Month: March 2025

The Rubik’s Cube, a difficult nut to crack. It is multi-faceted, offers the player multiple paths to victory, requires patience, determination and a methodical problem solving approach. One could say that corporate lending is the banking industry’s very own Rubik’s Cube.

For decades, financial institutions big and small have suffered the industry’s equivalent of aerodynamic drag. Lending operations managing highly complex (almost living and breathing), multi-party financing arrangements are slow and cumbersome. They require specialist resources with intimate knowledge of deals. They are heavy on user input and highly fragmented.

Why transforming corporate lending is needed

A lack of transparency and connectivity between parties is a major challenge, particularly in syndicated lending. Communication of mission critical information from the agent (the party that administers the deal) is instruction driven (fax and email based). Borrowers and lenders maintain their own records such as interest and fee calculations. They monitor covenants and conditions themselves and spend a significant amount of time reconciling inconsistent data. There simply isn’t a single source of the truth!

Across the board this business operates at high cost, high risk and the customer experience is poor. Errors are no stranger to this business and the impact can be catastrophic, take for instance the rather large $900M error made by one institution, which made the news recently. The current status quo means reputation and financial stability is at risk.

The operating models that are employed by the industry today lie at the heart of the problem. They are founded upon legacy technology – technology that considers only the user experience of a single party rather than all parties included in the financing arrangement. This technology assumes the agent’s operational staff act as the engine of the operation, doing all the heavy lifting when it comes to transaction processing, compliance monitoring and reporting for their customers. It is technology that is designed to facilitate some aspects of the process, but not all!

“The whole is greater than the sum of its parts”

I recently read this great phrase in Iain McGilchrist’s The Master and His Emissary.
As humans, when trying to understand our surroundings, we aren’t concentrating on every small detail. Instead, the brain distinguishes objects as part of a greater whole and as components of more complex systems. McGilchrist argues that, over time, we humans have lost sight of the value of the whole and the understanding that the whole is something different from the sum of its parts.

This dominates the approach to how we live our lives, see the world, and influences the way we problem solve. As a result, our understanding of things is often limited and we miss the big picture as well as the fundamental truths that come with it.
Applying this thinking to the world of corporate lending, I can see why it has been so difficult for the industry to move beyond the operating models and processes that cause it so much pain. You see, the general approach has been to introduce solutions that sit around existing systems and processes. Creating high barriers to entry (cost and time wise), associated with the integration projects required to implement them. Whether a market initiative or in-house development project, adoption has been slow and success rates low. What I have observed in my 15+ years of being in the industry is that historical approaches, with all the best intentions, have the wrong end state in mind.

That end state is not the whole but the sum of its parts.

In the meantime, the Rubik’s-Cube-like nature of this business is under extreme pressure and reaching a breaking point. Corporate customers are seeking a more retail-like experience. Regulatory and market changes are challenging the industry’s ability to adapt and introduce new products to market quickly, and do so in a cost effective and minimally disruptive way. The rise of alternative lenders, Bigtechs and Fintechs threaten traditional banks’ market share through the allure of seamless next generation technology.

If this industry is to effectively respond to the pressure and realise the digital transformation to which it aspires, the approach needs to be different. It needs to consider the whole from the outset. It needs to consider every party involved in a corporate lending transaction (that is, the challenges, needs and risks to the borrowers and lenders) and not just the custodian of the deal. It needs to consider what a modern user experience would look like if the technology was not a blocker.
The potential this offers is uncapped! Think entirely digital processes. No rekeying. No duplication of data. Think no more fax and email correspondence. Think data driven insights, market places and more!

The road to transformation in corporate lending

The road to transformation is a progressive one, but the destination needs to be a place that looks very different from the starting position for many organisations. That can only happen by taking a step back and looking at the bigger picture.
Oneiro (the Greek word for Dream) Solutions, has re-imagined the world of syndicated loan administration considering the whole, not the sum of its parts. If you would like to learn more then please get in touch.

