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Building a new ecosystem: A bank’s journey through sustaining digital transformation, understanding AI and managing the galaxy of continuous change
Journal of Digital Banking,
6
(1),
6-24
(2021)
Abstract
In October 2019, I delivered the keynote address to a room full of banking and financial services professionals on what to expect on a journey towards digital transformation (DT). At the outset I asked my audience if their business was in any of the following three categories — advanced stage of DT, somewhere in between or warming up to it. There was only one show of hand for ‘somewhere in between’, while the majority identified themselves as being at the starting stage. It did surprise me. Since then, however, the evolution towards DT has been rapid. Digital disruption has created a level-playing field for various ecosystems, with its own subsidaries offering services and generating real business value. If your business is an early adopter of digital disruption, then you already know the value, but if you are among the early majority, the conservative or even the sceptic willing to cross the chasm, I really hope that you can find at least one useful takeaway from this conversation. I am bringing the spotlight back to ‘where to start’, ‘why digital principles are required’ and ‘understanding and building your own strategy for data, platforms and machine learning’ to rebuild your organisation by facilitating the use of agile methods by important players across your organisation. Find your ‘why’ to connect customers, business and technology seamlessly through an opportunity well guided by data and machine learning.
Keywords: digital principles for banks; digital transformation; agile; machine learning; data strategy; platforms
The full article is available to subscribers to the journal.
Author's Biography
Nidhi Nikum is a banking service professional with over 18 years of experience, split between ‘building’ versus ‘running’ the bank. Her area of expertise is wholesale credit process transformation. She speaks regularly on the digital transformation (DT) of banking and advises on building a sustainable artificial intelligence ecosystem for DT. Nidhi has built software, led transformational business projects, mentored a large team of experts for enterprise data analytics and created a blueprint for risk services for an offshore centre. She has vast experience in core banking technology and Asian wealth banking products, validating risk models and methodology, implementing credit risk calculation engine and enterprise SaS and risk-weighted assets optimization, and building frameworks of customer data integrity. She has deep knowledge of business credit processes (from decision to execution using risk appetite, country risk, sector and product transaction guidelines, judgmental credit policies and requirements) and data life cycle across corporates, funds and the insurance and banking sectors. She uses her strong data proficiency to dissect systems, processes and policies to remove impediments and build solutions on limited budgets. As an accomplished enterprise architect and scrum master, Nidhi brings her main strengths of technology, credit risk and frontline wholesale lending experience to help heads of credit risk and capital reduce the regulatory capital by up to £180m and the cost of credit performance by about £500k per annum by leading the change through data strategy and DT. She often consults with FinTechs and is an avid reader on machine learning. Nidhi has a degree in engineering, professional certificates in machine learning and a UC Berkeley Executive Education on digital transformation.
