The Beginning – Discovering a Foreign Field:

Samik Chandarana, now Chief Data and Analytics Officer at JP Morgan, never planned to enter the world of finance. His journey in fact began far away from the trading floors of London, in the vibrant music scene at Manchester University.

Deeply involved in the techno genre, by the late 1990s, Samik and his friends even released an album, Loop 82 – The New Style Swing, which can still be found on Spotify today.

Although music was his passion, financial pressures took him down a different path. After completing an engineering degree, followed by a master’s in engineering, psychology, and management, Samik struggled to sustain his musical ambitions and found himself in a number of odd jobs. One of these jobs, working as a product controller at Chase Manhattan Bank (a predecessor to JP Morgan), would prove to be a turning point in his career – admittedly, Samik only joined the bank, not out of a passion for finance, but rather for financial stability so that he could pursue his music career.

However, it was not long before he realised that his future lay not in music, but in the world of trading. His proficiency in technology gave him a unique edge over his coworkers and he soon found himself well ahead of the curve. Samik was also gifted with an eye that would quickly analyse risk in trading credit products – such as bonds and credit derivatives – which helped him move from being a trader assistant to becoming a full-time trader, bypassing the traditional graduate scheme entirely.

From Credit Derivatives to Head of European Trading:

As Samik honed his skills, his career gained momentum. By 2001, he had joined a small team responsible for creating credit indices[1], a groundbreaking innovation that has since become one of the most heavily traded financial instruments globally. Within a short time, Samik and his team earned recognition as the top ranked credit trading team in the world, known for their blend of technology-driven creativity and strong customer service.

Samik believes curiosity is a key driver of success. “While you can certainly develop curiosity, as a natural trait it separates you from the rest. You’re never satisfied.” This allowed him to rise through the ranks, ultimately becoming the head of European credit trading – a role traditionally reserved for those who had followed the conventional path through graduate schemes.

Perhaps one of the most pivotal moments of Samik’s career was trading during the 2008 financial crisis. Being one of JP’s main market makers for credit indices, he navigated the turbulence of the global financial system, even suffering the significant loss of over $10 million in a single day. Fortunately, this revealed a key lesson in the industry: failure is common. However, what truly characterises a great trader is not their worst mistakes, but rather how they build themselves back up.

In Samik’s case, I believe his ability to learn and grow from the experience speaks volumes about his quality as a financial expert.

The Shift to AI and Data Science:

While Samik’s career as a trader continued to grow, his interest in artificial intelligence began to take shape around 2014. As technology transformed industries across the globe, Samik was convinced that AI would reshape the financial sector. He started using AI for better comprehension and analysis of market dynamics, mitigation of risks and optimisation of trading strategies by initiating the integration of machine learning algorithms into the trading space back in 2017.

Recognising the potential of these algorithms, Samik drafted a white paper[2] to JP Morgan’s leadership, advocating for the establishment of a data science infrastructure within the firm. His bold vision led to his appointment as JP Morgan’s first Chief Analytics Officer in 2018, marking a career shift from trader to technologist. By 2021, Samik had taken on the broader role of Chief Data and Analytics Officer for JP Morgan’s Corporate and Investment Bank (CIB), tasked with utilising AI and data to drive innovation in the firm.

One of the most transformative initiatives Samik oversaw was the use of AI to automate and optimise routine financial processes. A prime example is reconciliation, a task that ensures all transactions are accurately reflected across multiple systems. Previously, large teams of employees handled this task, but Samik’s team replaced it with AI-driven programs which brought costs down and hugely improved efficiency.

On the other hand, Samik does note that not all processes can be automated so easily. Complex tasks, such as matching payment flows across disparate systems[3], require a higher level of AI logic and extensive testing to maintain accuracy and reliability. This suggests that trusting algorithms implicitly and entirely removing human supervision would be concerning oversight.

AI’s Role in the Future of Trading:

With the financial sector only growing in regard to data-driven developments, Samik is on the forefront for AI implementation in trading. He envisions a future where many of the mundane, manual processes of financial operations are fully automated by AI systems. 

AI plays a crucial role in analysing large quantities of data today, allowing traders to make more informed decisions at a speed that was previously unimaginable. Competitive advantages can be created in financial markets by processing behavioural data and making real time trades using AI. By identifying patterns and predicting price movements and trends with improving accuracy, traders are able to recognise opportunity from the first time in far more promising and volatile markets.

Despite the optimism surrounding AI, Samik emphasises the importance of rigorous testing. AI systems in finance must adhere to strict regulatory standards and pass through multiple layers of scrutiny to minimise the risk of catastrophic errors. Moreover, he remains cautious about the current state of artificial general intelligence ,or AGI[4], admitting that, “[He is] not yet a full believer in AGI”.

He is optimistic with regard to AI potential and capability to execute tasks that are a repetitive and structured, calling for substantial human input. However, he explains that “we must be very careful before deploying any AI-based systems, because the consequences of failure are usually severe”. This is because the financial markets and regulatory oversight are so convoluted that nothing but a robust framework can be put in place to develop and implement AI.

Advice for Aspiring Finance Professionals:

This unconventional career path that Samik has taken offers an abundance of teachings for those aspiring to enter the world of finance. His journey highlights the importance of taking calculated risks, nurturing curiosity, and continuously adapting, whether it be to new technologies or failures along the way.

Reflecting on his own path, Samik wishes he had taken certain risks earlier in his career. “Choosing who you work with is as important as the work itself,” he advises. In addition to curiosity, Samik stresses the importance of empathy, logic, and creativity in problem solving – qualities that are becoming more and more important as machines take over more analytical functions.

Samik also points out that degrees in traditional finance subjects are helpful but not the only ways into banking. Graduates from fields as diverse as classics and computer science have excelled in the past. What matters most is the ability to think critically, solve complex problems, and adjust to a rapidly changing world.

AI & The Future of Finance:

AI is going to further revolutionise the financial industry and transform the operations of all institutions.

For people looking to be successful of the finance industry, understanding AI and its applications in finance is no longer optional – it is essential. Those who can combine financial knowledge with technological confidence will find themselves at the forefront of this new era in banking.

Samik’s journey from a techno DJ to an AI-driven finance leader demonstrates that success in finance today is not just about mastering the numbers but instead about staying ahead of technological trends and being prepared to take risks in pursuit of innovation.

References

[1] benchmarks that track the performance of a specific group of credit assets, like bonds or loans, reflecting the overall credit quality and yield trends in that market segment

[2] [in the context of trading] a detailed report explaining a trading strategy, product, or market analysis, aimed at educating investors on methodology, risks, and potential benefits

[3] the insurance to make sure payments processed through different systems align correctly, which enables accurate tracking, reconciliation, and reporting across various platforms

[4] the idea that machines could eventually replicate human reasoning across a broad spectrum of tasks