Showing posts with label digital transformation. Show all posts
Showing posts with label digital transformation. Show all posts

Monday, 24 September 2018

Why Corporate Banks should be embracing AI and Machine Learning

With Fintechs and other challengers threatening to pick off the most profitable parts of Corporate Banking such as international money transfers and the provision of FX services, never has there been a more important time for banks to invest in fundamentally improving the ways that they serve their corporate customers if they are to retain and grow their share of their customers banking business and importantly delivering this profitably.

Unlike in the Retail Banking industry, where most customers use only one institution for their banking services, Corporate Bankers have always had to operate on the basis that their customers will have relationships with several institutions and therefore they have to compete for share of wallet.

There are two strategic questions that Corporate Banks need to address.

What is it that corporate treasurers (the principle owners of the relationships with the banks) want and what will incentivise them to increase the proportion of their banking business that they give to one institution over another?

A lot of what is driving corporate treasurers’ expectations today is coming from their experience as consumers. Given their experience of looking for a product on Amazon, choosing, ordering and paying for it and receiving their order the same or next day, their expectation of what a customer experience should be has been significantly raised. When even in Retail Financial Services where it is simple and cheap to make a foreign currency transaction using a Fintech such as TransferWise, it raises the inevitable question of why does it have to be so difficult to do the same in the corporate world? Even when TransferWise can’t make the payment instantly the consumer has complete transparency on where the transaction is in the process and importantly in real time. The corporate treasurer is looking for the same level of transparency and ability to self-serve when they engage with their banks. Having to phone their bank to find out the status of a payment is no longer acceptable.

Speed of execution is another expectation that has been changed by the treasurer’s consumer experience. They expect their banks to make decisions quickly and for transactions to be executed faster than they are today.

A frictionless experience in sharing data between the bank and the corporate is increasingly being demanded. Traditionally one of the reasons that corporates rarely change their banks is because the on-boarding process by banks takes a long time, is error prone, highly bureaucratic and every bank has its own process requiring slightly different information. If a bank can offer on-boarding that is frictionless, where the bank does most of the work and where the time to on-board is dramatically reduced then the positive impact on that bank’s share of the corporates banking business will be huge. Introducing a standardised approach to switching (where every bank asks for the same set of information and not asking for what they already know about the customer), as has been introduced in several countries in the retail banking industry, should be introduced for the corporate banking industry. If this was put in place there would be a dramatic shift in the number of corporates changing their banks. It is understandable why the incumbent banks don’t want to do this for fear of losing customers. However, those who do, and do it well will significantly benefit. If they don’t do it then one or more challenger banks will and will pick off the most profitable parts of their corporate business.

For the corporate treasury teams too much time is spent reconciling the cash accounts in their General Ledger with the bank accounts that they have with their banks. Much as open banking is promoting the idea of consumers having a single place where they can see all their accounts, regardless of which bank is the provider, so too Corporate treasurers do not want to have to visit a different portal for each of their banks but rather have one place where they can see all of their bank accounts. Simplification of that whole process so that there is a simple matching of Ledger cash accounts with bank accounts through the use of a virtual accounts solution allows the treasury team to focus on the important decisions about cash management. The bank that can offer this to their corporate customers will win a greater portion of their cash management and other banking business.

A frustration for the corporate treasurer is that their relationship manager often does not have a total view of the corporate’s relationship with the bank. Most banks are still organised around product divisions and it is left to the corporate treasurer to navigate around the bank’s organisation or worse still fend off multiple sales people from the bank trying to sell competing or overlapping products from the same bank.

The corporate bank customer’s requirements have evolved but are fundamentally straightforward and reasonable.

What role does Artificial Intelligence and Machine Learning play in delivering the Corporate Banking customer’s requirements?

Much as young children have grown up with the expectation that every device is touch sensitive and there is an increasing acceptance of Alexa and other voice-enabled devices, it won’t be long before a bank (or more likely a non-bank such as Amazon) will offer corporate customers a banking proposition where Artificial Intelligence and Machine Learning will simply and seamlessly be built into all business processes.

There is already evidence of it beginning to be used across the whole lifecycle of banking business processes. At the front end the use of Machine Learning to display the help pages in the order that they are most frequently requested, encouraging self-service by customers rather than them having to phone for assistance. In the back office it is beginning to be seen to be used for fraud and money laundering detection along with payment instruction repair.

Due to the difficulties of switching banks (as mentioned above), Corporate Banking customers have low levels of churn. However, what they do exercise is the ability to flex the share of banking business that they choose to give to individual banks. Identifying the leading indicators that a bank is becoming less favoured by a corporate customer is a task highly suited to Machine Learning. The key characteristics that lends to this being solvable using Machine Learning are the large quantities of structured (e.g. transactions) and unstructured data (e.g. social media, emails, phone calls) from a large cohort of customers. Looking back at common events that occurred before customers significantly reduced the share of their banking business with a bank should help to build an understanding of the leading indicators of business attrition. With significant returns if this potential loss of share of wallet is addressed prior to it occurring this makes it an ideal case for using Machine Learning.

The recent uncovering of large scale money laundering being enabled by a number of banks such as Danske Bank, Credit Suisse and HSBC and the subsequent consequences, both financially and reputationally, for the banks involved could have been identified earlier had Machine Learning technology have been applied to the problem. Machine Learning is particularly appropriate to this type of dynamic problem where the money launderers adapt their techniques and approaches to avoid detection and the system to identify and respond quickly to these changes.

