AI is a must now

AI is a must now to speed up digital transformation

by | Jul 30, 2020 | Artificial Intelligence, Artificial Intelligence, Digital Transformation, Viewpoint

AI is no longer an either-or debate but a when-and-how discussion that board rooms must attend to now.
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The history of humankind has also been the history of human intelligence and its continuous evolution. Ironically, this has enabled us to amass so much knowledge and information that it has become humanly difficult for us to process it in real time. Artificial intelligence aka AI is a must now.

Moreover, as we acquire new knowledge, we also tend to lose what we had gained in the past. This is a weakness inherent to us humans, but the digital information systems that we developed help us overcome that shortcoming amazingly well.

Today, we can store and retrieve knowledge at will. More importantly, we can store it in one form and retrieve it in another form. Speech recognition AI technologies have matured to remarkable levels today. One would simply record a conversation and transcribe it within minutes in a perfectly legible text form. Similarly, chatbot technologies are rapidly redefining the customer interfaces for many an organization.

AI is the new game changer

Artificial intelligence driven solutions are now playing a critical role in processing knowledge and utilizing the learnings to augment human activities.

These AI solutions help us shorten our response times to a situation, so that we are able to make the most of an opportunity and deal with a threat in the best possible manner.

However, the AI deployments are still in early stages, though it is hoped that the Covid-19 pandemic will accelerate these deployments. Specifically, technologies like speech recognition, chatbots, and robotic process automation (RPA) have rapidly matured in the recent years and are now ready for large-scale adoption.

Imagine what would have happened if all cities and governments were armed with sophisticated AI tools when the Covid-19 cases surfaced or were in their early stages of spread. It is quite likely that authorities would have been able to contain the spread before it spiraled out of control.

That brings us to the theme of digital transformation, which could accelerate widescale deployment and usage of AI solutions by governments, businesses, and citizens alike.

Transformation and agility – two sides of the same coin

Transformation could be accelerated by being agile. If you are agile, then you can transform quickly. And if you’re committed to transformation then you will be eager to embrace agility.

Organizations that had already advanced on the path of digital transformation, are today better prepared to adapt and respond to the challenges. Expectedly, they will also be the ones to recover faster than others.

Other businesses too must undertake rapid transformation routes to emerge truly nimble and agile if they were to survive a long and slow macroeconomic recovery cycle. Such an approach would enable them to respond to market situations in dynamic and resilient ways, create value for themselves and their customers, and muster growth and profitability in a sustainable manner.

Moreover, businesses could also leverage IT to change the shape of recovery curve to an extent and create greater value for their stakeholders as well as customers.

AI is the soul of future digital transformation initiatives

AI could significantly accelerate innovation and transformation. It is time to open up new streams of AI conversations that will help realign the digital transformation agenda of businesses to the changed needs of a post-pandemic era.

AI case studies and use cases already exist that could be adapted and used by organizations and governments. Leading organizations in areas such as banking, financial services, retail, logistics, healthcare, automobiles, e-marketplaces, and cybersecurity are already at the forefront of AI adoption. In the near future, while they work to further perfect and mature their AI applications, other organizations will be keen to catch up.

One good way to accelerate AI adoption would be to watch the early movers and learn from their successes and failures.

For instance, Mastercard has been an early mover. It introduced Decision Intelligence, a comprehensive decision and fraud detection service, in November 2016. According to Mastercard, the solution uses artificial intelligence technology to help financial institutions increase the accuracy of real-time approvals of genuine transactions and reduce false declines.

Similarly, AT&T, the world’s largest telecommunications company, has also been an early deployer. In December 2016, AT&T rolled out its entertainment chatbot Atticus.

In April 2017, Vodafone UK launched its AI chatbot, TOBi, powered by IBM Watson and LivePerson. The telco described it as a virtual customer services’ agent that could handle a range of customer queries including device troubleshooting, usage, and order tracking, among others.

The Covid-19 scenario has made a profound impact on the way people collaborate and work. In this situation, AI and ML will be the key navigational technologies to deliver results, and hence, are expected to be embraced widely by organizations of all scales.

[If you would like to share a use case and recommend it in the larger interest of other organizations, please drop me a word at deepakk@bmnxt.com.]

