How Fintech App Development Companies have Revolutionized the world with the help of Emerging Techno

We all know global technologies have evolved around the corner of the world. Companies are quickly realizing they will have to change their approach to appeal to this demographic’s unique set of needs and expectations. We have switched from old television to the internet, and today we are gradually adopting AI to understand human behavior in a better way. The term AI was first introduced by John McCarthy in 1956. It involves several aspects ranging from process automation to the actual process of robotics. It has become largely popular in various verticals of the industries.Artificial intelligence has become the leading trend not only affecting the fintech industries and Insurtech industries, but also healthcare, marketing, and business intelligence.

AI makes tasks easier, efficient and low cost while attempting to trigger human behavior. Fintech app development companies are known to use AI in a wide range of services. Digital enterprises use AI for efficient chatbot response systems. Some businesses offer AI as an assistant for asset management and market trends.There are several use cases of AI that are widespread among the industry and we assume that the technology will be further used. According to the report, the AI market in Fintech is projected to grow beyond $7 billion in 2020.While Fintech companies adopt this change quickly, it is up to the banks to rejuvenate themselves in the age of millennials to remain relevant in the industry. They will have to learn new tricks of trades of how Fintech millennials are using AI and Machine learning.Let’s walk through how AI is revolutionizing Fintech industries.

1.   Algorithm Trading – Algorithm isn’t a new trend, but still blooming due to a very effective strategy that many financial companies use to automate their financial decisions and increase trades.Algorithm trading is nothing but the computer algorithm which automatically takes the decision, submits orders and manages those orders once submitted. For past decades, it has gained high popularity and now accounts for most trades that are put through exchanges globally. Furthermore, it has also attributed to the success of some of the world’s best performing hedge funds. Besides, it uses complex formulas, which combined with mathematical models and human oversight, make the decisions related to buying and selling financial securities on the exchange successfully.Innumerable financial companies invest in algorithm practice as the frequency of trade, that is executed by machine learning is impossible to replicate manually.

2.      Better Targeting – Nowadays, millennials value transparency and convenience when dealing with financial services. They mostly demand personalized services at their fingertips. These characteristics are what companies need to keep in mind if they want to maintain their competitive edge in this climate of lightning-fast technological change.  For this purpose, Fintech companies are now focusing to use machine learning-driven robotic advisors to replace the need of human advisors at the working hour.  Robotic advisors not only aim to attract the users but to resolve their queries and eliminate the excessive proceeding cost of financial institutes. The extent of ability and agility that the Robo advisor offers is the answer to how AI is revolutionizing the Fintech industry.

3.     Better Customer Experience – The time has gone where the people used to stand in the queue of banks for their turn. Thanks to technology, now banks and financial institutions are serving their services in digital and real-time. Let’s have a look at an example of how AI can be integrated with customer support and how it becomes one of the most important advantages of machine learning apps which are centered around Fintech:

Chatbots – Because of the increase in usage of chatbots, the banks, and the financial industry are getting most out of AI. Chatbots, the personal assistant is the innovation lately of AI, but they have been used for years in customer support. By using technology like Chatbots, machine learning has evolved the fintech industry in a unique way to solve the customer issue immediately. For instance, Bank of America has introduced Chatbots called Erica to give their customer the entire information about their transaction, account balance and similar information. Chatbots are beneficial for banking because they provide 24*7 customer support, save cost, streamline customer support, increase customer engagement.

Personalized Services – Personalization is a key element to develop customer loyalty and trust towards their business and organization. However, when it comes to financial services, people usually believe in transparency with fintech institutions and mobile apps.Machine learning is good to analyze human behavior and predict what services are being served to their customer or give helpful advice. For instance, Capital One has launched a new program namely – Capital One Second Look Program that can monitor expenses patterns. After analysis in-depth, this program can detect if the customer has been charged twice for the same products and services and notify them about it. Or it can analyze what tips usually customers leave at restaurants and warn them if it is over their budget.

There are many applications which use Machine Learning and AI in Fintech. It is beneficial for millennials as they feel they are given more value and motivate them to stay connected with these financial institutions.

Sentiments Analysis – Sentiments analysis is the application of natural processing language to determine whether the given text message conveys positive, negative or neutral sentiments, it is also called opinion mining. As of now, several finance companies claim to offer sentiment analysis software that could assist financial analysts in different roles for creating reports faster in searching documents for relevant information.

Sentiment analysis in the financial industry makes predictions of possible stock market trends more effective. In the financial industry, sentiments use machine learning or artificial intelligence to analyze financial news from multiple sources and make predictions in seconds. Have you ever wondered how this technology works? Here we explain to you! A sentiment application programmed to classify the information as positive, negative or neutral. For instance, the length of word increases can be defined as positive, while fall and risk defined as negative. Based on this technology makes predictions about financial trends.

4.  Help with Underwriting Services – The underwriting is coming under the risk that might be faced by the individuals or organization that wants to apply for any loan. The role of AI in underwriting is to analyze the true value of the applicants by looking at their data, especially ones related to their personal spending abilities on social media.AI can also make predictions of any underlying loan trends which can influence the finance sector in the upcoming years.5. 

Prediction of any changes in the Stock Market– Nowadays, stock marketing is the first choice among the people to invest their money wisely. As everyone knows, the stock market is regarded as one of the best investment decisions in the 21st century. But if investment in a good stock is worthy, then how can you know which stock is going well to increase and which aren’t?Here AI analyzes the past and real-time data of the companies and predicts which companies going high or which are not in their stock value. Furthermore, it can hunt financial news through different sources to collect data relevant to stock prediction.

Wrapping up – Now you people are aware of how AI is evolving the fintech industries for the millennials user base to get their attention and make them remain invested in the mobile-based financial offering. AI is playing an important role in the fintech industry and is going to show even more potential in the future.AI and Machine learning are two technologies where the future is headed. Companies are looking to capitalize on consumer’s mindsets to have fine-tuned for their approach. Those financial companies which haven’t started automating their services to appease the younger generation’s demand for transparency, interactive users’ interference is about to face the risk of getting extinct. There is so much competition in the market that a better product doesn’t just cut it anymore. Companies must be more consumer-focused and make sure they are building a brand that customers want and can be loyal to.

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