Understandably one of the most frustrating experiences for corporate customers is when payments made are returned by the bank due to clerical errors such as incorrect IBANs, payee names or account numbers being submitted. Increasingly banks are turning to Machine Learning to fix these issues and allow the payments to go through without having to be returned to the customer. This is because of the increased IT ability to handle fuzzy data for instance where there could be names spelt incorrectly or digits transposed. Given the high volumes of transactions and the varying nature of the errors Machine Learning is far more productive at addressing this than manual intervention.
The changing demands of corporate customers, the increasing competition for the most profitable segments of banking business and the increasing cost efficiency of IT processing means that this is an ideal time for Corporate Banks to apply the power of Artificial Intelligence and Machine Learning to deliver a far better experience to their customers in a more profitable way.

Tuesday, 22 August 2017

The Cloud is ready for the Banks but are the Banks ready for the Cloud?

Of all industries banking has been amongst the slowest to migrate core processing to the cloud. There is no doubt that the few cloud providers that started their businesses purely designed for the cloud have sophisticated, complete and secure offerings so what are some of the reasons for banks to consider using public cloud services?

Reduce costs

Reducing is always given as the number one reason to switch to the cloud and there are plenty of business cases that prove that to be true. Not least of all the ability to close data centres and reduce the headcount that is required to support IT infrastructure. On top of that is reducing the capital tied up by IT and deploying it in a more effective way for the business.


The ability to flex and pay for only the resources that are consumed whether it is storage, memory or processor power is a significant benefit for banks as all On Premise banks have very large quantities of redundant capacity both for operational and disaster recovery purposes.

As a simple example, the ATM network needs to comfortably support peak volumes. In the UK this is typically around 1.10pm on Christmas Eve where there is a huge spike in the number of people withdrawing cash for the Christmas period. This capacity is not only required in the operational system but also in the disaster recovery system should failover be required. Customers will certainly remember banks that weren’t able to dispense cash on Christmas Eve. For the rest of the year much of that capacity will remain idle with maintenance bills and licences still being charged.

For Paypal there is nothing to fear from Black Friday or Amazon Prime Day, when enormous spikes are experienced. Paypal uses public cloud services and only pays for the volumes that are used and only for when they actually used it.


Scale Public Cloud providers have the numbers of data centres and nodes that banks simply cannot afford. They have the networks and dark fibre because they need them to provide their service. Because providing a resilient service is critical to staying in business and because their businesses were created and designed from day one in the cloud they have the advantage over those who have started from an on-premise mindset and move to public cloud.

It is unheard of that Amazon, Google or Facebook are not available? Public cloud providers do not put out notices to say that there services will not be available for several weekends while updates are made.


Banks are under constant daily attack from hackers trying to break through their security and steal customer data or hold banks to ransom. As has been seen banks can and have been breached. However the providers of cloud services whose sole business is the provision of secure services to customers have much deeper pockets to hire the best and to invest in providing the most secure Identity & Access Management systems. Because their systems were designed for the cloud from day one and they employ the smartest technical people with the same mindsets as the hackers they have proved in many respects to far more secure than on-premise. If they weren’t why would they be used by the security services?


With increasing mobility of both customers and employees being able to access systems from anywhere in the world on any device at any time is increasingly being demanded. A public cloud solution makes this far easier than an on-premise solution.


By moving to a standard public cloud architecture, the overall IT architecture is simplified. Most banks have grown over time and so has their banking architecture which has led to a heterogeneous architecture made up of a mix of hardware and software of different ages that requires integration.

Regulator approved

A concern that has been often expressed is that the regulators would not approve banks using public cloud. However that is not correct – Monzo is an example of a challenger bank that is running entirely in the public cloud.

Even in more conservative countries such as the Kingdom of Saudi Arabia the central bank, SAMA (Saudi Arabian Monetary Agency) has approved the use of the public cloud by banks.

Not only that but Central banks and regulatory bodies such as FINRA are big users of public cloud as it gives them the ability to work on large datasets, structured and unstructured data, supercomputing and analytics tools to carry out tasks such as identifying fraud and suspicious trading in real-time and only paying for it when they need it.

Designed for Mode 2 Development

As increasingly banks look to innovate using Mode 2 Development methods then setting up and managing environments and tools to manage this is made much easier when using a public cloud provider. For those providers who have designed their businesses for the cloud from the start Mode 2 has always been the market they have served. All the exponential organisations started out being developed using Mode 2. It is far easier for a Mode 2 cloud infrastructure provider to move to Mode 1 (traditional development) than it is for a Mode 1 organisation to move to the provision of Mode 2 cloud services.

Access to innovation

The large scale public cloud providers have been where the innovation around new technologies has all been taking place whether it is AI (Google DeepMind), Voice (Amazon’s Alexa, Microsoft’s Cortana), Image Recognition (Amazon x-ray), Autonomous Vehicles (Google Waymo), Augmented Reality (Google Tango, Pokemon Go) or Gaming. These are the technologies that banks and other financial services providers need to embrace if they are to be relevant and able to compete.
Public cloud is ready to enable the future of banking. The challenge for banks is to embrace and exploit what public cloud offers.