Biggest Use Case of Artificial Intelligence and Machine Learning Tools Is in Underwriting Process of Loans

Biggest Use Case of Artificial Intelligence and Machine Learning Tools Is in Underwriting Process of Loans

Muqbil Ahmar 26/07/2019 2

Artificial intelligence (AI) and machine learning (ML) are catching up in a big way, particularly in the space of banking and finance. In fact, they are being seen as cornerstones of a digital India vision. AI tools can provide the flexibility and scalability needed for enabling digital transformation for enterprises in the banking, finance, and fintech space. No wonder, the banking and financial sector is leveraging digital to improve customer experience as well as bottom lines. The best part is that this wave is favorable for startups and those wanting to start out afresh as they are not burdened with legacy systems and infrastructure. There are a lot of use cases of such technologies that the industry can take advantage of.

“The biggest use case of artificial intelligence and machine learning, which everybody is focusing on right now, is in the underwriting process for loans. This is where the action is right now. The underwriting process is very chaotic currently. Humanly, it is not possible to do underwriting for loans for say Rs. 50,000. This is one area that organizations are working on to create the best value out of these technologies. The big question is: Is it fully there? Not yet. However, several banks and fintechs are already at several stages of designing the processes. The second use case is fraud management. Manually, it is not possible to figure out trends. Even if one is able to figure out, how does one stop it from happening? This is where technology can be of great use,” says Sameer Singh Jaini, CEO and Founder of The Digital Fifth.

At the core of the banking business model is to make every customer interaction digitally enabled, whether it is account opening via a tab or other functions. AI tools and chatbots are already being deployed by several leading players to enhance customer experience. There is no paper involved and no filling of forms. The benefits are myriad. The customer spends less time along with the fact that there is no rework at the back end. Plus, there is no data leakage or loss. There are AI/ML tools these days that will crunch all the data backend and provide you with insights into customer acquisition, the most capital intensive part in the financial world. For example, if you placed a request for a check book at a branch, it would capture the data. Even if you went on Internet banking the next moment, it would track the request, since they are all interconnected. There is visibility and the customer feels in command of his transactions.

No wonder, banks are already leveraging such tools in the area of customer targeting and how to design marketing strategies. Basic clustering is manual in nature currently. It basically classifies products category wise. For example, it will slot products for Category A, B, or C. However, all that is changing now. Machine learning tools are providing insights into how to approach a customer or how to elicit a favorable response by tweaking the existing processes.

“Currently, processes that were earlier getting done manually are now being done through AI/ML tools, including processes such as robotic process automation (RPA). Intelligent automation is where the greatest activity is and this trend should continue. Data Analytics can be optimally leveraged if the input and algorithms are in place. Interfaces can be enabled or even made voice-based. The technology is already there, the challenge is that the practitioners don’t know enough about it. Moreover, technology takes time to deploy. In my estimation, within 3 years, a number of these technologies should get deployed and come into use,” says Jaini, who has held top positions in several banking organizations. He was the CTO at DCB Bank along with other key positions at Wipro and Infosys.

With the coming of AI/ML tools, there is a lot of apprehension over jobs losses as these technologies go about digitally disrupting industries and sectors.

According to industry experts, in larger entities, we should expect 30-50% of headcount decrease. There are a number of processes that can be automated. Some of the typical mundane roles will go. The banks will shrink in size in terms of the number of people. Most transactions will be instantaneous.

At the core of the business model is to make digitally enabled every single piece of customer interaction, whether it is account opening via a tab or other functions. There is no paper involved and no filling of forms. The benefits are myriad. The customer spends less time along with the fact that there is no rework at the back end. Plus, there is no data leakage or loss. There are AI/ML tools these days that will crunch all the data backend and provide you with insights into customer acquisition, the most capital intensive part in the financial world. For example, if you placed a request for a check book at a branch, it would capture the data. Even if you went on Internet banking the next moment, it would track the request, since they are all interconnected. There is visibility and the customer feels in command of his transactions.

So, whether it is account opening or cross-sell servicing, or whether it is the ability to manage your money, everything is taken care of and is digitally enabled.

“We had this as our basic premise when we started off. It meant a very different architecture to allow us to do that. So, all front end and back end was integrated in a seamless manner for visibility. So, you will never have a situation where we would say that we will come back after checking because everything is present on a common system. It allowed us to dramatically change our throughput and enhanced our servicing capability, making a world of difference to our functioning,” concludes Jaini.

A version of this article first appeared on dynamicCIO

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  • Bethany Drinkwater

    The allure of artificial intelligence and machine learning is that powerful computing does the work that would once have occupied human workers’ time – and does it more productively and effectively.

  • Gareth Reilly

    AI and ML continue to change how we problem solve and operate in business.

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Muqbil Ahmar

Techl Guru

Muqbil is India's #1 LinkedIn Top Voice 2017. He is a tech evangelist, environmentalist, women's rights advocate, editor, and founder of www.greenubuntu.com. He is an experienced broadcast and print journalist with a demonstrated history of operating in the media industry. His main area of interest are social issues, tech, economy, economy, films and arts & culture. Muqbil holds a master of arts (M.A.) and PGDM in broadcast journalism from the Indian Institute of Mass Communication.

   

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