MORE FROM BETTER WORLD

Tech startups in India building resilience amid disruption

Tech startups in India building resilience amid disruption

Indian tech startups are setting a perfect example of building resilience amidst the crisis. Even though the havoc wreaked by the COVID-19 pandemic was unprecedented and resulting in severe pain, it is also true that the outbreak profoundly influenced indigenous innovations, new tech startup ideas, and digital transformation roadmaps in India. (See: Digital transformation deals put IT sector back on track)

When businesses were scrambling to find the best ways to deal with the crisis, Indian tech startups emerged as a force to reckon with. According to a recent Nasscom report, India added a whopping 1600 plus tech startups in 2020 and has become the third-largest tech startup ecosystem in the world after the US and China. 

Ravindra Kumar, IT Delhi Alumni AssociationRavindra Kumar, President, IIT Delhi
Alumni Association

“Fostering entrepreneurship and nurturing tech startups has always been a key priority area for IIT Delhi. We utilize technologies such as artificial intelligence (AI),
blockchain, and cloud to get all our students and alumni together and build a global outreach.”

Rajesh Kumar, Founder CEO of Sabzibhazi.com

“The last few months have been good for our business. As people moved to digital channels for their grocery shopping needs, we got thousands of new customer registrations, and there is substantial revenue flowing in now. We are planning to expand our operations and upgrade our app interface for better positioning.”

Akhilesh Shukla, TechshotsAkhilesh Shukla, Co-Founder and Editor TechShots.

“We saw a significant gap in the Indian news industry, lacking a common tech-news platform for enterprise decision-makers. And that’s how the idea of Techshots was born. Leveraging technology, we are delivering technology news and enabling technology decision-makers to make informed decisions.”

The number of unicorns (those who have a valuation of over $1 billion) is also growing steadily in India. In 2020 alone, 11 startups from India joined the unicorn club, which boasts of Paytm, Ola, Zomato, Cars 24, and 34 others.

The above figures are intriguing and contrary to the early fears raised by several industry observers. The Indian startup ecosystem was projected for a steep decline by many in March 2020 due to the Covid-induced bedbound economic environment. Technology interventions and innovative ideas played a pivotal role in resuscitating the growth path. (See: How is digital transformation shaping the new future?)

Turning the crisis into opportunity

When millions of citizens were confined to their homes, the rise of digital technologies created fresh opportunities. These technologies enabled people to do things efficiently and in a cost-effective way. Had it not been for the role of IT and tech startups in India, the impact of the crisis could have been more upsetting!

Amidst the widespread uncertainty and social distancing measures, the dependencies on digital solutions grew enormously. Whether it is healthcare consultation, retail, astrology, education, grocery supply, or entertainment, technology kept the economy running and helped us adapt to the new normal.

If Indian tech startups such as Byju, UpGrad, and Unacademy excelled in transforming the education and learning delivery, location surveillance apps such as Unmaze, Aarogya Setu, and Sahyog kept the COVID-19 virus in check. India also witnessed a massive surge in fintech and health startups as the demand for their services, such as contactless payments and telemedicine, grew much faster.

News aggregators such as InShorts, Dailyhunt, and TechShots have gained significant traction as people continue to switch to their personal mobile devices for real-time information and news.

Some of the new habits that people learned during the pandemic are likely to remain permanent, and this compelled many entrepreneurs to launch niche and specialized services. “Media consumption habits are changing quickly. Most consumers now prefer to receive their daily dose of news bulletin digitally in a crisp format. During the COVID-19 crisis, this demand reached a record level. We saw a significant gap in the Indian news industry, lacking a common tech-news platform for enterprise decision-makers. And that’s how the idea of TechShots was born. Leveraging technology, we are delivering technology news and enabling technology decision-makers to make informed decisions,” said Akhilesh Shukla, Co-Founder and Editor TechShots.

With quarantine and lockdown rules forced consumers to stay indoors, online grocery delivery demand witnessed a massive rise throughout 2020. Along with established online grocery suppliers such as Big Basket, Grofers, and Amazon, agritech startups such as Otipy, Sabzibhazi, Freshokartz, Agrowave, among others, also made their presence felt.

“I started Sabzibhazi in 2019. When I first launched this company with my meager savings in 2019, it didn’t do well. The idea was to provide the freshest produce at a reasonable price using a new-age tech platform. Even though we did much research, but there were still no customers. It was a tough time. We didn’t go for fundraising as we didn’t want to be answerable to anyone. Moreover, we were not sure if we would get that much attention from venture capitalists,” says Rajesh Kumar Pandit, Founder CEO of Sabzibhazi.com, a South Delhi-based digital farm-to kitchen service provider.

