Delivering Enterprise-Wide Innovation at DBS Bank
Lessons Learned from the World’s First Digital BankAdd bookmark
The largest bank in Southeast Asia, DBS Bank has emerged as a digital banking pioneer and trendsetter. In fact, over the past few years, DBS has been awarded numerous accolades for its cutting-edge technological endeavors and, in 2019, was ranked as one of the top 10 most transformative companies by Harvard Business Review.
DBS’s digital transformation story began a bit over 10 years ago when they attempted to overhaul their core banking system. However, things didn't go exactly as planned. Not only did the project exceed its budget and fall significantly behind schedule, it was ultimately deemed technologically unfeasible.
In the face of crushing failure the DBS team decided it was time to rethink their approach to technological innovation. Instead of looking towards its BFSI peers, DBS started drawing inspiration from tech companies on how to transform digital assets into competitive advantage.
“At the beginning of our digital transformation journey in 2009, we recognized that if we wanted to be digital to the core and act like a tech company, we needed to learn from the best in the business. These were Google, Apple, Netflix, Amazon, LinkedIn and Facebook [GANALF]. Our mission was to become the ‘D’ in GANDALF,” Bidyut Dumra, Head of innovation at DBS, recently explained to the Banking Innovation Awards’ online publication.
“To reimagine banking, we re-wired the organization to have a startup culture and mindset. We established experiential learning platforms, introduced new ways of working, re-designed office spaces, and fostered ecosystem partnerships to encourage our people to embrace a spirit of experimentation and innovation.”
Today we’d like to take a look at 4 key factors that have enabled DBS’s remarkable digital transformation.
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Continuous Integration and Continuous Delivery (CI/CD)
Continuous integration and continuous delivery (CI/CD) refers to a set of operating principles and practices that seeks to accelerate coding processes by incorporating automation into app development. Also considered an agile methodology, CI/CD, according to RedHat, “introduces ongoing automation and continuous monitoring throughout the lifecycle of apps, from integration and testing phases to delivery and deployment.”
By adopting a CI/CD approach, DBS was able to develop, deploy and modify new applications significantly faster than ever before. Fast forward to 2017 and DBS proudly announces that, with 155 plug & play APIs (application programming interface) in production, it is the world’s largest banking API platform.
As of January 2021, DBS has over 200 customer-facing APIs that can be used by business clients to support everything from mobile payments to loyalty programs.
The two things banking customers need more than anything else is speed and accuracy. Realizing that manual processes would only take them so far, in 2017, DBS partnered with IBM to develop an RPA COE to spearhead and govern the development of new, transformative RPA solutions.
Using RPA, DBS has been able to automate over 100 complex business processes in, amongst others, compliance, risk management, and human resources. In April 2020, it was announced that DBS was hiring JPM alum Mark Siaw as COO for middle office technology. Given his extensive experience in RPA, this choice could indicate, at least according to some experts, an increased investment in RPA and intelligent automation (IA)-powered innovation in years to come.
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Implementing Data Analytics & Artificial Intelligence at Scale
Data, at least financial data, is the cornerstone of any successful financial institution. However, though banks might be adept at transforming market data into profits, when it comes to leveraging customer data to deliver better financial products and services, this hasn’t always been the case.
Back in 2017, DBS realized that despite their expansive data infrastructure one major obstacle prevented them from scaling advanced analytics and, consequently, AI: data silos. With the intention of fully democratizing data analytics and AI, they decided to completely redesign DBS’s data architecture.
The end result was its first data platform-as-a-service called Ada.
“Ada stands for ‘Advancing DBS with AI. That is our ambition for this platform, we want this to be truly self-service so we can empower every employee of DBS to use data and AI” Soh Siew Choo, Managing Director and Group Head of Consumer Banking and Big Data, AI Technology, at DBS told CIO magazine. She added, “we want every single developer in the bank to become a machine learning engineer having created this platform from an open source solution – we curated the whole solution from scratch within the bank. Today it’s serving hundreds of users ranging from data scientists to data engineers and data analysts.”
As of 2019, they had at least 150 advanced analytics projects up and running, many of which were designed to deliver hyper-personalized product recommendations and financial guidance to customers. Furthermore, since the start of the COVID-19 pandemic, over 33,000 customers have embraced the bank’s fleet of intelligent banking apps to make better financial decisions. For example, the bank’s iWealth wealth management app uses AI to recommend stocks based on a customer’s individual investment portfolios or notify them about favourable foreign exchange rates in their trading accounts.
People First Digital Transformation
Early on technology leaders at DBS realized that long-term digital transformation success hinges on the human element. As a result, ensuring all employees across the enterprise were upskilled and engaged in the innovation process was a core component of their transformation strategy.
To start, DBS brough innovation “home” by insourcing innovation. Now 85% of IT employees are inhouse vs. 15% a decade ago.
Next, DBS launched a series of innovative training initiatives to ensure everyone across the innovation pipeline, from developers to business users, was fully prepared to embrace and capitalize this new normal of continuous innovation.
For example, in August 2020, DBS partnered with AWS to develop a cutting-edge, racing-themed training platform designed to equip business users with foundational AI and ML programming skills. Using gamification modules, participants basically build and race autonomous vehicles.
As DBS' chief data and transformation officer Paul Cobban explained to ZDNet, “we have never believed in limiting digital expertise to a small team. Instead, we passionately believe in democratising technology skillsets amongst all employees, so that they can run alongside the company as we advance on our digital transformation together.``
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The key for global corporate enterprise is to benefit from the collective intelligence presented by RPA and cognitive technologies along with human workers. Only by having technology combine with human talent can global corporate enterprise achieve scalable intelligent automation. And only with scalable intelligent automation enterprise resiliency be realized. Join that community for lessons learned at SRIA Live.
Scalable RPA & Intelligent Automation Live
The key for global corporate enterprise is to benefit from the collective intelligence presented by RPA and cognitive technologies along with human workers. Only by having technology combine with human talent can global corporate enterprise achieve scalable intelligent automation. And only with scalable intelligent automation enterprise resiliency be realized.
Join that community for lessons learned at SRIA Live.Register Now