Why your customers will thank you for modernizing your core systems
Hani Hagras, Temenos’s Chief Science Officer, foresees a future in which the combination of AI and machine learning, which we might call advanced analytics, will leave few parts of the banking industry untouched. “These technologies are going to be completely transformational for banks and their customers,” he says.
Hagras discusses how core banking systems will feed real-time transaction data into analytics platforms to generate deeply personalized customer relationships and entirely new forms of value. Ultimately, he suggests, intelligent systems will take over budgeting and purchasing in many households. (On this, Hagras is notably even-handed: banks will reap benefits, and so will customers, he says). In addition, our conversation touches on the potential of advanced analytics to accelerate and improve the detection of fraud and money laundering, sanctions screening, wealth management, investment portfolio management, automated error handling, mortgage applications and debt collection.
The vision is compelling but will involve hard work and significant investment. Poor data governance, for example, is one of two leading causes of AI project failure, according to a recent RAND Corporation report based on interviews with dozens of data engineers and data scientists. Advanced analytics requires large amounts of training data and the type of data matters. As the authors note: “In many cases, legacy datasets were intended to preserve data for compliance or logging purposes. Unfortunately, structuring data for analysis can be quite different: It often requires considerable context about why things happened as opposed to simply what happened.” Other characteristic challenges include the quality of data (e.g. missing values) and selecting the wrong data types to feed into AI systems and infrastructure that is not up to the job of taking AI models from testing into real-life use.
“If you want to use the full power of advanced analytics,” says Hagras, “your analytics software needs to sit on a core banking system that is modern and well-designed. You need to be able to extract data easily from it. You need to be able to feed outputs easily to it.
“There will be situations where modern core systems are not in place. In this kind of situation, Generative AI with appropriate semantic layers can play an important role in bridging the gaps created by legacy core banking systems. This will allow banks to enjoy some of the benefits of advanced analytics. But in the end, a solution based around a legacy core will be sub-optimal.”
Data-enabled and customer-centric
Modern cores will drive tomorrow’s data strategies. But they should also be underwriting operations today. “Data is not always front of mind when it comes to growing your bank’s market share,” says Mathieu Charles, Vice-President of Customer Strategy, Temenos and manager of Temenos Value Benchmark (TVB), the company’s in-house research organization. “However, requirements like reducing churn and increasing cross-selling are front of mind. To do these things, you need to be customer-centric. And to be customer-centric, you need data.”
When Charles’s team at TVB assess the burden of legacy at individual banks, many of the metrics they examine are directly relevant to customer-centricity: “The pain points that suggest a lack of customer-centricity include slow Time-to-Market (TTM), a low number of product releases, low levels of Straight-Through Processing and a small proportion of digitally active customers.”
Charles describes three strategies that banks aiming to become data-enabled should already be pursuing:
- A single source of truth about customers, without the siloed data sets and high levels of data duplication typically created by inflexible, siloed legacy systems.
- Embedded analytics for all the bank’s business operations, including recommendations for next best product in the front office, forecasts of profitability for product managers and operational dashboards in core banking.
- Self-service reporting that allows employees to get the answers they need without calling up the IT organization to set up a customized dashboard. (In a legacy core environment, Charles adds, the result “might take a month to achieve, with lots of back and forth between a business unit and IT. Even then, the resulting dashboards may not work particularly well”.)
Not all banks are well-placed to deliver on these objectives today. Charles points out that 75% of European banks suffer from above-average levels of data duplication and redundancy – a key symptom of ageing core systems. Historically, an above-average number of banks on the continent – six out of 10 – also find it challenging to deploy self-service data analytics across the organization. “It’s easier said than done: it’s actually a big transformation,” he says. “No bank that I’m aware of so far has achieved all of the steps required with 100% success.”
“Modern core banking is really the enabler for this, and other kinds of innovation, including and up to Generative AI. It enables staff globally to be more efficient. They have their dashboards, they have the information they need and it’s easily accessible. Risk and compliance staff can make decisions easily. Your front office staff have access to transaction data because there’s good integration with core banking. As a result, they can serve the customer better.”
