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Data, Analytics and AI in Financial Services

Customers want personalised, smooth journeys across the channels

As I looked through my online bank statement, I noticed an irregular service fee and immediately knew that this was an incorrect fee! So, I called the bank as the chat bot could not help and there was no other online means for sending this particular request digitally. I was skeptical that my call would be answered as this happened in the midst of COVID-19 circuit breaker, but it did get connected to the bank. The bank had been agile enough to provide the infrastructure required for working from home to its staff including to the contact center agents. I made my requests and was relieved that the matter had been closed.

However, this was not the end of my experience. I could not see the waiver of incorrect fee in the subsequent bank statements. So, I called again and finally got the waiver. Clearly the bank processes, customer engagement and analytics were broken which made it charge incorrectly and took more than required time to rectify. Forget the personalisation, it could not even offer a frictionless journey.

Customers want personalised, frictionless journeys as they rely more on digital products/ channels for their banking needs.

Financial services could experience higher risks as COVID-19 continues

The economic aftermath of the coronavirus pandemic is likely to worsen when authorities start rolling back relief measures - and banks could experience far more damage to their balance sheets. - Piyush Gupta, group chief executive of Singaporean bank DBS

Singapore banks have large loan portfolios across the corporate, consumer and SME segments. There is a heightened need to address the increasing credit risk as a result of Covid-19. No longer can the banks rely on the antiquated credit models for underwriting and stress testing.

Data, analytics and AI in the new normal

Banks are moving towards open banking, providing access of their data to third parties and vice versa, to leverage the hyper-connected customers and ecosystems. There has been an exponential growth of data within the financial services organisations as their products have increased and channels have multiplied resulting in mountains of structured, semi-structured and unstructured data including voice and text data. Data silos are widening and the traditional data warehouses, data marts are not able to cope up with the rising demands of harnessing the power of data.

Financial services organisations are acutely aware of their need to translate the data into insights and actions not only for customer experience differentiation but also for mitigating risks and frauds. Embedding data across the organisation has become an imperative for driving higher business value and for acquiring a distinct competitive advantage.

We are presenting an overview of how your data can be collected, integrated, stored, processed, analysed and modelled in a secure and compliant manner for actionable insights leveraging strategy, governance, platform/ SaaS, ML/AI and visualization tools.

Data, analytics and AI in Financial Services, Quantaleap

Changing the DNA of your organisation towards the one that is customer centric and data driven is a large, complex and multi-year exercise. The organisations who are ahead in this journey understand that the business, technology and people should come together for realising a successful transformation.


This publication is a part of our comprehensive point of view and approach on Data, analytics and AI in Financial Services. Please contact with us for a complete discussion.


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