How Big Data Analytics, AI and Machine Learning Help in Fintech Evolution

Having deep understanding of technology architectures, Pratik is responsible for driving quality and reliability of the company's technology platforms.

If you are not doing AI than you are not innovating, this has been a trend for the past one year. Everyone from Elon Musk to Jeff Bezos to Warren Buffet believe that AI and Machine learning is the way forward and nothing is going to be untouched by it.

What people do not realise is that AI, Machine learning and big data analytics is already a part of their daily life. Right from when they check the Google maps for traffic to when they talk to Siri, Amazon Echo or Google home. Even when they watch videos or for that matter buy some thing online, there is some or the other Data or AI Engine running to get more insights and making customers life easier.

Fintech industry in India is also going to see this surge of AI, ML and Big data use in day to day cases. Some of the innovative Fintech companies are already leveraging the same. So how will this work? How will this all come together? Here are few scenarios,

AI, ML usage in KYC
One of the biggest hindrances in today's time with Indian fintech companies is onboarding of a customer. Unlike e-commerce a fintech customer has to compulsorily go through a cumbersome account opening process where they are required to submit various documents like Address proof, bank proof and Id proof. One of the place where AI and ML can make a big impact is detection of data on these documents and also at the same time making sure that these documents are authentic or not. Most of the fintech companies in future are going to be using one or the other AI/ML tools in this area to make sure the KYC process is not at all tedious for the customers.

Big Data, AI and ML in Fraud Detection
Detecting patterns, learning from them and predicting is what AI, ML and Big Data analytics all combined together do really well. One of the best applications of this would be learning from the past frauds and apply them in real time. The key is to handle huge volume of data in real time and detect fraudulent patterns using AI and ML engines. Also such engines can be used in settlement of claims by analysing, comparing the frauds with past data and automating the claim settlement for such cases while at same time learning those patterns to avoid them in future.

All Lending companies in future will be moving to such systems and those who don't will become out dated and perish

Big Data, AI and ML in Regulatory Compliance
One of the latest buzzword in the western countries is RegTech, which is Regulatory technology. Finance is a highly regulated industry with a whole lot of compliance. With advancement in AI and ML, regulatory compliance can not only be automated but also applied in real time. AI can learn from past and comply with all the applicable laws which might get missed manually.

AI, ML (Natural Language processing) in Customer support
We are already talking to machines now-a-days like Siri, Google Home and echo. Such systems will become master conversationalist in future and most of the customer support will be automated using such bots or engines. Not only Fintech but most of the customer support in many industries will be completely taken over by it. One of the key areas in India would be Natural Language processing of multiple languages, it was learnt that Amazon echo can now converse in Hindi, if such innovations keep happening we no doubt will be talking to machines while having a feeling that we are conversing with a human.

Big Data, AI and ML - Auto Credit rating, lending and Risk Profiling
Today a lot of fintech companies in India are using AI to do risk profiling of a customer in real time and based on his credit rating are able to disburse loans instantly. All Lending companies in future will be moving to such systems and those who don’t will become out dated and perish. We have already seen that there are companies who use AI to rate a customer or evaluate the loan to be given using his financial documents and his social media history. Such use cases will only get more and more complex by use of AI and ML.

There are a lot other use cases also like Automated Stock Ranking, Algo Trading, Wealth Management, Security management and so on as so forth. Fintech industry is on the cusp of innovation and things which were never possible in past have become possible today thanks to AI, ML and Big Data.