Speed, flexibility and leveraging the cloud
“The real split in the banking industry is not regional, it’s not a question of the developed world versus the developing world,” says Charles. “The real dividing line is a culture of innovation versus a legacy mindset. A modern core will probably give you a lower cost of infrastructure, a lower cost for keeping the lights on, and therefore more money to spend on innovation,” says Charles. “But ultimately, it’s a big enabler for the bank across the board. It’s the nucleus that drives everything.”
Time to market: delivering innovation at speed
Today, banks need to respond rapidly to market signals, delivering new products and services in an agile fashion. Modern core systems – resilient, performant, data-driven and AI-enabled – enable this. Legacy cores, built for a slow-moving world, frequently don’t.
Typically, decades-old core systems have been subjected to repeated patching and workarounds, creating substantial technical debt. In many cases, it’s challenging to adjust the software code: the required skills are scarce. In addition, the way the code was written and a lack of documentation often creates the potential for unanticipated side effects. As a result, some legacy cores still resemble a medieval castle surrounded by a moat and drawbridge. Once, or possibly twice a year, the drawbridge is lowered to allow deployment of a small number of fixes – and perhaps some product innovation. Any changes create the need for exhaustive testing before going live with a revised system.
Software testing accounts for much of the additional time it takes for banks working with a legacy core system to bring new products to market. TVB’s database of banking technology KPIs reveals a yawning gulf between best-in-class performance (eight to 10 weeks) and worst-in-class (“an average of around 30 weeks”). “It’s a major difference,” says Charles. “The spread is huge.”
Platform effects: building on a flexible foundation
“There is a very big appetite for conversations about the business value of technology investment,” says Charles. “When we get into this conversation with banks, we talk to them about two broad objectives. The first involves doing the same thing, but better: for example, improved TTM.
“The second objective involves the potential to do new things in new ways. For example, exploring new business models like Banking-as-a-Service (BaaS), Banking-as-a-Platform (BaaP) and the potential of Open Banking and embedded finance.”
Business models like these rely on the flexibility created by a platform approach. McKinsey describes a platform as a way of making core functions “more accessible, reuseable and better able to support products”. Modern core banking systems create this kind of flexibility by offering composable architecture, sophisticated data management and efficient software tooling. Banks with the ability to leverage these advantages can distribute digital services across multiple channels, collaborating with new partners to create new revenue streams.
The cloud: leveraging its full potential
Modernizing core systems is often a major milestone on the journey to the cloud, which allows banks to improve scalability, resilience and performance and creates the ideal circumstances for accelerated software engineering techniques including DevOps and Continuous Integration and Delivery (CI/CD).
Not every bank is ready for the cloud yet. Nor are a number of regulators. But banks need a roadmap offering the right options for a journey they will almost certainly undertake in the future.
This explains why the vast majority of Requests for Proposal (RFPs) that Temenos receives today for any kind of core banking replacement ask about the company’s cloud and SaaS credentials. “I think it’s a way for them to glean just how modern and flexible your core solution is, by virtue of the answers you give,” says Cormac Flanagan, head of product management at Temenos. “They all want features of SaaS like application monitoring, ease of deployment and ease of upgrade. Even if they do deploy initially on premises, they’re interested in developing confidence about your ability to deliver a SaaS solution.”
For Flanagan, there’s no doubting the long-term durability of this proposition. “A decade ago, larger banks preferred the in-house route to developing core systems. Today, we’re writing code for 800 banks around the world and investing very substantially in banking software for use on-premises and in the cloud. The market has matured, and it’s driving towards the adoption of third-party software,” he says.
“When you put that together with the sheer scale of the technology and infrastructure investment by the hyperscalers, the end results will dwarf what any one bank can do, barring perhaps one or two examples worldwide. For me, there’s no doubt: the arc of history is bending towards the cloud and software vendors like Temenos.”
