{"id":566174,"date":"2022-10-14T05:45:46","date_gmt":"2022-10-14T04:45:46","guid":{"rendered":"https:\/\/ibsintelligence.com\/?post_type=leadership-interview&p=566174"},"modified":"2025-01-16T07:33:02","modified_gmt":"2025-01-16T06:33:02","slug":"how-intelligent-automation-helps-the-decision-making-process-vaibhav-gupta-visionet-systems","status":"publish","type":"leadership-interview","link":"https:\/\/ibsintelligence.com\/leadership-interview\/how-intelligent-automation-helps-the-decision-making-process-vaibhav-gupta-visionet-systems\/","title":{"rendered":"How intelligent automation helps the decision-making process, Vaibhav Gupta, Visionet Systems"},"content":{"rendered":"

Vaibhav Gupta of Visionet Systems explains how implementing intelligent automation solutions can improve efficiency within a financial institution and improve its end-customer’s experience as well<\/strong><\/p>\n

\"Vaibhav
Vaibhav Gupta, Head of Products, Visionet Systems<\/strong><\/figcaption><\/figure>\n

A lot of banking processes today require images of documents to be managed. These processes include mortgage applications, KYC, insurance, etc. Intelligent automation brings the capability to identify a document, read and extract the required data from that document and prepare the data ready for decision-making. According to Vaibhav Gupta, Head of Products at Visionet Systems<\/a>, this leads to better decision-making of a proposal with faster processing times and fewer errors.<\/p>\n

Gupta has worked extensively in leading the product journeys for some of the world\u2019s top lending solutions. At Visionet, he heads the product and business strategy for the entire banking and financial services portfolio with the intent to bring an innovation-driven approach and create more impact in the industry. He explained how intelligent automation goes beyond robotic process automation (RPA):<\/p>\n

\u201cRPA is rules-based automation of low-level tasks to increase speed and reduce errors. Intelligent automation uses a lot of different technologies, such as computer vision, OCR and AI. Intelligent automation can hence take the next step in automation by bringing capabilities that are more complex than RPA. An example is reading documents and extracting the required information.\u201d<\/p>\n

How do you identify opportunities to monetise Intelligent analytics, and how does this affect business strategy and product development?<\/strong><\/p>\n

\u201cFunctions in banking that have large human resources are a quick way to shortlist use cases for AI and ML. Today a lot of work that we do can be assisted by AI and ML. This increases the quality, improves the work culture of the team, and enables you to take up initiatives that can increase the value that your teams bring to the organisation.<\/p>\n

\u201cBanks and financial institutions can now move closer to \u2018no touch\u2019 banking facilities even to complicated and high-profit transactions such as mortgage and Insurance claims. This increases scalability and brings a lot of customer satisfaction at the same time. Delighting your customer and having the ability to fulfil an increase in demand while reducing your cost of operations is a really good way to get ahead!\u201d<\/p>\n

What are the 3 key areas in intelligent analytics in banking and finance?<\/strong><\/p>\n

\u201cI would try and answer this in a different way. Look at the functions with the following lenses:<\/p>\n