The Five Biggest Barriers to Banking Innovation and How to Overcome Them
In viewing the current state of the banking industry, it has become readily apparent that whilst innovation is challenging, it is also very much needed. Financial crime capture and control rates have effectively flattened since the early 2000s, and proportional estimates of financial crime in the market have remained equally unflagging (UNODC/Sidanius, 2019). Change is clearly needed, but innovation is incremental and sparse where it does exist. The question that must, of course, be asked is “What is preventing financial institutions from embracing innovation fully?”
1. Extreme Caution and Cultural Conservatism
For many banking executives, “innovation” and “technology deployment” mean complete disruption of their daily routines, and in some cases a reorientation of their role at an institution. These concerns over an uncertain future have been found to engender an understandable resistance to change and a fear that innovation will lead to redundancies (Bradutanu).
Of course, with an eye towards sustainability, not bottom lines, if properly implemented, innovations should focus on improving employee capability through the alleviation of trivial tasks. The purpose of any innovation should be the augmentation of an institution’s current workforce and the communication of that fact to all stakeholders involved. For example, by automating the work of conducting manual risk assessments, financial institutions are able to give their employees more time to focus on actual risk management.
2. Internal Communication Barriers
At modern international banks, solution implementation can become an exceedingly complex task, involving stakeholders across institutions and departments. During these transitions, clear decision making and goal communication become challenging, largely due to the number of moving pieces involved. As such, banking executives often report flagging enthusiasm and a lack of support for transitional processes when institutional goals and objectives seem unclear. SaaS FinTechs and RegTechs, on the other hand, find themselves in endless and costly Proofs of Concepts and Pilots where even meeting all pre-agree success criteria seem insufficient to drive clear decisions. In this sense, communication failures stand as one of the most substantial barriers that institutions seeking change must overcome.
Innovators in the banking industry must prioritise simplicity and iterative change when adopting innovative solutions. Keeping a focus on one goal makes communication and decision-making far easier, versus a complete structural reorganisation of a financial institution’s infrastructure.
3. Incentive Barriers
Financial institutions are complex, interconnected organisations, where even the most well-siloed reform processes often entail a lengthy and expensive disruption of multiple segments of the institutions, making coordination and alignment of interests a challenge (Bradutanu). This is why, in the eyes of many banking executives, major changes to critical systems are often viewed with a degree of scepticism. Yet even in those cases where a bank can clear these hurdles, and bear these costs, one has to be willing to accept a certain level of risk when undergoing change.
In overcoming this barrier, decision-makers must prioritise high-impact lightweight solutions.
Instead of costly consultant-driven change programmes where consultants benefit from expanding scope and timelines, one can overcome these barriers by using SaaS solutions, where implementation and maintenance costs are reduced, time to value is shortened and where the vendor bears most of the risk.
By reducing risk a willingness to make needed changes often arises, and when “change” means an affordable, easily reversed vendor contract, risk plummets.
4. Confirmation Bias
Within the anti-financial crime industry today, designations of business components as high-risk or low-risk often take the form of rote recitation of regulatory guidance. Consequently, as they are the most scrutinised, these pre-designated high-risk areas are where the majority of illicit flows are likely to be detected, potentially erroneously reinforcing the notion that they are in fact the riskiest. With this knowledge comes an admittedly biased certainty that any outcomes that do not conform to this pattern are the product of a faulty methodology. As such, for many, current systems appear sufficient, as they cannot know what they don’t see.
When minor revisions are presented as “innovation,” there is little reason for risk managers to ever make a change. Instead, any new product or solution must be capable of presenting first-order value, and a far greater depth of analysis than current industry standards. Realistically, it means having the courage to challenge common knowledge, a topic we fully explore in one of our recent posts.
As it stands, it is clear that the current state of financial crime control technologies is insufficient for the task at hand. The magnitude of illicit monetary flows has remained unchanged for decades, a fact that most are no doubt aware. The thought, however, of opening this Pandora’s box, so to speak, and acknowledging the degree to which financial institutions miss criminal transactions, can be daunting; not only because it could be perceived as an indictment of an institution’s competence, regardless of the systemic causes, but also because being the first in the industry to uncover the true magnitude of illicit flows may be poorly received by the industry on the whole. The work that would be needed to interrupt these flows may also seem daunting, when in fact the identification of the activity is the hardest part.
The goal of any technologies attempting to overcome this barrier cannot be to simply uncover as-of-yet unknown risk exposures but to develop a new way of holistically managing financial crime risk. By leveraging machine learning technologies towards the identification of illicit flows, the banking industry can move away from static control frameworks towards proactive financial crime risk control, leaving risk managers with a genuine assurance that their efforts are effective and beyond reproach.
Embracing innovation with Elucidate
At Elucidate we have incorporated the lessons from years working in the industry and in technology in the design of the Elucidate FinCrime Index (EFI). The EFI is a first-of-its-kind regulated risk assessment platform that leverages machine-learning capabilities towards the generation of a holistic rating of a bank’s financial crime risk exposure, that we call the EFI Rating.
Provided as a SaaS on a subscription basis, the EFI represents a simplification of the risk assessment process. With a reduced Time to Value, the time from the finalisation of a subscription agreement to deployment takes only a few short weeks, with Elucidate engaging directly with your tech team for rapid deployment and alleviation of implementation risks. And of course, with nearly all risk assessment procedures carried out internally by Elucidate, employees are left free to attend to actual risk management.