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Artificial Intelligence (AI) has become an integral part of the finance industry. AI gives a competitive edge to the industry. It helps in preventing fraudulent transactions. From analysis to monitoring, it helps in reducing the cost of human resource. In this article, we will talk about the impact of AI on fintech services.
Artificial Intelligence (AI) plays a significant important role in verifying the repayment capabilities of borrowers. There are various factors in the economy which affect financial institutions in India, and this brings risks for financial institutions.
Financial institutions like banks and NBFCs generate revenue through lending which involves risk as these financial institutions can not sanction loan to anyone. Therefore such financial institutions provide credit by verifying the creditworthiness of prospective borrowers. The creditworthiness of borrower depends upon the CIBIL score.
There are large numbers of potential buyers in the market who are depriving of loans due to bad credit history, while it doesn’t mean that they are the defaulters. If the financial institutions ignore such type of borrowers, it will affect their business.
In all, we can say that CIBIL score should not be the only way of judging the Creditworthiness of the borrower. To overcome this, a vital role is played by the Artificial Intelligence (AI) for financial institutions. Artificial Intelligence (AI) helps in verifying the re-payment capabilities of the borrower. In the financial sector, the digital credit evaluation system is undoubtedly a twist.
Lending institutions such as banks or NBFCs use credit score before deciding on lending to the borrower. Lenders use different type of model to check the borrower’s transaction history with other financial institutions. The credit score is calculated by such models based on the structured data which is provided by the statistical analysis.
Now, banks & NBFCs are using a more holistic approach in sanctioning loan. They are using data from different sources like social media activity, phone usage, and text message activity to ascertain the repayment capability.
Nowadays there are numerous tools which help in deriving credit score on the basis of various qualitative factors such as consumer behavior and willingness to pay. In this way, lenders can now take a credit decision in a much quicker and accurate way.
There are numerous benefits of Artificial Intelligence (AI) for Financial Institutions; some of them are as follows:
The machine learning has enabled greater access to credit as it has made it easy for the lender to access creditworthiness. While the traditional credit scoring model uses the historical credit information available of the potential borrower, because of which sometimes potentially creditworthy borrower rejected by the lenders. But things have been changed because of Artificial Intelligence (AI), now lenders can take better decision on loan sanctioning by recognizing the potential borrower.
FinTech companies are fulfilling the needs of its clients by sanctioning loan to them who failed to get the loan from the traditional financial institutions such as banks. Artificial Intelligence (AI) has brought a new credit scoring model for lenders.
Artificial Intelligence (AI) has enabled financial institutions to analyze credit score quickly with the help of analyzing massive amounts of data. It involves the low cost of credit risk assessment. The process involves the assessment of non-credit bill payments like payment of cell phone and other utility bills timely.
Machine Learning helps lenders by minimizing risk. Machine learning helps in analyzing the enormous amount of data in the real-time manner. AI helps banks in reducing the credit risk.
It has been proved that artificial intelligence is very compelling in battling financial fraud. In the past few years, we have observed that credit card fraud is growing exponentially due to online transactions which can be prevented by Artificial Intelligence (AI). Now with, fraud detection system borrower’s behavior can be analyzed.
Financial institutions employ AI to prevent financial crimes such as money laundering. For this, machines suspect such money laundering activities.
When it comes to providing additional benefits to the users, Artificial Intelligence (AI) is truly benficial. Smart Chatbots offers solutions to the clients which reduces the workload of call centers. We can also expect tremendous growth in future as Amazon’s Alexa is gaining much popularity because of its self-education feature. There are various apps which offer personalized financial advice and tracks income, recurring expenses, and spending habits.
For reducing the operational cost and for enhancing the boost productivity, robotic process automation is necessary. Robotic process automation (RPA) helps in eliminating human error. RPA helps in complying with KYC regulations.
Artificial Intelligence (AI) helps financial institutions in automated reporting and portfolio monitoring. It also helps in recommending financial institutions on possible actions. Thus, it emerges as the most instant, accurate and practical method to verify the repayment capability of borrowers.
In the financial industry, AI is increasingly reshaping the business landscape. AI will help financial institutions in planning or executing short term/ long term tasks like payment of bills or tax filing.
It will help in eliminating human error and maintain a high level of transparency in terms of know your client reporting and due diligence checks.
As there are multiple benefits of Artificial Intelligence (AI) in the finance industry we can expect positive changes from the AI in the future. It is exciting to hear that in upcoming g years AI will save huge cost of the banking industry. Banks & NBFCs are using AI with the intent to increase client satisfaction, maintain customer loyalty and improve efficiency in many ways.
AI has also enabled a tool to provide financial guidance to borrowers through voice & text messages. However, AI can be explored in the industry in many ways which require proper planning and infrastructure to collect and merge data. It will help financial institutions in reducing the workload of maintaining client information and after that reallocation can be done of human resources to perform revenue-generating tasks.