Banking and finance is a $28115.02 billion industry, and novel technologies such as Artificial Intelligence (AI) and Machine Learning (ML) are no longer futuristic concepts – but rather, present-day necessities. More now than ever, respected experts in the field such as Shiva Kumar Sriramulugari are highly sought-after when it comes to integrating these technologies across a variety of industries.

Shiva, a 2023 Globee Awards/Golden Bridge judge, is a seasoned professional with profound expertise in AI and ML technologies, marked by a rich career spanning 15 years across diverse domains including banking, finance, healthcare, and telecommunications. Shiva holds a Bachelor’s degree in Computer Science from Visveswaraya Institute of Technology and a PEGA LSA certification, and has distinguished himself as an innovative Solution Architect at Verizon. He is recognized for driving transformative solutions that enhance organizational processes and success, while also being an active IEEE Senior Member.

Shiva’s extensive experience encompasses business process analysis, domain consulting, and enterprise application design, and he is lauded for his adeptness in managing both on-site and remote teams to deliver high-impact projects, demonstrating a strong commitment to customer satisfaction and a passion for mentoring talent in the field of AI and ML.

With his expert understanding of AI and ML, Shiva is at the forefront of a new wave of technological innovation. While he’s currently working with Verizon, he’s spent time in banking and finance – and has firsthand knowledge of how AI can streamline operations, enhance customer experiences, and manage risks more efficiently.

“Like many industries, banking stands to be revolutionized by AI,” Shiva reveals. “My work in this sector saw the application of AI to transform banking processes. One area I focused on was process optimization, where my team and I used AI algorithms to develop systems to automate routine tasks, like data entry and transaction processing. This freed up human resources for more complex tasks.”

He says that in many sectors – not just banking/finance but in healthcare and telecommunications – automation is an integral way to increase efficiency and reduce the margin of error to ensure accuracy.

“I’ve also spent time applying ML algorithms to enhance fraud detection systems, which is a major concern in banking,” Shiva says. “Essentially, banks are caretakers of their clients’ assets. Imagine an elderly customer trusting their life savings to a bank, only to be hacked and robbed.”

He says that ML can analyze patterns in transaction data to identify anomalies that may indicate fraudulent activities. This proactive approach is crucial in an industry where security and trust are paramount. “Think about it,” Shiva says. “Say Mrs. Jones always shops at the same grocery store, and suddenly there’s a charge on her account for a grocery store in a different city, without any other transactions in that city to indicate that she’s really there. ML algorithms can catch those anomalies faster than humans and can protect customers from fraud.”

Shiva goes on to point out that AI/ML also have major implications in risk management within the financial sector. “We can use predictive analytics to assess credit risks by analyzing various customer data points,” he says. “These AI-driven models offer more nuanced and accurate risk assessments than traditional methods, allowing banks to make more informed lending decisions.”

He has also implemented ML models for market risk analysis. These models analyze market trends and historical data to predict market fluctuations – and this helps banks and financial institutions in better portfolio management and investment strategies.

“All of this really goes back to customer engagement and the customer experience,” Shiva says. “Where I’m working now in telecommunications, it’s no different: customer-centric solutions are a must.”

In the digital age, customer expectations are changing and evolving right along with technology. To address this, Shiva has used AI to personalize banking experiences, since AI algorithms can analyze customer behavior and preferences to offer tailored financial advice and product recommendations.

“I have worked to implement AI-driven chatbots and virtual assistants in banks, and I think this marks a shift towards more interactive and responsive customer service,” Shiva reflects. “These tools can handle customer queries efficiently, provide instant support, and they’re available 24/7, so that significantly improves the overall customer experience.”

Shiva’s application of predictive analytics extends to financial services as well. He uses AI models to analyze historical data and market trends to forecast future market movements. This helps financial advisors and clients make more informed investment decisions. This predictive capability is particularly beneficial in asset management and wealth advisory services.

“Another key area is compliance,” Shiva says, “which is a critical aspect of the banking and finance industry. We can use AI to streamline compliance processes, since AI systems can continuously monitor transactions and operations to ensure adherence to regulatory requirements. These systems can also quickly adapt to changes in regulations and reduce the compliance burden on financial institutions.”

Shiva also uses AI/ML to offer personalized banking services, tailoring financial advice and investment plans to individual customer profiles. “There are challenges in AI integration, like the need for robust data privacy and ethical AI practices,” Shiva says. “In the future I believe AI will transcend operational efficiency, driving innovation in financial products and services with a focus on technological advancement, customer-centricity, and ethical integrity.”

Learn more: https://www.linkedin.com/in/shiva-kumar-sriramulugari-96414221/