After news broke about Citibank’s loan processing error, back in August 2020, it wasn’t long before a WhatsApp group of mine started to ping.

We’d been through months of lockdown and these messages from ex-colleagues from my lending ops days were a welcome excuse to catch up – and share stories of our own heinous balls-ups.

We experienced the stress of keeping the boss in the dark until cash was recovered. Margin ratchets were corrected, missing trades found, followed by a sheepish but hurried call to Hippopotamus Capital CLO (or something) who would hopefully return the funds before cut offs and overnight recs outed the ‘oopsie’.

My own oopsie saw me nervously pushing a negative few million of Swedish Kroner around a nostro for three days before ‘Hippo Dave’ agreed my calcs and wired the cash back. A couple of sleepless nights was the price I paid. Minor, in comparison to the $400m fine levied against Citibank by the OCC following their incident.

My first job in loan ops was in 1998. We’d track loan lifecycles on handwritten ledgers, physically collect signed drawdown docs from neighbouring borrowers, and seal everything in waterproof and fireproof cabinets before leaving for the day. With that level of manual processing, operational errors were all but priced into the deals.

Mistakes happened because we were busy, especially at month or quarter end, and in my case, largely because I was 19 years old!

Roll on almost 25 years to Citibank’s blunder. With an operating model which mirrors that of most Tier 1 banks today, it includes an outsourced, offshore processing team for their ‘maker > checker’ inputs (four eye check) and, for sums of the value in question, an onshore, bank-side team for a last six eye check.

Someone had initiated a repayment instead of a rollover and had sent lenders the full loan principal instead of just the due interest.

Four eye check missed it. Six eye check missed it.

I sympathise and shudder when I put myself in their shoes. The dawning realization that you’ve just pushed a sum greater than a small nation’s national debt through your loan booking system and out the door in error… I’m certain large holes for crawling into were wished for that day.

Do you know what Citibank’s lawyer said as the incident explanation to the appeals court?

“This was a mistake. Humans make mistakes.”

So whether a bank’s underlying system has a process with four, six – or however many – eyes in place, it will do nothing to mitigate the impact of an error of this incident’s scale. As Citibank’s lawyer very plainly explained, if we allow humans to be the final safety net, mistakes will be made.

Commercial banks must ask themselves, why, with the sheer amount of innovation and technology available on the market, do we still allow errors like this to occur?

An agent like Citibank needs to manage hundreds, sometimes thousands of lenders on a single credit line on behalf of their customers and the tools they use are creaking under the pressure. Whether it’s an in-house solution built on an ageing tech stack or a third party monolith that’s been around longer than I have – it’s simply not good enough.

Look what technology has done for the retail sector in the last decade. OCR for cheque clearing, facial recognition for account opening and verification, AI-powered algorithms to authenticate customers’ identities, standardised API’s for open banking. The list goes on.

Why has commercial banking, especially lending, not taken advantage of new technologies at the scale it needs? Yes, yes I know global corporations are far more complex animals than us simple retail customers, and I know bank systems are fragmented by the very nature of the complex products and data those customers need. But how much longer are we able to justify the service a commercial lender can provide to its customers?

Did you know that corporate customers of the biggest banks are employing teams to second check the data sent to them by their banks? They maintain their own lending data because they can’t be sure their banks are accurate.

Again, I don’t think that’s good enough.

What do you think? Will we be reading about these kinds of colossal ‘oopsie’s in 2045?

Or can we work to adopt new thinking and next generation technology to spare ourselves another sleepless night?

It’s the millennial year 2000. Some guys from a young start-up company present their business to Blockbuster with a $50 million price tag. They promise to revolutionize the movie rental company’s online division.

Blockbuster “laughed them out of the office”.

Perhaps you’ve heard the story? That start-up was Netflix.

Fast-forward to 2010 and Blockbuster files for bankruptcy with one billion dollars of debt.

