Over the past few years, the banking industry has witnessed a new wave of digital transformation. Virtual banking, for example, has become more popular in many regions. Other digitalisation trends such as open banking, RegTech, AI and data-driven decision-making, to
name a few, are in the headlines.

In addition, the Covid-19 pandemic is changing the way that banks and customers interact. Today, retail banking products are very much commoditised, with interest rates and other features of bank offers proving similar between them. FinTechs and TechFins have therefore emerged to bring new and better customer experiences to their incumbent counterparts. Customer expectations have also been changing, and customers are seeking digital, seamless, fast and integrated services more and more. Thus, on the other side of the table, banks are not left with much choice but to undertake necessary digital transformations to meet
expectations.

Many retail banking transformations are taking place in the market. In the broad sense, we can categorise them into three types: (1) moving from product-centric to customer-centric (i.e. to have more and faster customer interactions, to offer more personalised services and advice, etc.), (2) automating end-to-end services (i.e. adoption of technology for on-boarding, e-KYC, risk management, internal controls, etc.), and (3) enabling big data analytics and data-driven business decision-making.

In this article, we focus on the second and the third categories. In particular, we dedicate this article to the discussion of credit scorecards, as one of the major tools for data-driven risk management and business decision-making. We will review traditional scorecard development methodologies and then discuss the latest trends.