How AI is Transforming BFSI Industry [Use Cases, Examples, & more 2021]

AI in banking industry

How AI is Transforming BFSI Industry [Use Cases, Examples, & more 2021]

How AI is Transforming BFSI Industry [Use Cases, Examples, & more 2021] 500 400 Alisha Fernandes

Automation requirements in the BFSI sector have been spotted. The demand for AI in Banking and Finance has skyrocketed. This demand only seems to keep increasing as there is a requisite for new and efficient methods to be deployed so that the strenuous tasks and unnecessary paperwork are left in the very capable hands of Data Science, Machine Learning, Natural Language Processing, Deep Learning, and Computer Vision, while humans successfully handle the more proficient responsibilities.

Use Cases of AI in BFSI Industry

Undermentioned are some examples of AI Use Cases in Banking and Finance that would help in process automation. Nevertheless, these are flexible and can be modified further.

Use of AI in Banking & Finance

Automation of KYC processes – This involves reviewing the completeness and accuracy of uploaded documents, identifying if the uploaded document is unclear, Xeroxed, or not the one in question. Aadhar card, pan card, passport, etc. can be analyzed to check if the quality of the text and pictures are up to standards. Contents from the different forms can be extracted and written in a specific format automatically. All this is done using Optical Character Recognition, Natural Language Processing, and Computer Vision tools. Video KYC is also possible.

Conversion of handwritten documents to digital format – Using OCR, any hardcopies, including those written by hand can be converted to digital softcopies to store online. The hard copies are converted to editable documents. This can be done with a high level of accuracy. If the documents are lengthy and need to be summarized, the next use case could be used post this

Automated Summary Generator – Keywords are fed into the ML algorithm and the solution is trained to understand which parts of the content are important. Based on these keywords, the words around them are analyzed. This is how any huge document of thousands of words can be brought down to a hundred, into one short summary with the help of our automated summary generator.

Non-Compliant Issue detection – The task of reading thousands of documents to check for issues could be automated. Non-compliant issues could be found in regulatory compliances. The solution will accurately find all the issues based on the constraints we provide and notify accordingly.

Marketing Automation – Using Automated Targeted Marketing, identify the right target audience to generate more leads and eliminate unnecessary spending. Using Sentiment Analysis, customer reviews and thoughts can be scraped from the internet to understand their experience and make the necessary changes. AI can also be used to interact with existing clients who are not responding and keep them satisfied.

Customer Churn prediction – Analyze the loyalty of your clients and the probability of them leaving you to know whether modifications need to be made. For this, the past data of your clients would be required. More the data, the better the prediction. Using this data, the prediction model can be built.

Financial Forecasting with default prediction – It is easy to predict your profit in a best-case scenario. One of the reasons why your financial forecasting would not be accurate is that some of the clients are not able to pay back the loan. By predicting whether your client will default, you will be able to calculate your financial forecasting more accurately.

Fraud Detection using Anomaly Detection – Fraud detection is very important in the loan and insurance sector to know whether the case is genuine or not. Based on historical fraud patterns, the solution can recognize them automatically. The solution can look for links between credit cards and loan applications, along with monitoring newly opened accounts to prevent financial damage. This is how AI can help in insurance and loan processing, and make sure you have the right clients.

Competitor Analysis – With the help of this solution, the internet is scraped based on hashtags and buzzwords to find out news about your competitors, what your competitor is saying, and what’s new. Even general information about the BFSI sector, or what’s new with a specific sector can be collected and given to you and keep you updated on the happenings in your sector.

Recommendation systems – Help your clients pick the right loan or insurance policy. This is done based on user data, including their background, who they are, and what they need it for. We can identify inputs from online (user visits to the website, for example), inputs from offline (user data kept in the bank’s database), or the mixture of both kinds of data to provide the best suggestions. A recommendation system can even be integrated into your existing Chatbot.

Chat Bot – Every active website needs a ChatBot. Answer FAQs, unexpected questions, customer queries, and make your website a hub of helpful information. ChatBots can be multilingual, i.e. they interact in all languages desired, and can be integrated with WhatsApp or your Web Apps and Sites. Another point to be noted is that our Chatbots are as kind and polite as your human customer care, if not much more.

Insurance Pricing – AI can assess a customer’s risk profile based on claims data, biometric data, health history, family history, and identify optimal prices for the insurance plans. Analyzing these past records and determining how prone to risk the customer is, the AI solution will help offer the appropriate price to your clients.

Automated cost repair estimation – This solution will analyze accident images to estimate repair costs in real-time. This will help in Motor Insurance. The solution will understand the impact of mishaps and authenticity of claims to provide the average cost that would need to be covered up for the incident.

Video Analytics integrated with CCTV – This solution helps with motion tracking and detection of equipment and employees to eliminate the need for full-time supervision. Identifies unsafe measures, detects unauthorized access and notifies the concerned person if anything is beyond normal. A solution can also be provided.

Face Recognition. AI can be used for surveillance and security. Any alterations or deviations from the regular will strike up an alert. Artificial Intelligence in the Banking and Finance sector (BFSI) is booming and growing, and will soon be amalgamated with insurance and loan processing, as well as in Capital Markets. It will not take a long time for all BFSI companies to make redundant some monotonous tasks that can be done so conveniently using AI & ML.

What are the Examples of Artificial Intelligence in banking?

In this modern era, the amount of data generated in the banking industry is very huge and requires unique AI tools to manage it. below you can see the different examples where Artificial Intelligence is used extensively.

  • Fraud Detection
  • Risk Assessment
  • Trading
  • Risk Management
  • Financial Advisory Services
  • Credit Decisions
  • Better Predict & Assess Loan Risk
  • Preventing Cyber Attacks
  • Save Money
  • Ability to Execute Task of any Length


After reading the whole article you would be sure that The future of Artificial Intelligence in Banking & Financial services is going to be very demanding. Many BFSI industries are leveraging the power an AI for different processes like KYC automation, competitors analysis, and insurance pricing, etc. in the banking & finance sector.