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Newgen Software 2022 Predictions: AI Unfolded - Top 6 Predictions for 2022 and Beyond for the Banking Industry

vmblog predictions 2022 

Industry executives and experts share their predictions for 2022.  Read them in this 14th annual VMblog.com series exclusive.

AI Unfolded: Top 6 Predictions for 2022 and Beyond for the Banking Industry

By Ashish Deshmukh, Head - Banking and Financial Services, Newgen Software

Artificial Intelligence (AI) has transformed into many facets over the years. Today, AI-powered products and services have become central to our everyday lives as enterprises continue to leverage them to provide intelligent, personalized services.

A Gartner report delineates the rate of AI adoption as "By 2025, 70% of organizations will have operationalized AI architectures due to the rapid maturity of AI orchestration initiatives." This substantiates the necessity for businesses to adopt AI faster. It is no longer a question of "to do or not to." The coup of AI and related technologies will only expand its wings in the future and will continue to redefine processes across industries, such as Banking, in a big way.

If you are in the banking and credit union sector, watch out for the following AI trends to navigate 2022 and beyond:

1.       Pervasive Adoption of AI

The pandemic has permanently changed how banking services have been perceived for so long. The shift from in-person to all virtual/digital services has completely disrupted the way financial institutions operate. Most companies accelerated their adoption of digital, with a focus on the adoption of AI-enabled solutions to streamline their operations and services. AI-enabled tools like bots, virtual assistants, data security tools, personal identification and verification services will continue to transform several aspects of the banking functions.  

2.       Process Automation and Upscaling through AI

AI-enabled process automation will help banks and credit unions eliminate repetitive tasks and streamline complex processes. Such systems generate insights by leveraging smart data capture tools, reducing back-office processing. Financial institutions will be able to speed up transactions and data retrieval through intelligent automation. AI can also enable such organizations to upscale their operations successfully through optimum utilization of resources.

3.       AI-powered Tools to Revamp Customer Engagement

Banks and credit unions can leverage AI to deploy tools like bots and virtual assistants that function as a two-fold solution. First, AI bots based on intent can automatically respond to customer queries. Second, agents in the back office can utilize these bots to respond aptly based on customer interactions.

AI-enabled bots can simplify complex customer engagement processes to hand-hold customers throughout their journey and provide a seamless user experience.

4.       Intelligent Document Verification and Identification to Transform Customer Onboarding

With best-in-class accuracy, AI-enabled document verification and personal identification will help financial institutions accelerate their customer onboarding process.

AI capabilities will help verify the sanctity of various documents and enable error-proof processing. Such systems will also speed up the identification of individuals by deploying self-learning facial recognition tools that can detect the liveliness of individuals to prevent any kind of fraud.

5.       Analytics to Deliver Personalized Offerings and Improve Cross-sell, Up-sell Opportunities

Data analytics will serve as a significant catalyst, driving intelligence into product offerings tailored to customer needs. Digitization of services has led to a sudden surge in the data wealth of financial institutions. They need to mine this data and derive insights by leveraging advanced analytical tools, which can be leveraged to design and deliver hyper-personalized offerings to customers.

6.       Low Code to Foster Innovation by Enabling AI and Natural Language Processing (NLP)

Building AI systems can be a complex task, especially for the lack of skilled developers in AI development. The shift towards low code solves this problem by simplifying application development through a visual, guided interface and drag-and-drop module.

Natural Language Processing is a new area of AI that is increasingly finding acceptance in the BFSI sector. Low code can help in deploying NLP tools by simplifying the development and execution of such systems.

As projected by a PwC report, "AI could contribute up to $15.7 trillion to the global economy in 2030. Of this, $6.6 trillion is likely to come from increased productivity." This shows how great business opportunities will be unlocked through AI in the coming years.

AI revolution is steaming ahead at an incredible pace, and it is only going to get more prominent in the future. It's time for financial institutions to make the most of this opportunity and become a part of this revolution.

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ABOUT THE AUTHOR

Ashish Deshmukh 

Ashish is an enterprise revenue leader with 25 years of experience in setting up global businesses, expanding markets, and running a winning sales organization for enterprise SaaS products. He is passionate about solving complex business problems across the financial services vertical with a "digital-first and digital best" strategy for leading global enterprises. In his free time, he likes to write and has a painting studio that he uses for his creative outlet.

Published Monday, January 03, 2022 7:30 AM by David Marshall
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