• Neil Mathieson

Happy Clients, Profitable Banks, The PossibilitIes in Machine Learning

Updated: May 19

It is always a pleasure to visit Denmark but with the battle on to become the Nordic's

Fintech hub we were especially excited to present at Copenhagen Fintech (CFIR) recently on ‘Machine Learning and Financial Advice’


For those not familiar with the subject, ML is a form of artificial intelligence where the computer learns without being explicitly programmed. It is extremely good for analysing huge volumes of data and variables, yielding insights that humans simply cannot. Moreover, a computer is not constrained by the assumptions of statistics or human bias.


Happy Clients, Profitable Banks

An explosion in the volume and complexity of data being produced, combined with the inability of legacy systems to process this, requires change. More importantly, it offers companies the possibility to gain competitive advantage through innovative new products, identifying cross-sales, making personalised offers to clients, predicting defaults, etc.


A recent study by Mckinsey on 12 European banks that replaced older statistical modelling approaches with ML techniques showed found that, in some cases, they experienced a 10% increase in sales of new products, 20% saving in Capex, 20% increase in cash collections, and 20% decline in client churn.


A similar study by Cognizant on 537 corporations in N. America and Europe estimated that 45% of banks had seen 10% revenue growth from aligning analytics to front office activity. This was forecast to rise to 73% in the next 3-5yrs. At a time when financial service providers face changes to their traditional business models these are compelling numbers.


Carbon v Silicon? It Depends!

In our presentation we looked at applications of ML in financial services, including algorithmic trading in Treasury, Robo-advisory in wealth management, Telematics, AML and supply chain finance. We saw that despite current benefits and future potential the speed of adoption has been slow compared to other industries. Why so given managed trading has been commonplace for commoditised transactions in corporate treasury for years? Robo-advisors can automatically rebalance portfolios to keep them within the client’s pre-defined risk parameters.


We know computers offer greater speed, consistency, auditability and cost efficiency but equally we understand the dilemma in delegating authority to a computer. It depends on the specific task and corporate culture (although we still advocate that if you cannot understand the process or outputs you should not do it!).


Getting f'IT

Digital Core Banking and Credit Scoring solutions store masses of unstructured data on which Big Data and Predictive Analytics can be run. At the moment they produce descriptive analytics about ‘what’ happened. Clients increasingly demand ‘why it happened’ and ‘when will it happen again’. This is the key to unlocking client satisfaction and profitability yet misperceptions persist:


1. Digital Transformation is a fashion. Nope, industries such as media and manufacturing demonstrate its power. Moreover, regulation such as MiFID II will soon require active monitoring rather that static policies and historic data.

2. Digital Transformation can be achieved overnight. Nope, it as a journey that affects strategy, people and process with many steps and milestones along the way.

3. Digital Transformation can be achieved on current infrastructure. Nope, you are going to need digitally enabled solutions – universal to eliminate silos, multi-channel, real-time, flexible, open. New technologies will emerge.


Dont Wait

Navigating the digital transformation path when faced with a jigsaw of legacy systems, budget scarcity and high competition is not easy (or cheap!) but a sensible first step is process automation.


Short-term this allows data to be standardised, processes optimised and systems rationalised. Medium-term it creates the valuable data lake required to generate deeper insights on client, product and business performance. Longer-term it supports more rapid and economical development of new offerings.


Cognizant found that process automation delivers significant benefits to front, middle and back office operations, why not take the first step today!



p.s. TUSIND TAK to everyone at CFIR, it was a real pleasure and we hope to see you again soon.


Neil Mathieson 01.08.2015

#fintech #cfir

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