Tikhnadhi Kamlakshya On How AI & Cloud Integration Are Reshaping Financial Services

According to the latest data, the financial services industry has one of the highest AI adoption rates in the USA. In fact, estimates show that by 2025, more than 95% of new digital workloads will be deployed on cloud-native platforms, up from 30% in 2021.

There are many reasons why these tools are becoming more widespread: they can help financial institutions meet changing compliance standards, improve employee productivity rates, and considerably enhance customer experience and satisfaction.

For Tikhnadhi Kamlakshya, a senior manager at a regional bank & financial institution, AI technologies, and cloud integration tools can be utilized most effectively in fraud detection by highlighting real-time data irregularities and enabling scalable, adaptive solutions.

Introducing Tikhnadhi Kamlakshya

Tikhnadhi Kamlakshya is a sr. manager for Cloud Mix — Innovation & Modernization

at a regional bank & financial institution, focusing on enterprise transformation and cloud management.

Kamlakshya's first major project was migrating a legacy enterprise communication tool to MS SharePoint for a multi-national electronic & engineering company, where he learned first-hand the importance of aligning technical execution with organizational goals. More recently, he has been leading mainframe-to-cloud migrations at a regional bank & financial institution.

In a time where 52% of Americans are more concerned than excited about AI, Kamlakshya is a strong advocate for leveraging AI technology to create scalable, impactful solutions in banking. His professional aspirations are centered around harnessing multimodal language models to automate fraud detection and eligibility assessments in mortgage underwriting, which will improve the process for everyone.

However, to make this possible, the challenges associated with this transition must be properly identified and addressed.

Challenges In Cloud Migration

Technical hurdles are one of the most significant challenges associated with cloud migration. Enterprises are increasingly moving away from inefficient and expensive legacy systems towards cloud modernization, with 40% of organizations citing data security as a primary driver for migrating their legacy systems to the cloud. While 97% of leading enterprises have active plans to migrate parts of their legacy applications to the cloud, only about 28% have successfully done so, with more than 30% of organizations still running systems over two decades old. Given these challenges, it's not surprising that over 50% of organizations prefer an incremental approach to migration, tackling the process step by step rather than attempting a wholesale transformation. One reason why integration is challenging in this regard is the fact that many legacy systems use outdated programming languages.

Migration is made even more complicated when you consider the fact that legacy systems may predate certain standards (or be somewhat outdated), such as Sarban Oxley Audit and ADA standards.

Challenges in cloud migration can also arise due to more typical workplace issues, such as keeping stakeholders aligned on transformation goals, debates over capital vs operational costs, and shifting workplace priorities.

There's also a certain level of operational risk due to the steep learning curve associated with new technologies — especially if the legacy systems have been used for some time. In fact, 49% of business owners consider employee 'resistance' and lack of technical skills to be the most significant challenges when it comes to digital transformations.

Overcoming Challenges

Kamlakshya believes that proactive and strategic leadership is the best approach to overcoming these challenges. By providing continued guidance and support, he ensures that his team can confidently tackle problems while also adhering to compliance standards and best practices.

A key part of his success in this area comes from hosting iterative design sessions for employees so that they understand the changes being implemented ahead of time, ensuring alignment and helping to overcome resistance.

Finding Success

A State Government Agency

When working for a state government agency, Kamlakshya oversaw the development of a cloud computing & service provider, making it the first agency in the state to adopt a cloud-based application. This change was initiated to generate printed court invitation notices for appeals.

He developed a microservices framework to connect a cloud computing & service provider with the institution's legacy systems, enabling compliance with state-mandated formats for court notices. This helped bridge the gap between the cloud and legacy platforms by allowing for a gradual transition instead of making the changes all at once.

He also introduced a solution to package and queue printed documents, which allowed for seamless communication between traditional and digital platforms.

A Regional Bank & Financial Institution

In his current role at a regional bank & financial institution, Kamlakshya has played a critical role in advancing the digital engagement strategy, especially when it comes to leading the migration from legacy systems to a cloud computing & service provider and Amazon Connect.

This has allowed the bank to create a seamless, trusted platform for client-loan officer interactions. One of the most significant benefits of this shift is the increase in productivity for loan officers. With their previous outdated systems, they could complete an average of just 15 applications per hour.

They can now complete 60 to 80 applications within the same time frame while prioritizing high-value loans, thanks to Kamlakshya.

A Vision For The Future

Kamlakshya believes that cloud migration and AI technology will play a significant role in the future of financial institutions.

AI in Banking

The number of financial institutions investing in AI is growing all the time. Based on this and the growing capabilities of the technology itself, Kamlakshya predicts that both generative AI and predictive AI will be heavily relied upon to streamline processes and reduce human error.

Moving forward, he plans to leverage multimodal language models (models trained on large datasets of both textual and non-textual data) so that they can be used to prioritize applications, automate fraud detection, and provide data-backed, actionable insights to a wide range of consumer banking personnel, such as underwriters, auditors, and advisors. These tools can be used to quickly and accurately analyze documents such as loan applications and detect unusual patterns in data, making them invaluable in the industry.

Customer-Centric Innovation

Kamlakshya believes that AI-powered personalization will drastically change the way people use their banks. For example, AI tools can analyze customer behaviors like saving patterns or spending habits and signpost them toward relevant services, such as wealth management support.

Long-Term Impact

In the long term, Kamlakshya believes in fostering financial inclusivity by democratizing access to advanced banking services through AI and cloud integration, which make the relevant platforms more accessible. This gives account owners access to a wealth of tools and insights that allow them to improve their financial standing by helping them figure out the steps they should take to improve their credit score, their chances of being granted a mortgage, and more.

Final Thoughts

While there are challenges to AI adoption and cloud integration within the financial services sector, they are outweighed by the many benefits of utilizing these tools.

Tikhnadhi Kamlakshya's 21 years of experience have given him the skills, background, and passion to continue leading innovation in AI and cloud integration for the financial sector. His core goal is to use these tools to improve the day-to-day work of underwriters by reducing processing time and enhancing accuracy so they can prioritize high-value tasks.

BDG Media newsroom and editorial staff were not involved in the creation of this content.