Fast-forward to 2022 and Netflix is worth $99.7 billion.

Quite the turning of tables.

It’s telling what Blockbuster’s former UK Chief Marketing Officer said:

“I am sure 99 out of 100 people involved in Blockbuster would have told you the future was in digital downloads and online ordering, but the chief executive had a retail background and his priority was to save the high street business at all costs. Perhaps we would have benefitted from a different perspective.”

A different perspective

Blockbuster would be a huge commercial smash no more. They really should have heeded Billy Beane’s advice in Moneyball to “adapt or die”.

All businesses need to adapt, transform even, to move with the changing habits of their clients and customers.

Blockbuster missed a colossal opportunity as the CEO was so focused on bricks and mortar. In hindsight, let’s question why. I can imagine it’s because:

It was familiar.

It was working.

It was how it started.

I implore business decision-makers in the corporate banking industry to ask themselves: is what we’re doing familiar, working just about, and how we’ve always done things?

If the answer to any is yes, ring the alarm.

The truth is most banks are using technology that is thirty years old and counting! Can you believe it? It’s 2022 and the industry still uses fax machines.

The future of corporate banking

As we’ve seen in retail banking, an online platform is now not only a nicety but a necessity. Customers expect it. They expect to be able to move money around using their devices. They expect to be able to check their balance in real time, at any time.

They don’t expect to have to walk into a high street branch. They don’t expect the handling of their money to be prone to human error.

Why should the service within corporate banking be any different?

There’s a cultural mindset of: this is familiar, this is working, this is how it’s always been done. This perspective is blinded by an unyielding allegiance to the way things are.

In my experience, in any organization there will always be someone in the room who is opposed to next generation technology. Why do we need an online platform? The way we work works alright. Do you realize how much effort, how much cost it would take to change?

This is the Blockbuster mindset.

It’s settling for little tweaks; superficial plugs to their aging dam.

In effort to compete with competitors, Blockbuster stopped charging people late fees. But then people held onto DVDs for longer, meaning others couldn’t rent them, and so this intended plug made a double crack in revenues.

Netflix understood that a flood was coming. They took the technological, game-changing approach. They looked forward and said, take the physical disks away, utilize next gen technology, stream the movies, let there be no limit to how many people could watch a film at one time.

I love what Reid Hastings, Netflix’s co-founder and CEO, said…

“My greatest fear at Netflix has been that we wouldn’t make the leap from success in DVDs to success in streaming. Most companies that are great at something — like AOL (AOL) dialup or Borders bookstores – do not become great at new things people want (streaming for us) because they are afraid to hurt their initial business. Eventually these companies realize their error of not focusing enough on the new thing, and then the company fights desperately and hopelessly to recover. Companies rarely die from moving too fast, and they frequently die from moving too slowly.”

And I think we can all agree, the corporate banking industry has been progressing too slow for too long!

As Netflix gained subscribers, it took Blockbuster six years to launch a similar service (Blockbuster Online). As we clearly see now, they pivoted too late.

The tipping point for digital transformation within corporate banking is long overdue, so you better believe it’s near.

Whether it’s how we watch movies or deal with money, looking forward to the next new thing, not shrinking back from the potential of technology, doing something seemingly drastic today… it’s what’s vital for companies to survive and thrive tomorrow.

Adapt or die, corporate banks. Adapt or die.

The future of any business is only as bright as its ability to retain young talent. So what’s new with this new generation of professionals, what are they looking for in a prospective employer and what can they bring to the table?

Take Andrea Scott. She graduated with a Master of Mathematics, now she’s ready to take the world of cloud engineering by storm.

She walks bright-eyed into the back office of one of the world’s largest corporate banks. She’s introduced to a 20+ year-old core system that requires another masters just to understand the UI. And there’s a machine in the corner churning out paper, they call it fax. What on earth is that? Then she’s told more about the system:

‘Sure we’d love to innovate but this has over 100 up and down stream interfaces, some of which we don’t even know what they do. It’s too risky, too expensive to change. You should focus on smaller advances and efficiencies.’

