Cloud Computing: A catalyst for the IoT Industry
I think Cloud computing became a catalyst for the IoT industry and the proliferation that is seen today probably may not have happened in the absence of Cloud integration. Typically, IoT devices like sensors generate huge amounts of data that require both storage and processing thus making Cloud platforms the perfect choice for building IoT-based solutions. In an IoT implementation, apart from data assimilation there are some fundamental aspects like security, managing devices, etc. that needs to be considered and Cloud platforms take over some of these implementation aspects enabling the solution provider to focus on the core problem.
An interesting case study of how IoT and Cloud technologies can help to create innovative solutions was presented in a Microsoft conference few years back. It’s a solution developed to monitor the pollution levels in Ganges which is a project sponsored by Central Pollution Control Board. For more information, readers could go to this link https://azure.microsoft.com/en-us/blog/cleaning-up-the-ganges-river-with-help-from-iot/
Digital technology in the financial services
When we talk about disruptive digital technologies in Financial Services industry, perhaps Blockchain is the one that stands out immediately. The concept of DLT (Decentralised Ledger Technology) has been around for some time and there’s lots of interest in leveraging this technology primarily for transparency and efficiency reasons. After an article by Reserve Bank of India in 2020, many Indian banks responded to this initiative by starting to look at opportunities that involve DLT. For e.g. State Bank of India tied up with JP Morgan to use their Blockchain technology.
Adoption of Blockchain could simplify Inter-bank payment settlement and perhaps could be extended in future to cross-border payment settlements across different DLT platforms. It could also be used for settlement of securitized assets by putting them on a common ledger. Another application is using DLT for KYC whereby multiple agencies (like banks) can access customer data from a decentralized and secure database. In fact, EQ uses Blockchain in its product offering to privately funded companies and PEs for Cap table management.
The next one is probably Artificial Intelligence (AI) and Machine Learning (ML) which is predominantly being applied in Financial Services industry in managing internal and external risks. AI-based algorithms now underpin risk-based pricing in Insurance sector and in reducing NPAs in the Banking sector. The technology helps banks predict defaults and take proactive measures to mitigate that risk.
In the Indian context, Unified Payments Interface (UPI) and Aadhar-enabled Payment Service (AePS) are classic examples of disruptive products in financial services industry.
Effective Network Security acts as a gatekeeper
In today’s connected world where much of the commerce happens online, it’s imperative businesses focus on security to safeguard them from threats in cyberspace. The recent approach to Network security is “Zero Trust model” which basically means never trusts any user/device unless verified. In this model, mutual authentication happens between the two entities in multiple ways, for e.g. using User credentials followed by a second factor like an OTP and sometimes application authentication happens through a digital certificate. The process also uses analytics and log analysis to detect abnormalities in user behaviour and enforce additional authenticating measures while sending alerts at the same time. This is something many of us might have come across when we try to connect to an application from a new device that the application is not aware of. The security mechanism might enforce additional authentication whilst sending an alert to us. Nowadays, businesses also use innovative methods of authentication like biometrics, voice recognition, etc. and some of these are powered by AI/ML.
Fintech players leverage Artificial Intelligence to bridge the gap in MSME lending
I think MSME lending (maybe Retail Lending too) is one of the segments significantly disrupted by technology. In a way, it has opened unconventional options for MSMEs to attract capital both for capex and working capital requirements. There are products ranging from P2P lending to Invoice Discounting offered by Fintech companies which is opening up a new market place. There are Fintech players interested in lending in this space and they use AI/ML models to predict probability of defaults and assess credit risk and appropriately hedge against them.