DigitalTransformationTalk: WEF Special Episode – Delivering digital transformative change in banking with Microsoft

On 18 January 2024, Digital Transformation host Kevin Crane was joined by Peter Hazou, Director, Business Development, Financial Services, Microsoft; and Paul Hewitt, Director and Head of the Data, Analytics and Machine Learning practice, DXC.

Views on news
Fintech is not threatening the market position of big banks but makes competition between them fiercer. So, big banks must figure out where innovation can have the most impact on their competitiveness. Therefore, to mitigate opportunity risk, banks must experiment while also maintaining guardrails. Visibility of where and what type of AI is used is becoming key to safeguard a bank’s reputation. The stellar rise of genAI has speeded up regulation too. However, non-generative AI has been infused in banking for a long time. AI is changing banking on two vectors – business model and business operations. A shift is taking place as banks start thinking of AI not as a technology of the future but as part of how they operate. 

 

Leveraging data in the cloud with the help of AI
DT in the banking sector is till progressing relatively slowly. This is partly down to traditional banks being large organisations where managing change is an extremely complex task. It’s usually not great shifts such as cloud migration that stand in the way of successful transformations but more basic inefficiencies – processes are not documented properly and are too manual. What makes a difference is leveraging the contextual and predictive potential of data. With the cloud, banks can better focus on their core business (about 100 years ago banks generated their own electricity). The less complex a system gets thanks to a unified source of data or standardisation, the more efficient the IT system will be. Start-ups’ edge is in having simple systems. 

When seeking to make a bank futureproof, the focus should be on its operating model. Futureproofing should be an ongoing effort. Embedded finance, where banking gets to the heart of the economy is the area where the biggest changes are to be expected, as well as the way in which banks are going to leverage data they’ve captured. As a result, bank should manage a data lifecycle the way they have done with managing their software development, so they can demonstrate to auditors what data has been used to train a model that has made a particular decision.

 

Partnerships are extremely important for banks. A bank’s vendors after procurement should ideally  become partners in their ecosystem. 

 

The panel’s advice

• The successful implementation of technology should be measured through business performance metrics.  
• The key to futureproofing banks is an experimenting mindset and the ability to change as the environment changes.
• You must treat your vendors and counterparties as your partners.
• Banish silos. Data is an enterprise-wide concept.