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Why legacy isn’t bad, it’s just misunderstood | Fintech Finance

January 25 2021

Why legacy isn’t bad, it’s just misunderstood

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Legacy has long been the scapegoat of the financial services sector. Blamed for being old, out-dated and siloed with integrated systems seen as the holy grail. While it is often true that legacy systems demand our attention, much of this technology is far from obsolete – and works well. 

Darragh Pelly, COO and co-founder, Reitigh explains why those organisations that fail to see the value in their legacy systems are really missing a trick.

Understanding legacy systems 

We first need to re-think how we view legacy systems. If companies think of them as foundations rather than failings, there is the potential to build on them and still create successful digital transformation projects. To do that, the digital transformation mindset needs to change. 

Transformation never ends 

Zendesk recently found that only one in four (26%) firms recognise that transformation is a continuous process — suggesting that the majority still see it as a destination rather than a journey. The truth is that these transformations are never one-off initiatives. They are also rarely finished. Rather, transformation is a continual iterative process that evolves into the future alongside market and business requirements.  

This misconception explains the most common failure in many digital transformation projects: they try to do too much in one go. 

There is no need to overhaul everything at the same time. The primary focus instead should be on getting legacy systems to talk to modern platforms (today and tomorrow). This integrated approach will enable firms to transform the front-end efficiently and cost effectively – utilising the existing legacy back office effectively – whether they are looking to build a new broker portal or improve interactions with clients. 

Getting automation right when it comes to processes (RPA vs STP) 

When it comes to “Automation” there are two very different and often confused approaches:

  • RPA – Robot Process Automation: This involves automating manual user activity. Robots are trained to click buttons and enter data through the same screens manual users interact with currently. Robots will scrap data from emails and forms and enter this data into excel spreadsheets or frontend user interfaces of existing admin systems. 
  • STP – Straight Through Processing: This involves removing manual entry/systems. All data is transmitted between systems electronically. Excel spreadsheets and user interfaces are made redundant. They are replaced by APIs (application programming interface) and direct database links. Effectively this means that data is posted directly from one system into another. The whole process becomes automated at its core.

    • A rudimentary comparison is to think of RPA as automating your hands, whereas STP is automating your head.

    When it comes to automating processes the first and most fundamental question to ask is – “Is the process as it exists now correct or good? i.e should we spend time and money to automate this process, or should we implement a new automated process.” The point here being that if we automate a broken/bad human process then the robot will just achieve the same outcomes as the human – we are no better off for the money we have spent. In this case STP is the answer, not RPA. On the other hand, if the process is good, but just manual, then RPA may be the most cost–effective solution. 

    By way of example, take the recent news of Microsoft Excel causing Covid-19 results to be lost. Public Health England (PHE) built an “automated process” in excel to gather C19 data. But, because of the size limitations of Excel, not all data was recorded. It is estimated that nearly 16,000 coronavirus cases went unreported in England. This is one example of automating a fundamentally bad process. Automation achieved the same bad outcome – just faster.

    Do you speak legacy? 

    Legacy programmers run many legacy systems and applications. Now, with an increasing number of developers heading towards retirement, financial services firms need to get a solid succession plan in place. 

    The pressure is on to bring in multi-lingual talent.  

    The need for people who can translate between business and the IT teams is very real, as is the need for those who can form a link between legacy systems and modern platforms. Specialist consultancies – with carefully selected expertise built-in – play a lead role here and will continue to do so throughout 2021.

    These tech translators can focus on the processes worthy of automation and transformational projects that can sit on top of legacy systems creating innovation and value from within. 

    Companies wanting to avoid risky and costly projects must not only learn the language of legacy, but must speak it fluently. In this respect, domain knowledge of both the data and the business which it supports is key to quickly and effectively delivering solutions to meet new market and regulatory demands.

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