By Emil Eifrem, co-founder and CEO of Neo4j 

Legacy systems are usually large in terms of both their code base and functionality, which can make modernisation problematic. Data expert Emil Eifrem explains how graph databases can help

Emil Eifrem

Financial institutions are struggling with legacy systems. In the 1970s, banking systems were written in COBOL (common business-oriented language), a skill that is becoming harder and harder to find. These systems were not built for the digital age. These systems weren’t built to change either, which makes updating them difficult.

Faced with new competition from FinTechs and other technology companies, banks are being forced to rethink their digital transformation. In doing so, tier one banks and smaller financial institutions are being held back by systems and architectures.

In an ideal scenario, financial institutions would replace outdated legacy systems with new, integrated infrastructures that could support business growth in real-time. But this is highly expensive and not without risk such as costly downtime if there are compatibility issues.

Legacy systems have inherently gone through many changes, making agile change extremely difficult. As a result, scaled change is seen as the way forward and one that has worked for investment management company Vanguard.

Embracing Change at a Large Investment Management Company

Vanguard is one of the world’s largest investment management companies with more than $3.5 trillion in assets under management. It’s also the largest provider of mutual funds and the second largest provider of exchange-traded funds (ETFs). In addition to mutual funds and ETFs, Vanguard offers brokerage services, variable and fixed annuities, educational account services, financial planning, asset management and trust services.

The company employees 17,600 people worldwide and has more than 20 million trusted investors in around 170 countries. Headquartered in the US, Vanguard also has offices in Europe, Asia and Australia.

Vanguard migrated across to a modern microservices based infrastructure by enhancing the management and quality of its legacy code base, which in this case was built around enormous Java systems. Although the transformation was seen as essential, it was a gargantuan task as some of the old Java archives had 4 million lines of code that needed to be cut back.

Moving Java archives across to microservices required the careful management of a large number of components. To achieve this, Vanguard’s in-house IT team initially started to manage services in a spreadsheet compiled over twelve months. Despite trying to carefully group areas and document dependencies, the IT team recognised this approach was not working.

The Vanguard IT team saw that the management of modules and services was actually a “graph problem”. Graph databases model complex problems in a way that is easier to work with than other database approaches, in particular standard relational technology.

Graph databases are a powerful way to model how data works and connects in the real world. Modelling this complexity using relational databases results in lengthy queries that are technically difficult to build and expensive to run, with performance sliding as the dataset size grows.

The Vanguard IT team was no stranger to the concept of graph databases. The technology has garnered interest in financial services. All of North America’s top 20 banks rely on graphs for data lineage, customer 360 and regulatory compliance. Meanwhile, eight out of the ten top insurance companies have used graph technology to fight fraud and effectively manage data.

Fuelling Digital Transformation

 Vanguard’s IT team started with a simple graph database model. This was used to model the logic and connections inside the computer code, and it proved to be a very productive route to managing, reading and visualising the organisation’s data.

By utilising graph technology’s analytics capabilities, Vanguard’s IT team was also able to measure its code against current software engineering best practices and identify where to make improvements to align it with today’s required standards.

Data relationships were quickly visualised and risk reduced by simplifying and clearing up the code’s components. Via graph database technology, Vanguard’s IT team also gained full 360 visibility into its legacy application. This allowed for impact analysis to be carried out before modernising the older systems to ensure a smooth, safe migration. Internal stakeholders were able to track metrics through an intuitive dashboard to ensure the project was on track.

Having seen the power of graph database technology in action, Vanguard is now leveraging it for future application development in the company, ensuring new development fits with the overall architecture of the organisation.

Instant replacement of legacy technology with new systems is too expensive and risky for most banks with highly complex core infrastructures. Graph technology facilitates a phased approach to transformation that provides increased efficiencies, cost reduction and a faster time to market.

The author is the co-founder and CEO of Neo4j, the world’s leading graph database