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Tag: machine learning in fintech

The future and applications of machine learning in Fintech

Posted on by Imarticus

Fintech as an evolving discipline, has been majorly facilitating banking industries. However, to perform more accurately, banking institutions are now inclined towards utilising Machine Learning algorithms to use. This will help in optimising money circulations regulated with ML-bSed credit scoring.  

Incorporating Machine Learning enhances the workflow, customer services and ways of conducting business. Using Machine learning in Fintech helps in opening new opportunities by expelling any kind of outdated techniques and setting the way for a confident future. 

 

Here, we will discuss the benefits of incorporating Machine Learning in Fintech and how it will be beneficial in future developments. 

Significance of Machine Learning in Fintech

Both Machine Learning and Fintech are evolving disciplines that are helping to shape the technology. Combining these two principles help in creating better technology. Here, we have pointed out some significance of Machine Learning in Fintech and how it will shape our future. 

  • Forecasting Financial Trends

Fintech companies can use ML algorithms to analyse market risks, identify future financial opportunities and reduce fraudulent activities. Companies often train their ML models on massive amounts of data to improve financial interactions, loan repayments, interactions with customers and of course, safeguarding the company stocks. The Machine Learning algorithms act as a warning system predicting any kind of risks or financial anomalies. 

  • Trading Algorithms

Algorithm trading generally involves the execution of different trading orders by keeping in mind the pre-programmed tradings already in existence with trading instructions. These trading instructions are created using ML algorithms conjugating with financial formulae. There are no preconceived notions present in this automatic algorithm trading. Algorithm trading poses several advantages. Since it is automatic it keeps in mind the changing market variables which are important to keep up with the market trends. 

  • Advanced Customer Support 

Machine Learning plays a vital role in providing customer support to their clients. It helps to answer the basic questions without making the customers wait at all. Machine Learning has created chatbots that have facilitated providing customers with ultimate support and solutions to their problems. This saves time for the Fintech companies as their agents do not have to engage with customers in solving basic problems. 

  • Outsmarting Thieves and Hackers

Fraudulent activities are one of the major concerns in the Fintech sector. Incorporating ML algorithms would reduce the risks of hacking data. ML algorithms help in evaluating huge data sets of simultaneous transactions in real life. By running ML algorithms the systems would be able to identify activities that might look suspicious. 

Comparison between Rule-based Fraud Detection and Machine Learning-based Fraud Detection

Before the concept of ML algorithm-based algorithm to detect fraudulence in Fintech companies, rule-based fraud detection was in use. Here, we have listed down a comparison for you to understand the need for Machine Learning in Fintech and how it has improved the conditions of a company. 

Rule-based Fraud Detection  Machine Learning-based Fraud Detection 
  • Catches obvious fraudulent activities. 
  • Catches the hidden and implicit data correlations. 
  • It requires manual work that is extremely time-consuming. 
  • Automatically detects fraudulent scenarios. 
  • Incorporates multiple verification steps harming the user experience. 
  • This reduces the number of verification measures. 
  • Processing takes a longer period. 
  • Real-time processing. 

What Is Machine Learning Importance in Fintech Companies? 

Machine Learning plays an important role in performing different regulations of the Fintech companies. They are helping to shape the future and reducing human contact thus improving accuracy. Here, we have listed down the importance of Machine Learning in Fintech companies that makes them one of a kind. 

  • Machine Learning helps in improving customer experiences and provides optimal financial performance analysis. 
  • Machine Learning plays an important role in providing better market opportunities by identifying hidden insights. 
  • Reduces the cost of process optimisation and human efforts altogether. 
  • Helps in delivering constant support with the help of incorporating chatbots and RPA. 
  • Ensures optimal decision-making by the companies to make the best financial decisions with the usage of data. 

The Future of Machine Learning in Fintech

Machine Learning possesses amicable qualities to displace human interaction for better decision-making. Machine Learning also aims to improve internal organisational processes as well. Fintech will be much more advanced once the qualities of Machine Learning are incorporated into the companies. The Fintech companies are bound to gain profit and have upfront information for any future risks. 