Things changed quickly for Rajesh when India announced nationwide lockdowns. Many established players failed to meet the unprecedented surge in demand for online fresh produce. “The last few months have been good for our business. As people moved to digital channels for their grocery shopping needs, we got thousands of new customer registrations, and there is substantial revenue flowing in now. We are planning to expand our operations and upgrade our app interface,” an enthusiastic Kumar adds.

In the healthcare space, startups like Pharmeasy, CureFit, and EyeNetra attracted massive investors’ interest.

Innovative ideas fueling startups

Besides the above, innovative virtual event platforms Airmeet also garnered significant attention from enterprises. Businesses took their services for hosting various internal workshops, panel discussions, and customer events in a setting where physical events are restricted.

There are also pure-play data analytics firms such as Mu Sigma, which are growing exponentially. 

The tech startup culture in India is equally supported by the government and premier institutes like IIT. The Indian government has taken several initiatives recently to help the local startup ecosystem grow. Under the AatmaNirbhar Bharat vision, the government has eased regulations, announced tax exemptions, and set up a Rs 10,000 crore fund exclusively for startups.

“Fostering entrepreneurship and nurturing tech startups has always been a key priority area for IIT Delhi. We utilize technologies such as artificial intelligence (AI), blockchain, and cloud to get all our students and alumni together and build a global outreach,” said Ravindra Kumar, President, IIT Delhi Alumni Association, in an earlier interaction with Better World. (See: IIT Delhi can help develop an Indian equivalent of Google or Facebook).

The year also saw spectacular ideas such as anti-viral t-shirts and COVID-19 protective lotions unveiled by E-TEX and Clensta, two startups incubated at IIT Delhi.

Another startup that caught our attention was ATAI Labs; an applied AI company launched recently. The startup provides AI-based digital transformation solutions for the supply chain and logistics industry, which bring the data center capabilities closer to the source of data and enable AI inferencing, decision making, and analytics at the EDGE.  The 70-employee young Indian startup offers innovative solutions to augment maritime, retail, locomotive, and surveillance capabilities. (See: AI is a must now to speed up digital transformation)

Factors.ai is also an AI-based startup that focuses on providing marketing analytics for entrepreneurs and small-medium businesses. The startup was chosen as one of the 20 firms for the fourth cohort of the Google for Startups (GFS) Accelerator program in India last year.

An equally exciting tech-startup, The Water App, was launched to solve the water crisis in Hyderabad. The company leverages advanced technologies and intelligence to monitor supply chain management of water and deliver clean water at the doorstep.

Final thoughts

Before the pandemic, many enterprises were reluctant to go online entirely. But things changed quite dramatically. Across all sectors, there was no option but to accelerate the digital transformation.

Indian tech startups and IT companies proved that integrating innovations with adaptability models led to new pathways and behavioral models, bringing together enormous resilience and resolve.

At Better World, we believe that this is just the beginning. Indian tech startups not only took risks and found new innovative models but were also instrumental in adding thousands of new jobs at a time when people were losing hopes. In 2021, according to Nasscom, the Indian IT industry (along with the tech startups) is expected to add over 1,38,000 new hires, taking the total employee base in this sector to 4.47 million.

By leveraging technologies such as artificial intelligence, analytics, and cloud-based collaboration tools, these young tech companies will continue to bring the best of the ideas and tools to revive the economy and develop life-enabling solutions.

Narendra Agarwal joins Dabur as Global CIO

Narendra Agarwal joins Dabur as Global CIO

Narendra Agarwal CIO

Narendra Agarwal, Global CIO, Dabur.

Narendra Agarwal has joined Dabur India as its new Global CIO. Agarwal moves from Hindustan Unilever Limited (HUL), where he donned multiple IT and automation leadership roles during the nine-year tenure. He was responsible for digitizing Dabur’s newly acquired Nutrition (GSK) business.

“We are delighted to welcome Narendra Agrawal as the Global CIO of Dabur India Ltd. Narendra is an MBA professional with 13 years of industry experience in technology transformation and leadership. Narendra comes with vast exposure in successfully leading large-scale global transformation projects in ERP, Logistics Operations, financial forecasting, and S&OP,” Dabur said in a statement released through its official Twitter account.

Among his HUL accomplishments, Agarwal led E2E IT integration for Unilever’s biggest merger and the first-ever remote merger in the industry. He led the technology stabilization and automated platform management for the logistics technology solution, driving continuous improvements in the DevOps model for business.

Overall, Narendra Agarwal has led several large-scale business and technology transformation programs with Dabur, Amdocs, and Capgemini as a CIO or IT leader.

