Data has been a hotly discussed topic in the banking world for some time now. And as firms learn to adapt to the latest Covid-19 pressure – whether that be new working environments or unprecedented levels of market volatility – the need for real-time visibility of their data has never been more important.
But when it comes to maximising the value of that data, there are still obstacles to overcome. At our recent invitation-only Banking Ruminari event, banking leaders in the cash management and treasury space discussed some of these challenges and how they can be tackled.
To explore this critical topic further I took the opportunity to sit down with David Christie, CEO of Bleckwen, a behavioural analytics software company working with banks and financial institutions, to get a data science perspective on the opportunities and challenges facing banks in this area.
DC: I think they are only touching the surface – they are guardians of our money, but also by proxy, they are effectively guardians of our identity and our risk profile – they need to leverage this more, possibly even monetise this – but obviously they need to do this in the right way. Data is tomorrow’s oil as they say – or more accurately, tomorrow’s money. And banks are sitting on a lot of latent value!
DC: Banks sit on an enormous amount of data, and generally are very good at protecting it, but are not really leveraging it as a complete asset like some fintechs to quickly generate new revenue sources or improve efficiencies and customer outcomes. Some of this is because they have stringent controls that inhibit their ability to move quickly with this data and some of this is down to the legacy platforms not being able to leverage it correctly.
DC: Privacy regulation has evolved to encompass consumer rights over their personal data – first in Europe’s General Data Protection Regulation and subsequently in the California Consumer Privacy Act in the United States. Consequently, the majority of financial services privacy executives have said they consider it a key material risk.
It stands to reason that firms need a privacy function with capabilities that are commensurate with this new status. Privacy, security and data risks are now interconnected and interdependent, but most financial institutions organize privacy, data management and information security as separate domains. This increases the likelihood that important responsibilities will slip through the cracks, which creates real risks for firms, along with potential costs.
Privacy issues increase as banks try to leverage data insights across their organisation and as collaboration between banks and third parties increases, additional efforts are required to protect the shared data.
Getting a complete grip on what data exists and where is a critical step, as is understanding how and why it’s being used, ensuring that the appropriate consents are in place and that people understand and are enacting the policies to protect it. Most banks have data siloed across their organisation with derivatives of this data being used across the business from BI to AI which increases the risk of misuse, lack of tracking and loss/breach.
DC: The ability to categorise and extract information from unstructured data so it can be used to enhance the customer journey is a difficult process but advances in image and document recognition and natural language processing (NLP) and understanding (NLU) provide an opportunity to transform these processes – from identifying fraudulent documents to extracting key information for risk management or operational efficiency improvements. Being able to integrate these new technologies into legacy platforms is probably the biggest challenge.
DC: Data here is critical in identifying risk levels as well as ensuring low levels of friction in the customer journey. Having the right levels of data enrichment to make quick and transparent decisions is critical in creating competitive advantage. Leveraging data to empower the client also improves the experience and reduces cost for the bank.
DC: The potential is enormous, but it is not an easy task. It requires next gen systems to be integrated into legacy platforms, data to be in a state where it can be leveraged by AI/ML and the skills available to implement and support this enhanced IT and data estate.
Banks need to improve the quality of their data and the ability for it to be consumed easily whilst maintaining privacy/security etc., whilst simultaneously being able to implement AI tech to leverage this new enriched data asset.
They also need to ensure that the models and data artefacts they create have the right level of governance, explainability and they are addressing bias and fairness in the right ways where applicable. Like any tool, AI needs the right policies and procedures in place to ensure they are being used in the right way.
But a word of caution – AI is not a silver bullet – it is just one set of tools that should be used and sometimes it’s easy to see everything as a nail when you have a hammer. In some cases, a simple rule or a statistical approach is a much better way to get a result at a better cost.
DC: COVID-19 has driven huge amounts of behavioural change. We are working from home more, conducting commerce more locally. We now do more online than ever which increases the contact points and number of events we generate. Our payment habits have thus changed where we use more contactless than cash etc, and it is probably accelerating things that were changing already but much faster. This means an ever changing data landscape which the bank needs to respond to whether that be in capacity on certain channels (like online/mobile etc), in its risk profiles to how it protects them and their clients (fraud and AML) and more importantly how they need to change their products at pace to react to their clients’ changing behaviours and needs. Behind this is how the bank operates and governs itself in an increasingly remote world - it’s a huge amount of change, which carries risk, but also opportunities to fast track digital transformations and product development for a “new normal”.
BW: Data clearly offers rich opportunities for product managers and their customers alike provided that they can overcome some of the practical challenges and get the right visibility and connectivity of their data in place. Thank you, David for sharing these illuminating points.
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