Artificial intelligence in fintech – PayU Blog https://payu.in/blog Mon, 16 May 2022 09:34:09 +0000 en-US hourly 1 https://wordpress.org/?v=6.4.3 https://payu.in/blog/wp-content/uploads/2020/05/favicon_index-1.png Artificial intelligence in fintech – PayU Blog https://payu.in/blog 32 32 How Has AI Entered The FinTech Space And Its Management? https://payu.in/blog/how-has-ai-entered-the-fintech-space-and-its-management/ Sat, 14 May 2022 09:50:00 +0000 https://payu.in/blog/?p=10537 FinTech (financial technology) is a type of technology-enabled innovation for finance. It can include everything from managing financial transactions to detecting fraud. Consumers now have unique ways to handle their...

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FinTech (financial technology) is a type of technology-enabled innovation for finance. It can include everything from managing financial transactions to detecting fraud. Consumers now have unique ways to handle their hard-earned money that was not feasible even a few years back, thanks to the massive surge in financial institutions that have emerged in recent times.

Financial services were one of the first industries to see the potential of the Big Data revolution and the surge of innovation that has accompanied it – including Artificial Intelligence (AI). AI is a powerful technology that has already been used extensively in the financial services industry. It has a lot of potential to make a positive difference if organizations use it with enough caution, wisdom, and care.

FinTech firms are more likely to utilize AI to launch new products and services, whereas incumbents are more likely to improve the existing ones. A growing number of FinTechs are taking a product-oriented perspective to AI implementation, delivering AI-enabled solutions as a service.

For the FinTech industry, AI is offering novel solutions. AI can evaluate enormous amounts of data incrementally over time via machine learning. Artificial intelligence is being utilized to recognize fraudulent activities unusual transactions and overall provide a rise to handling sensitive financial data – all with a lower possibility of privacy risk – by identifying suspect behaviors.

Why Is FinTech Lagging?

Finance, like other sectors, has already undergone several changes as a result of the digital transformation, including information sharing, financial consumer and shareholder engagement, and increased data analytics. 

However, a significant reason is that most institutions are still restricting themselves and operating in minor ways. Some of this may be owing to the regulation established in the sector. Additionally, it will not be easy to change. However, our perceptions and behaviors account for a significant portion of the lag.

Enter into the digital domain and make greater use of the resources available to you. The earlier we conform to how the financial scene has already altered, the quicker we see the results and keep pace with other technologically advanced industries.

The Need For AI in FinTech

In FinTech, AI can assist businesses in achieving their growth goals, an advantage over competing and becoming more accessible to their customers. It can also help them in lowering operational costs and streamlining internal operations. Customers can benefit from this by better managing their finances.

Here are a few instances where FinTech is helpful:

Security & Fraud Detection

FinTech apps provide new and innovative ways for users to digest information, resulting in better financial decision-making. Data analysis through applications becomes simple because of machine learning and visualization tools, translating it into understandable insights.

Offers Better Security

Financial cybercrime will rise as digitalization procedures become more popular worldwide. Thanks to AI, users and businesses can now protect themselves and their credentials.

Algorithms can detect questionable conduct and, even further, alert consumers. Because these technologies can closely and constantly monitor abnormal trends, there is no need to stay attentive 24/7.

Personalized Banking Apps Powered by AI

Many banking applications provide tailored financial guidance to help users meet their financial objectives, monitor their income and expenditure, and more. AI-powered FinTech developments are primarily responsible for this personalization.

Customer Service

The best AI application is bots. ML algorithms have only gradually begun to gain traction, even though they have been here for some while. One can observe the rise of intelligent chatbots that can communicate with consumers and respond to a range of customer queries on a real-time basis.

Asset Management

For a long time, investment funds have depended on complicated algorithms to create reliable forecasts and models. Several asset and wealth management processes have been restructured, and additional services such as the introduction of wealth management tools.

App users may now access their bank statements and conduct important transactions on any of their gadgets. Most significantly, AI and machine learning technologies give users the option of reducing the rate of intermediaries. As a result, asset management cuts expenses by eliminating redundant processes.

AI-powered Payments

Transaction banking is a sector with the ideal conditions for AI to thrive.

In the payment business, artificial intelligence can drastically reduce fraud detection. An AI-powered payment system calculates a risk score based on various parameters. The payment gateway sector can now execute large transactions with greater precision and lower mistake rates thanks to AI.

Use Cases of FinTech Innovation Driven By AI

As per the FinTech 5×5 survey, 67 percent of FinTech organizations believe AI will significantly impact the industry over the next decade. Ignoring a technology transition in the finance industry means depriving your company of the prospects for proper growth and development that AI in FinTech may offer.

ZestFinance has used AI to construct an automation interface that enables FinTech firms to screen potential loans more quickly. The software assesses the risks and provides employees with a rapid image of whether a potential borrower is trustworthy.

Payoneer and Skrill, both online payment providers, use AI to evaluate complex data.

Crest Financial Group uses the DataRobot machine learning platform to study client activity, and create predictions to detect and prevent suspicious transactions.

Privatbank, a prominent Ukrainian bank, employs AI-powered chatbots that utilize Natural Language Processing to address fundamental questions of users and give advice using the bank’s different services.

These solutions have the same purpose – to boost FinTech organizations’ productivity. You can considerably reduce the stress on your human personnel by deploying data analysis automated processes and chatbots.

Conclusion

Because of artificial intelligence in FinTech, companies in the financial services sector have entered a new age of progress and expansion. These technologies are becoming increasingly important in a wide range of processes. This is the right time to leverage the possibilities of machine learning and AI as a driving factor for your FinTech company’s survival and prosperity.

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