

Efficient AI systems can monitor financial transactions in real-time, and Artificial Intelligence algorithms can discover strange patterns or abnormalities that show a deviation from a user’s daily spending habits. With Artificial Intelligence, Fintech can respond to potentially fraudulent activities more accurately and quickly.

Personalization of Banking Services

If not millions, large financial institutions have thousands of customers. Providing individualized services to countless unique individuals without AI-powered technologies will be a monumental task. Personalization can surly increase brand loyalty and client trust in your firm. Artificial Intelligence systems collect and evaluate customer data when customers download banking apps. Data can be used to propose customized financial advice and relevant pre-approved items. Artificial Intelligence in banking apps can also help customers to track their financial expenses and objectives.

As they are self-learning, Artificial Intelligence systems will only improve at offering personalized experiences and reading client data. Artificial Intelligence models evaluate speech and voice characteristics to generate helpful information and find accurate patterns from monotonous babble. AI transcript analysis can predict customers’ moods and help agents decide what solutions will satisfy them.

Predictive Analytics

The way financial companies make decisions, integrating data science within the process, has been revolutionized by predictive analysis. Artificial Intelligence can help firms analyze a wide array of market and customer data, streamlining the overall management process and business development. All activities – converting revenue in financial services to nurturing leads use predictive analytics.

With predictive analytics based on the individual risk profile of the clients, programmers can develop various algorithms to compute credit scores. They can offer financial services accordingly to decrease the possibility of incurring bad debts later.

Predictive analysis can also be used in branding and marketing campaigns of FinTech firms. For example, FinTech organizations can proactively evaluate the success of a branding strategy in a customer’s mind.

AI-Powered Financial Assistants

The customer support team gets help from AI in Fintech to train automated digital financial assistance for interacting with customers. The saved time can be used for performing more value-adding tasks.

As the automated assistants can use data analytics from external and internal sources, they can also provide a lot of information to the clients that are time-consuming and difficult for humans to learn.

More interestingly, developers also use Natural Language Processing (NLP) for internal processing. This helps the digital assistants learn customers’ facial expressions and emotional states during interactions. As clients do not feel like they are interacting with a programmed bot, it is particularly useful during client onboarding. Thus, customer satisfaction is higher from instant communications powered by speech recognition software.

Also Read: HMBradley has signed onto the Thought Machine platform

Save Resources and Money

Fintech industries can save dollars in billions in labor costs, capital, and resources using various AI-powered solutions. Manual procedures are often more expensive and time-consuming due to labor expenditures. AI automation saves time and money by taking over these duties and activities. As AI technology handles lesser questions, the customer service team will experience a significant drop in staffing costs.

Through personalized insights, AI saves banks money at the front office through anti-money laundering in the middle office and credit underwriting in the back office. Because of the money saved by deploying AI technologies, Banks can offer better deals and attract more clients. Thus, money is saved while profit and income are increased.

The benefits of Artificial Intelligence in Fintech can never be undermined. Artificial Intelligence is helping the FinTech industry and other institutions to grow as a technology-driven powerhouse. The disruptive technology revolution has led many AI FinTech companies and startups. With the constantly changing technology landscape, businesses also need to change. To stay relevant in the market, FinTech software development companies have to incorporate new AI trends in their solutions.

Bineesh Mathew
Bineesh Mathew
Bineesh Mathew is an accomplished senior writer with 10+ years of experience in multiple domains. With a proven track record, he has specialized in writing for business strategies, marketing technologies. Currently, Bineesh is working as a Senior Content Writer with TalkCMO. Bineesh is an English Literature graduate who has mastered the language with excellent editing skills. As a writer, he has contributed exciting writing pieces for various topics such as digital marketing, cybersecurity, and different latest technologies, including Artificial Intelligence, data analytics, machine learning, and much more.


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