An alumnus of IIM Indore, Agarwal has a keen interest in strategizing and rapidly executing technology capabilities for specific business capabilities that help build business models to get closer to users and help enterprises gain a competitive edge. Narendra has also done a Bachelor’s in Engineering from Mumbai University. 

About Dabur India

Dabur India Ltd is one of India’s top FMCG Companies with revenues of over Rs 7,680 Crore and a market capitalization of over Rs 88,500 Crore. Riding on consumer discretionary spending revival, Dabur India reported its highest-ever quarterly revenue and profits in December 2020.

Dabur also plans to set up a new subsidiary to manufacture, sell, and export its consumer care products. The company was founded in 1884 by SK. Burman and headquartered in Ghaziabad, Uttar Pradesh.

AI tools can drive big efficiencies in oil and gas

AI tools can drive big efficiencies in oil and gas

The role of artificial intelligence (AI) is evolving, especially in industrial organizations such as oil and gas, where data acts as a critical enabler to provide a competitive advantage. Industrial organizations operating in the fields of mining, oil, and gas; and marine, are going through a radical transformation and seeking innovative ways to optimize performance with minimized risk.

The volatile and ever-competitive nature of the industrial companies demands them to identify new and innovative sustainable models to stay profitable, grow and unlock efficiencies. The situation has become more challenging in the wake of the coronavirus pandemic. According to a Capgemini research, over 50% of the European manufacturers, 30% in Japan, 28% in the USA, and 25% in South Korea implement AI solutions.

Enterprises operating in Oil and Gas, Marine, and Oil use traditional machinery which may not be easily replaceable because of the huge costs associated with it. Hence, they need advanced technologies to optimize their operations. They are the ones where data could act as a critical enabler to provide them a competitive advantage if managed with the right combination and tools. (See: How will AI impact enterprise ecosystems in 2021?)

Intelligent machines, optimized production

An estimate from the Robotic Industry Association says the cost of one minute of production-line downtime for a company like General Motors could be around $20,000. That’s enormous!

AI for industrial organizations has become essential for driving operational efficiencies of their assets and processes. With AI and ML advancements, industrial enterprises can make their machines smarter, predict maintenance schedules, minimize downtime and let the devices identify problems sooner, and even rectify them automatically in some instances.

Industrial organizations have an enormous amount of data from their different manufacturing processes. However, the lack of talent and necessary tools prevent them from leveraging the same for deriving meaningful insights.

By monitoring and analyzing data carefully, industrial organizations can anticipate the gaps in the output and receive automated warnings to stop the machine when there is an issue. This helps save cost and time, assisting companies to better their efficiencies. For instance, by leveraging AI-based predictive tools in oil and gas, companies can identify the machine and pipeline deterioration signs and raise alarms to pipeline operators. The use of voice-enabled AI chatbots can also help in oil and gas and mining areas, whereby operators can engage in meaningful automated conversations around the processes, focusing solely on production-related activities.

The supply chain is another crucial process gaining substantial benefits from the AI and ML-driven applications, ensuring industrial companies create equipment buffers as per the real-time market demand. Besides, AI capabilities are also being used extensively for manufacturing and industrial companies to reduce energy consumption, minimize assembly lead times, and increase asset utilization.

Key challenges

The challenge, however, for the industrial organization is a widening gap in the knowledge and competencies of various enterprises’ internal IT departments. The shortage of internal talent to deploy and scale AI in production and integrate with existing standardized solutions.

The successful predictive maintenance strategy is heavily dependent upon the data to integrate necessary engineering in the machinery. Data can not bring efficient results in case they are working in seclusion.

The industry needs strong foundations and collaboration models to create new enterprise-specific applications to analyze data and automate critical processes. Another major challenge that many enterprises need to deal with is managing the people and cultural change. It becomes necessary for organizations implementing AI solutions to conduct essential workshops and focus group discussions on understanding the pain points and queries of their employees.

As we move forward in 2021, AI for industrial organizations will see greater demand as they focus on reducing time to impact and balance their supply chains according to the real-time demand. The industry is likely to witness a steep rise of several integrated solutions from emerging solutions providers and specialized companies to help Industrial companies drive further innovations.

Star-Disney India ropes in Tirthankar Dutta as CISO

Star-Disney India ropes in Tirthankar Dutta as CISO

Tirthankar Dutta, CISO, Star-Disney India

Tirthankar Dutta, CISO, Star-Disney.

Tirthankar Dutta has joined as the Vice President (VP) and CISO of Indian media conglomerate Star-Disney India, a Walt Disney subsidiary in India.