Andrea is now looking for the nearest exit.

Andrea walks into the back office department of another neo/challenger bank. No vintage throwback in sight. The bank has just gone live with a cloud native platform that administers corporate loans. It uses cutting-edge technology and is limitlessly buildable. She’s told:

‘Get dreaming of new ways the bank can provide its different products.’

Andrea is now looking for the nearest opportunity to impress her line manager.

What Gen Zs want – and what they can offer

Here’s a rundown of their preferences and strengths…

Common among Gen Zs is their desire for purpose-driven work. They need a sense of meaning. Andrea doesn’t want to just apply quick fixes to old world problems. That doesn’t align with her values. She wants to be part of forging a new world for her generation and the one to come.

Gen Zs are also hungry for opportunities for continuous learning and development. This is great news for the future of the company they choose!

With the Covid pandemic being a core experience for Gen Z, they prefer flexible work arrangements, mixing remote and in-office working for the best of both worlds. This can improve work-life balance, productivity levels, and cut office-based overheads. Flexible working is made increasingly possible through technological innovation.

Speaking of technology, Gen Zs have grown up in the digital era; it’s second nature to them. They are extremely tech savvy and need modern and innovative workplaces in which to thrive. They’re looking for a place where they can leverage advanced technology to build next level solutions.

Andrea is hungry to problem solve, but not for a company with rigid structures and outdated approaches where her voice is unlikely to have a meaningful impact. She has an entrepreneurial spirit and mindset, and seeks a workplace culture that encourages experimentation, risk-taking and game-changing ideas.

What corporate banks can do to win Gen Zs

Competition for talent in this industry has majorly intensified. Corporate banks are not only competing with one another, but with tech companies, start-ups and fintechs that clearly embrace emerging technologies, dynamic approaches and innovative digital tools.

To stand out and win new talent, commercial banks need to fight the mindset of this is how we’ve always done it. They need to demonstrate their commitment to advancement for the good of their company and their people.

How? They can:

• Offer career development opportunities such as training programs, mentorship, and career advancement opportunities that nurture innovation and support the growth of all employees.
• Encourage cross-functional collaborations and so provide further opportunities for young talent to work on diverse projects to enhance their skill sets.
• Foster a culture of innovation by encouraging creativity, continuous learning and experimentation. Initiatives such as hackathons or innovation challenges enable young professionals to contribute their fresh perspectives.
• Embrace technology by investing in and adopting innovative technologies such as artificial intelligence, machine learning, blockchain, and digital platforms.
• Partner with fintech firms and start-ups to infuse the company with innovative ideas and practices, and in turn attract young talent who are eager to work at the intersection of finance and technology.

Our tale of Andrea Scott is based on the personal experiences of our team.

We are a start-up fintech company with the world’s first, purely digital, cloud native, corporate loan administration platform. Get in touch. We’d love to chat with you.

For quite some time now, I’ve questioned why traditional software vendors in the banking space can’t seem to evolve their software alongside the evolving market and user demands.

Google keeps their search software fresh. Uber, Facebook, Microsoft and Palantir – their software consistently meets the demands of the user. Just look at all the features that Facebook has added in their main app, starting from a simple social media app for college students. Microsoft has evolved their flagship Windows software many times during the last 25 years.

And yet banking legacy vendors appear to be stuck in time. They do not have a good set of APIs. They are slow in delivering change. They say they are cloud native, but this is not the same thing as taking a big monolith and deploying it on a EC2 instance in AWS. Upgrading their software requires careful planning and it is an entire project of its own.

I believe legacy vendors cannot keep up because they do not build software in a sustainable way. 

