When it comes to banking, there is a major disruption happening. The FinTech ecosystem in the nation has matured considerably and banks like RBS have taken a lead in staying abreast of all the advancements in analytics and AI.
To know more about the bank’s analytics unit and its roadmap for the coming year, we got in touch with Arun Mehta, Head of Data & Analytics – Digital Engineering Services at Royal Bank of Scotland (RBS). In this article, we shall also cover how Mehta has played a pivotal role in architecting RBS’s operations in India.
Arun Mehta has played a significant role in transforming analytics function at RBS India. His day-to-day role and responsibilities include leading the data and analytics engineering platform related deliveries ranging from regulatory commitments to enabling analytics and data tools enablement for data science activities.
Since the get-go, he has been involved in multiple projects and flagship strategy programs to deliver stakeholder value by optimising the entire value chain of data that spans across optimized data sourcing, simplified data architecture, optimal data platforms for varied needs of elasticity of compute & storage and to enable appropriate and cost-effective tooling for reporting, analytics and data science activities.
Analytics Tech Stack
Talking about the technology aspect at RBS India, the bank has been using analytics extensively to improve operational efficiency and internal processes. He reveals analytics had been prioritized for improving digital customer journeys, gaining a better understanding of customer experience & behaviour, improving the effectiveness of due diligence processes and digital channel adoption. “Tech direction for us is geared up towards embedding analytics for insights and decision making using the near time mode of data procurement. This is intended to enable contextual and personalized customer offerings and experiences,” said Mehta.
At RBS India, analytics is embedded within both functions and works as a separate unit. Also, the models are prevalent with central data and analytics guiding new design patterns, technology strategy, new ways of working and future data strategy.
Furthermore, when asked about RBSs’ way of hosting data, Mehta said that the bank has a robust security framework, control groups and a decision tree protocol basis which it decides the placement of workloads into different data hosting platforms.
“In my view, any cloud cases would be considered basis the need for the elasticity of compute, cost efficiency opportunity and faster time-to-market. We have a strong intention of enabling analytics workloads on elastic compute cloud ecosystem,” Mehta added.
The Hiring Phase
Being an analytics-driven bank, RBS India ensures the team attracts the best talent that is well-versed with all the nuts and bolts of analytics. “We are always on a lookout for deserving and promising candidates to join our group,” said Mehta.
Talking about the key capabilities required for an analytics professional to join RBS India, Mehta said that there are certain things that a candidate must have to be a part of RBS India’s analytics domain. Some of the key capabilities required for analytics professional range from softer aspects like open mindset can-do attitude, innovative traits to essential skills ranging from data engineering, data science, cloud computing and knowledge of analytics.
While banks like DBS, ICICI, Axis have built a partner ecosystem with startups and have been building innovative solutions, RBS India is in the process of establishing a partner ecosystem with STPI and NASSCOM CoE. According to Mehta, the motive behind it is, “To potentially co-create artefacts for the industry as well to assess the FinTechs as endorsed by them to address some of the pain points and prompting business outcome use cases.”
Going forward, Mehta believes that the key trends that will see impacting FSI in India are analytics, cybersecurity, API driven architecture, cloud computing, digital integration with the customer journey and last but not the least artificial intelligence and machine learning.