The Financial scene is changing with Fintechs and new businesses ascending in the market with more noteworthy deftness and increased cloud-based services coming down on Financial Institutions. To change their plans of action and simultaneously drive cost productivity, client centricity, trust and consistency, they are moving towards broad reception of Artificial Intelligence (AI) and Robotic Process Automation (RPA) innovation. The mixture of the two advancements catalyzes computerized transformation across traditional as well as modern financial institutions.
We spoke to Vineet Tyagi, CTO, Biz2Credit & Biz2X to understand the intelligent automation and digital transformation across financial institutions.
Intelligent Automation is happening across the globe. It's happening both in interactions with the customers and it's happening in the back office as well. Chatbots are one good example chatbots are becoming more and more intelligent. Intelligent Automation is helping banks be better responsive and understanding of the customer. So instead of the common answers, you would get, you know, based on a script, there is more predictability about the type of problems a particular customer can face. And hence, banks can be more responsive to the segment of one which is us and customer.
AI/ ML-based Analytical engine
Digital technologies like OCR, machine vision recognition, AI will understand your bank statements and can produce credit decisions that can understand your GST data. It is also helping banks and financial institutions design new products, for example, much faster. And it's also affecting the regulatory aspect in compliance as banks are much, much better able to take care of regulatory and compliance aspects. Intelligent Automation, you know that AI and big data techniques are allowing process efficiency to come. So if you need something today, instead of having to wait for 10 days, it's coming to you today. It is also helping banks and financial institutions design new products, for example, much faster.
Intelligent Automation in Financial services can be used to help organizations with improving cash flows. Automation can be deployed to send invoices on time. This simultaneously leads to earlier payments and improved cash flow.
We have the whole lending lifecycle, digitized and simplified. If you look at SMEs, even in a digital economy, now India is far ahead of many countries, where our digital tech stack is very advanced. , for example, the GST database. There's a lot of data available, but how do you convert it for fast credit assessment. Electronically we have different types of data, whether it's the GST data or bank statements or KYC data. And we have models that bring together analyzes and produces credit decisions that can help make faster decisions or even automated decisions to give credit. The whole digitalized lifecycle, as well as the faster decision cycles, increase the unit economics, meaning that, you can give smaller loans and still make money because you don't have a lot of overhead. What we have made possible with this is to give loans as small as 5000 rupees and still make money.
India lives in rural India and that's where 80% of our workforce and economy are. If you look at rural India, two things which have happened today is that barring let's say 10% of the really rural India, which is very disconnected very remote, and even in those areas young government has done a good job and there is some semblance of good internet connection internet connectivity coverage map is fairly spread out two lenses, let's say that 80% plus of our religious covered with very good coverage which is a fact.
The second thing is that the penetration of mobile phones and smartphones is also increasing. A lot of our population now is perhaps not internet savvy like they cannot go to a browser, but they're very mobile-savvy. They all know how to use mobile phones. With a phone, it's easy to take a photograph, even if you have paper documents you can take a photograph and can do many other things. These phones come with vernacular language support some of the tech giants have done some good work. You can respond in vernacular languages, this capability can be leveraged, so now we can support rural areas with lending.
Our technology can recognize photographs machine visions extract information from documents instantly and digitize them. We don't claim to have built everything but we have been smart with using what is available. And some of these bigger companies have done very good work with image recognition machine vision that's a draw reading of documents and OCR in vernacular. So, we partner with this such solutions and use those solutions to create these kinds of implement interventions.