Conclusion 

Incorporation of Machine Learning in the Fintech industry is one of the best decisions taken. However, there needs to be a proper training program for future aspirants to have a budding career in the Fintech industry. Imarticus Learning’s online MBA in Fintech training program in association with KL University will be shaping the future of many aspirants. This is a 2-year program and guarantees 100% placement. The incorporation of Harvard case methodology for understanding the concepts of Machine Learning in Fintech is top-notch. If you want to enrol in this program and learn Fintech at ease, check out the website right away!

The growing importance of Machine Learning in Fintech in 2023

Posted on by Imarticus

Machine learning in the fintech sector is gaining popularity. And, if your career goal is to become a fintech expert, then you must be aware of what machine learning is and how it’s affecting the sector. Most financial institutions today are in favour of investing in machine learning and consider the two an ideal match. Did you know that a Forbes survey has found that as high as 70% of financial institutions use machine learning these days to detect fraudulent incidents or adjust credit scores? If you’re interested, then jump into this article that is all about the importance of machine learning in fintech and get a clear understanding of the field. Read on to find more.

Machine Learning: What is it? 

In layman’s terms, machine learning is a field which explores the capacity of a machine to mimic the intelligence of humans without any specific programming. It is based on statistical techniques which are used for building intelligent computer networks. It is most commonly used in the detection of fraud, filtering spam, detecting malware threats, etc.

Is Machine Learning The Same as Artificial Intelligence?

Although the two might sound similar, they are not the same. There is a thin line of difference because machine learning falls within artificial intelligence, it is the subset of the latter. While AI or artificial intelligence helps a machine to replicate human behaviour, machine learning aids a computer system to learn automatically from previous data sets without any need for explicit programming.  

How to Pair Fintech With Machine Learning?

The fintech sector is associated with a vast customer base with an ocean of data, which is related to the fluctuations in the market and along with it the sector also faces continuous threats of illegal activity. Tracking down such a massive threat manually is next to impossible, and this is where machine learning comes in as a saviour. It mostly involves the identification of patterns, which it can identify from a vast number of sequences in only a matter of seconds. Machine learning is also equipped with pattern prediction, which helps most businesses to explore new opportunities and find out the most suitable strategies.

What Are The Benefits of Coupling Machine Learning And Fintech?

Smart solutions have long invaded the fintech market and the following are their benefits:

  • Greater cost efficiency, because with automated processes, staff requirement automatically becomes less
  • Greater customer engagement with more personalised choices and options. This makes sure customers feel more involved in the offered products
  • Against manual search for illegal activities in any financial institution, machine learning works in a jiffy. Thus, the coupling offers greater time management
  • Machine learning algorithms help financial institutions in better risk assessment before the institutions can guarantee any payback in case of losses 

What Are The Uses of Machine Learning in Fintech? 

Given below are the top uses of machine learning in the fintech sector:

Algorithmic trading

This strategy of machine learning is used by many financial institutions for decision making and increasing their trade volume. For instance, the company 8topuz makes use of machine learning to help its investors boom their wealth.

Fraud detection

As mentioned earlier, machine learning helps in fraud detection with its feature of finding patterns from an array of data sets in a matter of seconds. For instance, renowned company Capgemini has claimed that with the help of machine learning, the time required for fraud detection went down by 70%. 

Enhanced customer service

In terms of finance, it is the accuracy and transparency of the institution which are highly valued by any customer. Machine learning is equipped with features like analysing customer data and predicting on the basis of analysed data. For instance, Wells Fargo launched a machine learning-driven customer chatbot service for Facebook Messenger. 

Why Should I Learn About Fintech And Machine Learning? 

Is your goal to be a financial expert? Then you must already be aware of the growing importance of machine learning in this field. However, simply having the knowledge doesn’t suffice and you need to have a relevant academic degree to prove your worth to your potential employers. You can opt for a postgraduate diploma after graduation, such as the postgraduate diploma in management offered by Imarticus in partnership with Birla Institute of Management Technology. 