In his new role at Star-Disney, Dutta will spearhead the company’s security transformation initiatives and provide the necessary direction and guidance to the CTO/CFO and key Disney-Star business leadership members.

Besides, Tirthankar Dutta will also manage information security governance processes, chair the information security advisory committee, and lead information security programs and project priorities at Star-Disney. He will be internally assessing and providing necessary recommendations around security controls to the Disney leadership in India. Dutta’s responsibility also includes establishing an inclusive and comprehensive security program for Disney and developing essential support for internal information systems and technology research capability.

As an IT professional with over 14 years of experience, Dutta has led several IT and IT security projects in top financial services, travel shopping, and IT services companies such as Religare, Expedia, HCL, TCS, and IBM.

Dutta has established and implemented large information security programs, including deploying a patent-pending fraud detection solution that protected thousands of clients from phishing attacks. He has been credited with performing evaluation and selection of IT security tools and successfully implemented IT security systems to protect availability, integrity, and confidentiality of critical business information and information systems.

Before moving to Star-Disney, Dutta was the Sr VP and Head of Information Security at Infoedge India, a pure-play internet classified company. At Infoedge, he led the information security program and built cohesive security and compliance programs to address state and Country statutory and regulatory requirements effectively.

About Star India

Owned by the Walt Disney Company, Star-Disney India is an Indian media conglomerate with its headquarters in Maharashtra. The media company offers content in eight languages through its 60 channels. Its network reaches approximately 790 million viewers a month across India and globally.

For other recent C-Track movements, click here.

Five key steps to a successful RPA implementation

Five key steps to a successful RPA implementation

The Robotic Process Automation (RPA) adoption in India has picked up pace as enterprises focus on developing automated intelligent process automation bots to support their users and employees round the clock. (See: RPA-led tools helping enterprises sail safely through a storm). Despite the benefits RPA offers, many companies struggle to maximize the value of their RPA implementations. Let’s delve deeper into some of the critical steps to a successful RPA implementation for enterprises.

These steps can also ensure there is no gap between reality and expectations from an RPA initiative.

#1. Define your objectives 

RPA is a game-changing digital transformation initiative, automating several traditional mainframe applications by leveraging AI/ML-based software robots. At the backdrop of the pandemic triggered economic slowdown, businesses are increasingly exploring intelligent automation and RPA for refining quality while controlling costs.

According to McKinsey, RPA can deliver up to 200% ROI in the first year of deployment and 20-25% cost savings. Additionally, it also enables organizations to enhance compliance, become risk-averse and strengthen the customer experience. The mundane and time taking processes turn fast, and users get an opportunity to switch to higher-value work.

However, like every strategic technology investment, RPA investments need to be evaluated based on their potential utility to a particular enterprise or a process.

There is no one size fit all solution! As a first RPA implementation step, the process you select for RPA should be carefully mapped against your end-goals. Before you assign the process execution from your employees to bots, you need to set clear goals around what you want to accomplish from a specific RPA implementation and the financial aspects of the deployment.

#2. Select your processes intelligently

An overarching strategy for process selection and implementation should be in place before you move to RPA. The most critical goal that drives RPA adoption is achieving enterprise efficiency for highly repetitive tasks. RPA tools imitate a human being’s actions by following a rule-based structured approach to accomplishing specific routine tasks, helping employees retrieve a significant proportion of their time.

Hence, as a key step for a successful RPA implementation, the process you select for RPA should be mature, predictable, and stable, high-volume, involve a considerable amount of repetitive human efforts, based on pre-defined data patterns, and evaluated on measurable savings. For instance, data validation, extracting data from PDFs, and employment history verification.

#3. Build an execution team

It is paramount for any automated process that a group of team members is assigned to keep a closer look at all the change-related developments and flag any inconsistencies. This team is often called as Center of Excellence (CoE) team for RPA projects.

Enterprises that do not have the right capabilities and resources or deploy the RPA model for the first time can also support specialized external consultants to facilitate RPA implementations effectively.

#4. Develop a robust change management plan

The success of any RPA initiative is dependent mainly upon how internal employees perceive the change.  Similar to any other digital transformation initiative, RPA is also bound to cause apprehension among impacted employees.

While some team members may follow a cautious approach for any recent change, others may like to debate the relevance of change. Moreover, there could be a fear of job losses, change of roles, the transition to a new team, anxiety around lack of training to supervise any new tool, and more.

