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Why Sphaghetti and Business Don’t Mix?

While Spaghetti may be some people’s favourite food, I don’t think anyone would like it on their keyboard. Even worse, it’s probably nobody’s taste for their bank’s business architecture.


Nevertheless, even after years of investment in ‘digital transformation’, this seems to be the state of play at many financial institutions around the world.


Think this may not be the most important problem to fix, right now?


-  Here are a few recent UK banking outages and Losses Due to unstreamlined infrastructure:


-  And here are a few UK Risk and Compliance fines that are attributable to inefficient systems:


  • Starling Bank (£28.9 million, Oct 2024): The bank’s automated sanctions screening system was misconfigured, matching customer names against only a fraction of required entries for over five years.


  • Metro Bank (£16.7 million, Nov 2024): Over 60 million transactions went unmonitored due to flaws in the transaction monitoring system, which failed to activate until account data was fully validated-delays that persisted for years despite internal warnings.

    https://www.thistleinitiatives.co.uk/blog/key-learnings-from-2024s-biggest-financial-crime-fines


How can we improve as an Industry?

It starts with stating the obvious: Data is Key. Getting the right data into the organization, and making the most of the data already available internally, are ‘tablestakes’. It is recommended to regularly analyze:


1.   Are there additional sources of data that you can obtain, out there? For example, corporate credit and risk scores, demographics data that can feed the firm’s marketing efforts, Ultimate Beneficiary Ownership, and other data sources that can provide a better view of risk and opportunities.


2.   Are there any internal hurdles that block your teams from accessing, and understanding, the data you already have? In the case of IT infrastructure, the data can be related (for example) to outages and processing delays. Those delays introduce risk and cause missed opportunities.


For further deep dive into key challenges banks are facing, with supporting insights into how to overcome them and drive data-first digitalistion, I recommend reviewing this excellent article by Sara de la Torre from Dun & Bradstreet

https://www.dnb.co.uk/perspectives/master-data/future-of-banking-digitalisation-data-driven.html


Making the Most of Your Data: 2 Tech Concepts Every Financial Services Leader Should Know Right Now


The rapid increase in the amount of available data, which led to a decline in data quality, has led to the emergence of new solutions and concepts (AI being just one) that represent a dramatic shift in the role technology plays in the industry. This holds true whether your organization is in fintech, investment banking, or any other sector serving customers. The AI revolution has the potential to accelerate all transformations, and the first step to readiness is updating your language and mindset to reflect these new opportunities.


Recently, Gregg Aldana, the Global Solution Consulting Lead at Appian , a fast-growing technology firm, launched a program called ‘Solution Consulting 2.0’. The essence of this initiative is to rebrand Solution Consultants from traditional product demonstrators into business consultants and advisors. Why did Appian make this change?


Appian’s leadership recognized that to remain competitive and relevant to their global customer base, they must focus on the business value they deliver and leverage their platform’s capabilities to unlock this value. Software-even AI-alone isn’t enough to make a difference, as organizations may choose not to buy it or fail to implement it effectively, missing its potential benefits. Only by clearly articulating the business impact can a technology company like Appian truly engage clients and grow together with them.


In this context, business leaders must also educate themselves on the key technology concepts demanding their attention. True partnership arises when technology consultants speak the language of business, and business leaders can ask informed questions about high-level technology concepts. This dialogue leads to tangible benefits: reduced risk, increased client satisfaction, and higher growth. The combination of ‘Solution Consulting 2.0’ and business leaders’ awareness of technology concepts can drive sustainable enterprise growth, powered by the new ‘magic tools’ technology offers.

Concept 1: Agentic AI

Agentic AI may seem like the latest in a series of AI buzzwords-following ‘machine learning’ and ‘Generative AI’. What sets Agentic AI apart, and why is it a game changer?


  • ‘Traditional AI’ relied on Machine Learning (ML) - programs that learn from past data and feedback, adapting to produce new insights. Its main limitation is that it relies on data and delivers quantitative results. For example, it might predict the success of a product based on historical sales data. ML can achieve sophisticated outcomes, especially when guided by expert-curated data and human feedback.


  • Generative AI has dominated 2024, enabling AI to generate text and other content by training on vast datasets. Its novelty lies in its creative capabilities, producing stories, reports, and more-not just numbers.


  • Agentic AI describes autonomous AI systems that can set goals, make decisions, and perform multi-step tasks with minimal human supervision. Unlike traditional or generative AI, which typically responds to prompts, Agentic AI proactively plans, acts, and adapts to achieve objectives, often integrating with external tools and APIs to take real-world action, like drive operations forward, conduct research, and generate responses based on its findings. It is a game changer because, in theory, its capabilities are limitless in the digital world. Agentic AI can: Read KYC data from various sources, assess risk based on submitted documents, flag high-risk cases for human review, and process low-risk cases through operational steps tailored to client type, segment, or jurisdiction. Receive customer input (by text or voice), understand customer demographics and location, ask clarifying questions, check internal systems for required services, and process requests accordingly.