Bottom Line

Machine learning in the fintech sector is much like a brain that hardly ever gets tired of working. It is always starving for more data that it can process. No doubt the pairing of fintech with machine learning is a new one and it has more to achieve, yet we can already hope that the coupling will offer more refined services in future. Fintech executives with an MBA degree earn handsome salaries in our country. So, hope you’re all set to kickstart your fintech career!

Machine Learning Trends in Fintech

Posted on by Imarticus

Machine Learning Trends in Fintech

Fintech is one of the rising sectors in the Indian economy, and artificial intelligence and machine learning in fintech has played a big part in its rapid growth. The power of automation, along with data science, has enabled companies to help even novice investors to find the right options and helped the experienced ones to further their portfolios. Apart from that, they have reached the masses with rising internet penetration, helping a lot more people than before.

So, let’s look at the trends emerging from fintech in AI and ML.

Trends around artificial intelligence and machine learning in fintech

There are many trends that are rising in the field of fintech. Due to these fields becoming prominent, there has been a complete revolution in finance. The companies are launching new products which are digital and accessible through the cloud. So this has resulted in the customers behaving in new ways. A fine example of this is the UPI (Unified Payments Interface) and other digital payment services. 

Anyway, returning to the issue of rising trends in the field of fintech, they are:    

  • Lending in fintech

This old service has been packaged in such a way that it has adapted to the new times, especially as per the channels of the digital medium. According to the Bank of Baroda, lending in fintech allows the lender to issue loans online through websites or mobile apps. Earlier it was quite traditional, where the mechanism was primarily balanced sheet underwriting. Now it has been leveraged into a digital format. This has helped to ease business processes and make them faster and more secure. 

  • Mobile or digital rupee

This is purportedly the currency of the new age, where a digital medium of exchange is connected to your digital wallets or bank accounts. It is highly helpful in sending money all throughout the world within a matter of seconds. The best thing is that it helps to skip the channels and tax ports in between, making the transactions less expensive than the conventional ones. Due to its brisk transactional speed, it has become quite popular among people, and it is one of the biggest attention grabbers for the fintech sector.   

  • Online investing platforms

Corporate leadership
Although online investment platforms are the biggest draw of the Fintech sector, it is quite cumbersome. They are offered as a platter or combination of allied services. Nowadays, almost all traditional investment services are available online. For example, most platforms these days offer stock trading options, gold loans, gold purchases, mutual funds and other investment options through fintech apps. You will find multiple services under one roof. This sector uses the assistance of advanced technology to find the right products for an individual customer, and it is one of the biggest trends of machine learning in fintech.

  • Stock price prediction

This is another trend in fintech that heavily uses technology and is dependent on AI and ML. It is required by most stock marketing companies and investment brokers who need to guide their customers about building the best possible portfolio which yields them the most traffic.   

  • Sales forecasting

Machine learning algorithms help ecommerce companies to predict how much sales they will be able to make during the present fiscal year. They train the machine learning models to observe data and give better insights by calculating the demand and the supply, helping them to predict how much selling could be done and how it could be optimised towards a particular target. 

  • Cryptocurrency

It used to be a fintech star at one point in time, and it heavily employed machine learning to secure investors’ digital transactions. Even if the cryptocurrency market is seeing a slump in present times, it is still trending worldwide. In the future, it might transform, but it will still use a lot of AI and ML to provide a bigger and very different investment option for investors.   

  • Blockchain and applications related to it

Blockchain is the talk of the town even years after its launch, and it has become a buzzword because of the fact it finds its application in almost every operation of the fintech business. Today, it has become the backbone of the fintech industry and has helped to make this sector more secure.

The introduction of machine learning in fintech has shaped the industry and made it future-ready, and it has also played a significant role in its transformation. Today, fintech is a growing sector with more promising years ahead.

If your interest has been sparked towards fintech, then you should also opt for the right training. In this regard, an MBA in fintech sounds like the right option. Imarticus Learning, in partnership with KL University, runs the MBA course that includes an updated curriculum, training from industry veterans, placement assistance and a host of other facilities to ensure that you have the best career ahead.