Their software engineering teams have been stripped back, reduced. They’re treated as a cost centre with the goal of making software delivery as cheap as possible. There is no culture, the morale is low, and the product teams feel they are working hard just to keep the lights on. Their voices are not heard. They don’t have a seat at the table.

Senior management is focused on doing reorgs over reorgs, as if this would somehow avoid the inevitable, like switching chairs on the Titanic.

Their sales teams have taken up the slack, and instead of selling innovation they are telling banks to adapt their way of doing business to the software, rather than the other way around. But even the best sales team will run out of steam. And client feedback and references will outweigh the voice of the best salespeople on the planet.

Banks have started looking elsewhere, either to modern fintech upstarts or by building software in-house. They feel the pressure of change way before the vendors do.

What if developing banking software could be done differently? (And actually be great.)

What if it could be developed in such a way to be sustainable over time – always being up to date with the latest innovations in cloud computing and beyond, and also with new client demands in an evermore digital world?

Sustainability in software needs a precise definition, and a number of key ingredients to make it happen. First let’s define what sustainability means in this context.

By sustainability (as per Google’s definition) we mean software that allows for the possibility of cost effective change either because of business demands or changes in technology. 

Sustainable software engineering needs to maximise speed, quality and maintainability at a reasonable financial cost. Design decisions need to ensure that the impact on any of these metrics are factored in. Scaling costs need to grow sublinear with the increase of number of engineers, processes, customers and geographies.

Design decisions should be based on quantitative metrics as well as qualitative assumptions (customer feedback, metrics, back of the envelope calculations, test results, engineering best practices and computer science), rather than hunches, ‘It worked before’, politics or organisational setup, or just ‘Because I say so’.

New technology shouldn’t be adopted for the sake of it, because it makes us cool. Old technology shouldn’t be kept simply because we are afraid to change it. Software should be written with the future in mind, with the idea that it will be maintained or expanded on by someone else.

I believe investment can be allocated by making changes at the right time, in the right order. Overengineering, gold plating, as well as technical debt, need to be carefully managed.

This is only possible when you have the right raw materials in place.

Talent density in engineering and a high bar in hiring is key. And that doesn’t mean that building software should be a large expense. On the contrary, a skillful team will unlock the ability to scale software cheaply over time, which at the end of the day will far outweigh the staffing costs.

Having a strong team of individuals is not enough though. Take football, FC Barcelona are on the brink of exiting the UEFA Champions League this season despite investing €150M in new players. You can have a team full of stars that fail to win because they do not share principles and a clear vision, and therefore fail to play together as a team.

An engineering team needs principles and a strong culture (that favours the development of sustainable software over time) to bind talented engineers together.

Without principles the software loses its design integrity and becomes a hodge-podge of different approaches. This affects the speed, quality, maintainability and cost, many times in an unknown way until it becomes visible, most often when it is too late. Without a strong principled foundation the software will be rewritten many times. It will cost a huge amount of money to build even trivial features and it will never fully satisfy customer demands; while the cost of scaling will become prohibitive. Worst case it might affect the viability of the entire company and lose people jobs.

In the next posts we are going to explore some of the key principles enabling sustainable software development.

These principles will help guide engineers to find the optimal balance of speed, quality, maintainability and cost when building software. 

We can use them as beacons or north stars when making any engineering decision impacting the software.

As a taster, these include:

• Shift left. Maximise the speed and quality of feedback loops.
• 80/20 rule. Prioritise the 20% that provides the 80% of value.
• Design options. Build iteratively. Eliminate bad options at design stage, and build the chosen option in stages, from prototype to full production build.
• Design for volatility. Favour encapsulating and decoupling the potential of change in software (volatility) above everything else.
• Fail fast. Minimise for cost of failure rather than for probability of failure.

I welcome you to share your thoughts and experiences as we go along, thank you.

I believe that banking software can be developed in such a way to be sustainable.

Sustainable software stays up to date with new client demands and with the latest innovations in cloud computing and beyond. It allows for the possibility of cost-effective change. It is written with the future in mind, expecting that it will be maintained or expanded on by someone else.

