The world and its technology are moving faster than ever and the narrative of “evil” fintech companies eating the revenue streams and replacing traditional banks has long since died out. In fact, Fintechs and Banks are coming together more than ever to define an advanced, ever-evolving financial infrastructure and better customer journeys.
In a recent webinar panel hosted by S&P Global Market Intelligence, industry experts Alina Timofeeva Principal Olivier Wyman, Conrad Ford Chief Product Officer, Allica Bank, and Napier’s Chief Data Scientist Dr Janet Bastiman discussed ‘How fintechs are reshaping the banking industry’, moderated by Sophia Furber, Research Analyst at S&P Global Market Intelligence.
Here are the key insights from the panel discussion:
Are banks really the dinosaurs of the technological age?
The idea of traditional banks with siloed processes is gradually fading away as the financial landscape undergoes a significant transformation. Conrad Ford pointed out that the success of traditional universal banking models was predicated mostly on one aspect: the proximity of their branches to customers. This paradigm is now shifting as banks move from providing everything to everyone; the model that served all the way from the smallest consumers to the largest corporates and governments with loans, cash, savings, insurance, payments etc all together, to ours and our parent’s generation. In the post-pandemic world, the pace of these models dying is even faster as they evolve with more focus on their products and services.
Shifting from the processes and technology banks have been operating on for decades can be difficult. Trying to mass together the fragmented pile of data banks are sitting on to gear up for innovative, transformative changes from the siloed legacy approaches is a big hurdle in the transformation process.
Doing digital transformation right
According to recent statistics, 70% of digital transformation projects fail to achieve the business outcomes they were intended for. So, how do you do it right?
Alina shared one of her client’s recently remark, "I know that 50% of my digital transformation spend is wasted, but I don't actually know which 50%." The key is to understand and analyse why you might be failing first, and tying these to a business strategy.
Cultural shifts and moving away from legacy systems and processes might be particularly difficult for large and institutionalised financial institutions. ‘Smaller empowered teams who are the best in their jobs will outperform larger transformation teams’ noted Conrad.
Ultimately, the success of any digital transformation project depends on the bank itself, and how primed it is for innovation. In a world where Artificial Intelligence (AI) is powering up and evolving processes in less time, larger projects that span a couple of years working with siloed filing cabinets might turn redundant by the time they’re implemented.
There’s a need to replace behemoth multi-year innovation projects with faster proof of concepts and agile practices. Many banks are successfully doing this by partnering with fintechs to enhance their technological capabilities, internal efficiencies and to improve their speed to market.
Dinosaurs evolving into fast, flexible birds: The power of AI
Janet Bastiman remarked; while the analogy of legacy systems and universal banks becoming extinct soon might hold true, they aren’t being completely wiped out yet: Some have just evolved into faster, more flexible birds by embracing agile technologies and AI.
Human beings are limited in many ways, particularly in how we analyse data. But with some of the deep behavioural analytics, and graph-based networking that AI provides, especially in the regulatory environment where there’s a need to amass millions of data points to analyse financial behaviour, banks that have adapted agile practices are thriving.
People are now using AI predictive texts to make their lives easier- completing email sentences or paraphrasing an assignment. While these technologies enhance and supercharge the way we work, it is also important to know how best to use it in a way which is both safe, optimal and effective. Janet advises anyone who is using advanced technologies like generative AI not to indulge in sharing any sensitive or confidential information online (unless you have downloaded one of these models and it's entirely within your network). When using such models, it is crucial to loop in factors like accountability, oversight, transparency, data privacy, security and bias into the system and model data.
In the world of financial crime compliance, where the outcomes of your actions are potentially blocking financial transactions, it is crucial to have measurable, accountable activities which do not impact marginalised customers negatively. Janet explained this as using ‘AI for not bad’ if not ‘AI for Good’.
Understanding the consequences of the gaps, biases and quality of your data clearly to define what you should and shouldn’t build is absolutely critical. When the algorithms used to train the system are not sufficiently diverse, inaccuracies and unfairness in identifying individuals creep in.
AI should also be explainable- not just to the data science team but also to the compliance officers, the tellers of the bank and the decision makers in the end. This needs weaving human in the loop, and building ethical practices from the beginning so that there’s a fair and auditable AI program.
Through strategic collaborations and investments, banks are now harnessing the innovative potential of fintech companies and the power of AI. The results of these partnerships are promising as they are revolutionising the way we access, manage, and interact with financial services, and ultimately creating a more efficient, inclusive, and customer-centric financial ecosystem.
Interested in these insights?
Watch the full webinar replay here
