{"id":25719,"date":"2022-01-26T14:44:21","date_gmt":"2022-01-26T13:44:21","guid":{"rendered":"https:\/\/www.intellias.com\/?p=25719"},"modified":"2023-10-04T14:30:26","modified_gmt":"2023-10-04T12:30:26","slug":"modernizing-legacy-banking-systems-how-to-get-it-right","status":"publish","type":"blog","link":"https:\/\/intellias.com\/modernizing-legacy-banking-systems-how-to-get-it-right\/","title":{"rendered":"Modernizing Legacy Banking Systems: How to Get It Right"},"content":{"rendered":"

The banking sector has a lot of external stressors: regulatory pressure, TechFin and FinTech competition, and rising customer demand for faster\/better\/cheaper services. To put out all those fires, banks often resort to patches. But a quick interface fix here and an app improvement there won\u2019t change your odds of success in the long run. To stay profitable in the 2020s, banks need to look straight into their core systems.
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46% of bankers see these legacy systems as the biggest barriers to the growth of commercial banks.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\tFraedom<\/span> <\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section><\/p>\n

The case for modernizing financial legacy software systems<\/h2>\n

As we mentioned in our first post about digital innovations in banking, pioneering new customer-facing solutions is just one piece of the puzzle. To support those new solutions, you\u2019ll also need to modernize your legacy systems<\/a>.<\/p>\n

Legacy banking software, lovingly dubbed \u201cthe next financial crisis\u201d by some industry analysts, is a major constraint, preventing traditional banks from attaining the same rapid product scaling capabilities as more nimble digital banks have.<\/p>\n

The word crisis may sound strong. But when you look at the data, crisis may be an understatement:
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IBM released its flagship System\/360 back in 1964. Today, 92 of the world\u2019s top 100 banks still rely on these 50-year-old IBM mainframes.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\tFraedom<\/span> <\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section>
\nOn average, larger incumbent banks can now have 20+ different core legacy banking systems<\/a> at their disposal. Unraveling these setups becomes more challenging over time, as most were written in COBOL \u2014 a trendy programming language in the 60s and 70s. As you might guess, finding a COBOL programmer these days isn\u2019t easy, since most are enjoying a happy retirement.<\/p>\n

What\u2019s even more aggravating is that it\u2019s hard to identify how new code (e.g. Java) or new tech (e.g. cloud technology) will interact with older COBOL systems. These factors make it hard to gauge where an integration issue may arise.<\/p>\n

As a result, some banks end up being powered by so-called spaghetti connections \u2014 a setup where every system element is connected to everything else, and pulling one string can create a crippling operational knot.<\/p>\n

But despite being one very expensive plate of spaghetti \u2014 legacy financial systems eat up 60% to 80%<\/a> of banks\u2019 total IT budgets \u2014 few banks are rushing to modernize their systems.<\/p>\n

But here\u2019s the deal:
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With every new feature that you are adding to the existing system, you are making migrating off that system harder.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\tDavid Knott, <\/span> HSBC Chief Architect<\/span><\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section><\/p>\n

So how can you muster the strength (and gain buy-in) for a legacy systems modernization project?<\/b><\/p>\n

Start by building a strong roadmap, clearly showing which financial systems should be unbundled first and demonstrating the risks and potential gains.<\/p>\n

4 priority areas for backend banking transformations<\/h2>\n

\"Modernizing<\/p>\n

1. Data governance & management platform<\/h3>\n

In 2020, financial data can reside anywhere thanks to cloud technologies. Yet it remains stranded in legacy systems. Or uncollected for the lack of ability to do so in real time.<\/p>\n

As a result, incumbent banks cannot compete with digital players in terms of personalized up-sells\/cross-sells\/advertising, cannot deploy innovative analytics-driven solutions such as personal finance management<\/a> or coaching apps, and cannot experiment with predictive analytics, artificial intelligence (AI), and machine learning.<\/p>\n

As Luis Moreira-Matias, the Head of Data Science at Kreditech, said in :
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Personalization or the ability to make the right offer at the right time \u2014 either to grab a customer or to make a profit out of them \u2014 is a key factor for banks to increase customer lifetime value. Such personalization is impossible without big data analytics and data science.<\/p>\n\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t <\/span>\n\t\t\t\t<\/small>\n\t\t\t<\/blockquote>\n\t\t<\/section><\/p>\n

Neither can incumbent banks embrace real-time business intelligence and move towards advanced big data analytics without having a strong data management platform.<\/p>\n

Moreover, shifting to a unified data platform can majorly improve data traceability, accountability, and, subsequently, reporting capabilities to help banks stay compliant with the latest industry regulations. It also can make payment system architecture<\/a> more resilient to security vulnerabilities.<\/p>\n

To capture this host of benefits, your data governance framework should strongly align with a wider IT governance framework (discussed in the next section).<\/p>\n

One way to do this is to map each business driver to a respective IT objective and then to a technical solution. For example:<\/p>\n

\"Modernizing
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Learn more about our experience building data management platforms<\/p>\n

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2. Cloud migration and transformations<\/h3>\n

Cloud computing has made significant leaps in terms of efficiency, affordability, and security, resulting in a host of new opportunities for banks:<\/p>\n

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\nSource: Accenture \u2014 Moving to the Cloud: A strategy for banks in North America<\/a><\/em><\/p>\n

Replacing struggling on-premises legacy systems and breaking away from the costly equipment replacement\/upgrade cycle is one obvious reason for migrating to the cloud. Indeed, the total cost of ownership ends up being attractive for most financial institutions.<\/p>\n

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Read our cloud vs on-premises guide for more insights on the matter<\/p>\n

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Apart from causing this major shift in IT spending, the cloud empowers banks to grow and scale through the consumption of external services connected via APIs.<\/p>\n

Rather than building a new product from scratch, you can seamlessly integrate existing solutions from vendors and other FinTechs. Or you can go a step further and start assembling an ecosystem of financial and non-financial products available to your customers via a single interface to embrace the marketplace banking model<\/a>.<\/p>\n

The best part? You can attempt gradual IT modernization, bringing one element of your legacy systems to the cloud at a time, as Deloitte<\/a> suggests.<\/p>\n

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\nSource: Deloitte \u2014 Getting cloud right: How can banks stay ahead of the curve?<\/a><\/em><\/p>\n

Shifting towards a portfolio of cloud services and delivery models (SaaS, IaaS, and PaaS) can help you gradually unbundle your legacy software without causing major operational disruptions.<\/p>\n

Depending on your business priorities, you can pick and choose your cloud battles. For instance, Credit Suisse partnered with Cloudera<\/a> to launch an enterprise-wide big data analytics platform rather than building all the infrastructure from scratch, achieving a 38% reduction in total cost of ownership and faster access to cutting-edge analytics capabilities.<\/p>\n

Ultimately, the key to reaching the cloud is having a clear roadmap that includes the following steps:<\/p>\n