Top 6 Ways Artificial Intelligence will Impact the finance industry

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The adoption of AI application in various verticals has already proven their substance. It is not surprising that even the finance industry is revamping their traditional model and deploying artificial intelligence for better infrastructure. Here are the recent statistics


AI in FinTech is creating a significant impact, let us have a look at how

1. Personalized services:

AI has the power to add a personal touch to all the consumer interactions with the help of AI-backed chatbots and other machine learning tools. AI services help financial companies to provide customers with a financial concierge that is modeled keeping in mind the customer’s spending patterns and goals. So, a customer will have a detailed review on how much he should spend, save and invest based on the available insights.  With AI the financial companies can learn what is working for them and what is not and keep track of their financial activities better. 

2. Reduction in costs: 

The advent of AI has automated several processes that have drastically reduced costs in several sectors. One of these sectors is the customer service department where the automated process has replaced the manual workforce. While, on the one hand, AI application is reducing the costs on the other it is providing comfortable and efficient financial channels which are super easy to avail. Because of ease of the processes, the financial sector is now attracting more consumers who were previously intimidated by the cumbersome financial processes. 

3. Advanced decision making: 

Artificial intelligence works on a wide variety of data sets that are collected from various sources and ingested into it. It is capable of processing this data accurately and provide insights that are data-driven and have a real logic base. The financial experts can seek advice and recommendation from these systems for making accurate forecasts. Consumers can also get their financial portfolio managed without any management fee as opposed to availing services from a traditional advisor who might charge a handsome percentage of your investment. 

4. Fraud detection: 

The digital landscape make things easy but it also comes with a set of challenges and one of it is cybercrime and thefts. All online processes that involve money transaction and private details need to be secured to build the trust of the consumer. AI can help to make the environment safe and breach-proof. Unlike the traditional models where the breach is reported when the crime has already taken place, AI can be used to pre-empt a fraud through the continuous monitoring and understanding of the data patterns based on human psychology. 

5. Reduce human errors:

The automation of processes and dependency on machine tools can help to make an efficient decision that is not prone to errors. AI in finance is implied through thorough research and understanding of the available data collected over extended periods of time. This data helps to develop full-proof solutions.  AI introduces automation in the field that requires extreme incisiveness thus safeguarding the trust of customers.  

6. Predictive modeling:

AI is used to process large volumes of data and extract actionable information around it. As the data is increasing each passing day, the systems need to be more efficient to be able to process this extensive amounts of data. AI helps with the fast processing of the data that gets collected from various sources such as social media channels, online transaction, emails and many more. These details help with insight generation and creating market strategies for the future. 

AI in finance is all about flexibility and improvement of the existing systems. An AI system can be continuously improved and overhauled through continuous learning and re-learning of the data patterns. With time AI will become an unavoidable part of the finance industry and will get better with time. 

AI companies are also playing hard to keep up with the growing demands of various industries. AI has a lot to it, and it will take several years to unravel the full potential of AI and machine learning.

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