A robust change management plan includes addressing these fears and anxieties, upskilling and reskilling impacted teams, setting up a robust governance framework, providing the necessary knowledge to groups about the positive impact that RPA will bring for the business. The technology heads and project leads should encourage people to ask relevant questions and engage them through focus group discussions or one-on-one interactions to understand the objectives behind the RPA implementations.

#5. Make sure to conduct the pilots

Any automation process is a long-term journey and needs sustained efforts for success. Do not expect to gain immediate benefits by deploying software robots. It’s a continuous process and needs several pilots before you ultimately obliterate any process-related obstacles or iron out flaws for a smooth run. It is advisable to have a multiple-phase rollout if the process spans several business operations geographies and impacts people from across teams.

Planning for pilots is one of the essential steps to any successful RPA implementation. Pilot implementations of RPA provide an excellent operating overview of the control frameworks, governance structure, and training to ensure that objectives align with expectations; remove reserves, if any;  and get buy-in from key stakeholders.

The growing web of digital payment frauds

The growing web of digital payment frauds

The rapid maturing of digital technologies and contactless payments have made lives of businesses and consumers easier. During the pandemic-stricken, confined ecosystem, enterprises quickly moved to digital and incorporated new digital payment and supply chain models. Consumers were also quick to shift to new behavior patterns and replaced in-store shopping with online shopping. Along with merchants and consumers, cybercriminals switched to new ways as well to expand their malevolent and fraud activities.

The upsurge in the online ecosystem is likely to create a brand new generation of digital customers in 2021. As digital experiences continue to become mainstream, cybercriminals are sensing an unprecedented opportunity to use new tricks and technologies to weave a deep fraud web around the gullible people and vulnerable IT networks.

Pandemic fueling fraud surge

By leveraging the latest technologies and network vulnerabilities, fraudsters explore new ways to target individuals and enterprises who lack adequate knowledge or cybersecurity tools to defend themselves.

Consider some statistics to understand the gravity of the situation: India witnessed over 2.9 lakhs cybersecurity incidents related to digital banking in 2020 (Source: CERT-In); a few months back, grocery delivery major Bigbasket faced a data breach, revealing data of 2 crores of its registered users; according to various industry reports, data breaches cost Indian firms Rs 15 crores yearly on average; FICO, a US analytics company revealed that four in five Asian banks are losing money to fraud as real-time payments rise.

The above data is just the tip of the iceberg. With the pandemic as a backdrop, digital payment frauds can upsurge even further.

Unified Payment Interface (UPI) emerged as one of the easiest ways to transfer money through Google Pay, Paytm, PhonePe, Freecharge, and others. This trend, however, also gave birth to various frauds associated with UPI payments.

The situation’s enormity can be fathomable as fraudsters didn’t even spare the Delhi chief minister’s daughter, as reported by various media outlets recently. She recently fell victim to an online payments scam while selling a piece of old furniture on an e-commerce platform. Last year, an Indian Air Force officer too fell prey to one such scam. The UPI-related frauds are even more concerning as India target massive uptake of digital transactions in the next few years, up from the current 46 billion.

There are also instances where users have fallen victim to fake shopping websites and transferring money by relying on unauthorized payment links received through SMS.

In one of the advisories issued in 2019, the Reserve Bank of India had warned all banks to take robust measures to prevent digital banking frauds that can wipe out the entire balance of a customer using UPI technology. With the more users connected to the mobile and the internet, such incidents are ordained to increase.

AI, ML, and user awareness

It is reasonable that most new customers moving to digital payments lack the knowledge and can be tricked by fraudsters to make security mistakes or provide sensitive information about their accounts. It becomes essential for enterprises and banks to take the necessary steps to combat digital payment frauds in such a scenario. (See: AI in banking now geared for a takeoff)

Enterprises and banks overhauling their payment and customer interface mechanisms by integrating digital pieces need to embed technologies such as machine learning and artificial intelligence to provide a secure and frictionless payment experience to customers.

By leveraging AI and ML algorithms’ competencies, the network can flag anomalies and derive a risk pattern, approving or declining a payment. In the year ahead, AI-enabled virtual chatbots will also play a pivotal role in enhancing user awareness and answer all payment-related queries. Enterprises are also testing predictive and prescriptive analysis to identify fraud in digital payment transactions.

There is a strong need for the industry to come together and make appropriate investments in next-generation security frameworks, real-time fraud monitoring solutions, and knowledge sharing programs to outsmart cybercriminals and strengthen consumers’ confidence in digital payments.

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