Concept 2: Business Orchestration and Automation Technology (BOAT)

As organizations face increasing complexity and rapid technological change, Business Orchestration and Automation Technology (BOAT) has emerged as a new term that reflects all the tools that connect the various systems used by the organisation together.


BOAT integrates a range of tools and concepts:


·   Robotic Process Automation (RPA)

·   AI-driven decision-making

·   Workflow automation / orchestration

·   Low-code platforms

·   Integration services


The commonality between those components is that without them, the AI capabilities mentioned above are a dead letter, because there is no technological lever that will actually make anything happen in the organization as soon as the AI reaches a conclusion that something needs to be done.


In the recent past ‘automation’ was mentioned under different terms like Business Process Management (BPM), the main advancement in the way the term BOAT is used today is that it refers to the flow of multiple automated activities, ensuring that systems, data, and people work together seamlessly to achieve broader business objectives. By consolidating disparate automation solutions into a single orchestration layer, BOAT simplifies the firm’s business architecture, making it easier and quicker to adapt to market changes, respond to challenges in customer experience, and integrate new AI technologies as they evolve.

Illustration: Future State of Business Architecture

The following 2 diagrams showcase how the business architecture may look today and in the future at large corporates, for example large banks.



1.   Origination from various data sources (external and internal) that flow into data repositories / lakes, as well as BI tools that provide a lens of insight on top of the data


2.   Applications consume this data and perform functions like determining applicability for a loan, calculating the risk, creating documentation, and interacting with compliance teams. Those applications may be ‘analytical’ (for example Transaction Monitoring, Credit Risk), or ‘case management’ (as may be used for Customer Service case tracking) or, increasingly, AI-enabled.


3.   Operations solutions include several domains, notably customer outreach and CRM.


In the Current State, most organizations have their Data Origination sources connected to several Applications; the applications are inter-connected and they feed into the Operational solutions that perform the ‘next steps’ as determined by the respective applications. This readily creates a spaghetti-like situation, which delays changes and makes any update due to new market conditions (for example expansion into a new demographic) or new technologies (new AI solution with improved fraud detection rate, for instance).


Enter another tasty photo of Spaghetti, before we dive into the Target State:



Target State : A Peek into the future (3-5 years timeframe)


The Target state in this scenario should be seen as an ‘idealized’ version. While I have no doubt that AI will eventually take centre stage in all aspects of business technology, it may take time to get there.



1.   Origination takes data from the various data sources and feeds it into the new BOAT layer; while the application layer would be primarily tasked with extracting intelligence and actions from the data, it expected that enrichment, traceability, and governance will be enforced through a uniform orchestration layer.


2.   AI Agents are likely to replace traditional business applications across time. Gartner forecasts that by 2028, 33% of enterprise software applications will integrate agentic AI, up from less than 1% in 2024, marking a significant shift away from traditional software toward AI-driven, autonomous systems. 

https://www.holisticai.com/blog/ai-agents-governance-business


3.   BOAT will evolve to adapt to the new capabilities of the AI Agents; crucially, the vision whereby all data streams into the BOAT layer will require elevation of capabilities on behalf of software firms operating in this domain, like Pega , Appian and Service Now. We can already see this trend accelerating as all these 3 firms have announced new capabilities that help embed AI into any organizational process. Circling back to the beginning of this article – this is the reason that Appian has embarked on the SC 2.0 journey – the only way for a BOAT solution to be strategic is to be able to speak to the business benefits of the AI being deployed by the firm.

Conclusion

The journey from “spaghetti” business architectures to streamlined, AI-driven operations is not just a technological upgrade-it’s a fundamental shift in how financial institutions must think, act, and deliver value. As recent outages and compliance fines have shown, the cost of clinging to legacy systems is rising, both financially and reputationally. The future belongs to organizations that can harness the power of their data, leverage advanced solutions like BOAT, and embrace the transformative potential of Agentic AI.


The real differentiator will be the ability of business and technology leaders to collaborate, speak a common language, and focus relentlessly on business outcomes. Initiatives like Appian’s Solution Consulting 2.0 exemplify this new mindset, where technology is not just implemented, but fully aligned with strategic goals.


Success will come to those who break free from established approaches, and have the courage to lead in sourcing new data, extracting more from existing assets, and most importantly: speaking the same language across silos, so as to build partnerships-internally and externally-that are rooted in shared understanding and mutual growth.

About the Author

Yair Samban

is a financial services and technology leader with extensive experience in KYC, AML, and financial crime transformation. He currently serves as Head of Solutions Delivery at Elliptic, working at the intersection of digital assets and traditional finance.Earlier in his career, Yair held senior roles at Goldman Sachs and Pegasystems, where he led global consulting and delivery teams across financial services. His work focuses on driving technology adoption across AI, automation, and compliance systems, helping institutions navigate complex regulatory environments while scaling securely.


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