Welcome back! Have a read of my introductory blog if you haven’t yet seen it.

We’re going to dive into the first key principle enabling sustainable software development.

Shift left

Shift left is the first in my list of principles for a reason. This is the practice of collecting timely, empirical data about the behaviour of the software as early in the development process as possible.

Without this, it’s hard to know if we’re making the right design decisions. We would have to rely on best practices and our experience alone.

History holds a long list of well-engineered systems ‘on paper’ that have failed dramatically, even with some of the most talented and famed engineers working on them. 

Collecting timely, empirical data means getting feedback about the behaviour of the system as fast as possible and with minimal cost. And receiving it before it gets into the customer’s hands.

Shift left requires investing engineering effort in developing platforms around the product itself to be able to generate, collect and analyse the data both before and after the software reaches users.

All software is unique to a various degree, and ambitious. Differentiated software products require ambitious, unique platforms. At Uber, more than 30% of engineering investment is dedicated to developing the underlying platform promoting the shift left principle.

In practical terms, the foundation for shift left in software is a strong CI/CD pipeline. This makes it cost effective and fast to collect data via automated tests covering both non-functional and functional requirements.

The mirror aspect of a strong CI/CD test automation tooling is a quality observability stack. Without tracers, logs and metrics, it is hard – almost impossible – to analyse the results of tests and make informed decisions.

At Oneiro, shift left means automating all aspects of the software delivery process. From automating the underlying software infrastructure, security configuration and deployments, even the versioning process, to implementing an entire battery of tests including production-like testing.

We are data hungry, and our goal is to extract as much information from the software delivery process as possible using automated means.

This enables us to make informed design decisions based on actual data and focus our resources on what is important. This is a fundamental prerequisite on which we build the actual product.

The shift left principle also makes us rethink what is the essence of software engineering…

At its core, like any other engineering discipline, software engineering is the application of the scientific process to solve a problem in an economical and efficient way.

As David Farley correctly mentions in his influential book Modern Software Engineering: Doing What Works to Build Better Software Faster, there are no manufacturing costs in software as the cost of replication is zero. Though the principles of production engineering do not apply to software engineering; the principles of engineering design through a scientific process of discovery do. And science is in essence progress through measured facts.

Similar to building a new model of a car or a plane that has not been built before, a lot of experimentation is required as well as testing of models before the product is ready for mass production.

In software engineering, the product itself is the model which makes testing and measuring easier compared with other disciplines, as it will end up being the final product. However, like other engineering design disciplines, what is still key is collecting empirical data through experiments on the product before it goes into production, and iteratively improving on it based on hard evidence.

Automated testing can be considered a form of scientific experiments where we control some variables to test for specific behaviours in terms of correctness, performance or resilience.

By following our scientific experiment metaphor to its conclusion, the tests have to be designed for one purpose only, and kept deterministic and hermetic, i.e. measuring the variables.

A note on building banking software systems…

For a long time banking systems have lacked the quality needed for this business. They have been built almost as an antithesis of applying scientific and empirical principles.

Systems that track tweets and social media posts (arguably far less essential) have been better built due to the fact that they have followed these shift left principles, which slowly permeated the Silicon Valley engineering culture.

The fact that management in financial institutions and legacy vendors have seen engineering as a production plant for a long time, where the goal is to ship mediocre features at the lowest cost possible, has not helped.

What hasn’t solved the problem either is the quasi-religious application of whatever engineering process was formalised in the company, regardless if it’s kanban, scrum or waterfall (which in essence are manufacturing processes applied to solving design problems).

I hope, in this essential business of handling money, that software engineering approaches would adopt the shift left principle: collecting timely, empirical data about the behaviour of the software as early in the development process as possible, and making rational decisions based on facts.

Let me know your thoughts or experiences. And coming up next… the 80/20 rule.