GRAPH DATABASES HELPING BANKING WITH DIGITAL TRANSFORMATION

The author is Emil Eifrem, co-founder and CEO of Neo Technology, the company behind Neo4j (http://neo4j.com/), the world’s leading graph database 

Emil Eifrem

Neo Technology’s Emil Eifremlooks at how dependency management techniques and technologies are being utilised in financial services to develop their technology infrastructure to support digital transformation (DX) 

Many banking systems are outmoded and outdated, holding back banks from making digital advances towards DX.

Technology is paramount to banks’ processes and operations. Its infrastructure provides the central artery that powers business units, back office functions and ultimately serves customers. These very systems are the key enabler to DX. They are also central to the digital disruption that is going on in every corner of the banking industry.

But despite the necessity for banking to look at new and innovative digital ways of working, or risk becoming just a back-office operation, financial institutions are held back by outmoded and outdated systems and architecture. At the same time banks have been moving to lower costs to offset the pressure on profits.

Many of the legacy systems are a complicated maze that has been added to over the years. Fully replacing these complex systems would be the best way to move forward.But the cost is prohibitive. The good news, however, is that processes and tools for managing these systems have been greatly enhanced resulting in performance upgrades.

Connections are key to dependency management 

Financial institutions can of course use a number of best practices, notably best-in-class dependency management systems that tap into the power of graph technology. For example, one customer has instigated graph technology to enhance its investment trading platform established to support traders in a number of functions including currencies. It knew it had to upgrade as it was facing increased complexity and inefficiency through a lack of visibility into the effect of proposed changes to one of its core applications.

Hundreds of developers where involved in managing the transformation on this mission critical trading platform. The big challenge, as in all application change management, was to control what is known as the ‘ripple effect’, when one small revision can affect the work of other programmers in the team. In this scenario it is heightened by complex compliance workflows, continued legacy usage and in some cases, manual processes.

To manage the complexities of change and at the same time meet compliance objectives, a bespoke internal dependency management tool has been developed.

This new system enables developers to box any code change and relevant modules into a safe place. Whenever a change to a process is requested, a special release of the system is created for full testing first.

If the special release does not pass stringent testing and quality assurance procedures, the software requests the programmer revisit the process. This alert is repeated until the change passes all the tests.

This approach radically simplifies the change management process, while significantly contributing to overall programming quality. The solution also automates the entire process, recording all the information needed for monitoring and Q&A. This not only saves time, but limits errors.

Graphs take centre stage 

The only data framework found that could manage such a level of multiplicity in the banking arena was graph database technology, because of its innate power.

The graph-based platform has proven such a success in change management processes that the bank is now looking to roll it out to other departments across the banking group.

DX is no longer a choice for banks, it is a journey they must make to deal with increased competition from traditional and non-traditional players. A few banks have started to look at dependency management techniques, but there are many more that need to as part of their digitisation strategies. They will quickly see that the enhanced efficiency and growth it provides will also help them mitigate risk. This has to be a win-win situation.

The author is Emil Eifrem, co-founder and CEO of Neo Technology, the company behind Neo4j (http://neo4j.com/), the world’s leading graph database 

Emil Eifrem

Neo Technology’s Emil Eifremlooks at how dependency management techniques and technologies are being utilised in financial services to develop their technology infrastructure to support digital transformation (DX) 

Many banking systems are outmoded and outdated, holding back banks from making digital advances towards DX.

Technology is paramount to banks’ processes and operations. Its infrastructure provides the central artery that powers business units, back office functions and ultimately serves customers. These very systems are the key enabler to DX. They are also central to the digital disruption that is going on in every corner of the banking industry.

But despite the necessity for banking to look at new and innovative digital ways of working, or risk becoming just a back-office operation, financial institutions are held back by outmoded and outdated systems and architecture. At the same time banks have been moving to lower costs to offset the pressure on profits.

Many of the legacy systems are a complicated maze that has been added to over the years. Fully replacing these complex systems would be the best way to move forward.But the cost is prohibitive. The good news, however, is that processes and tools for managing these systems have been greatly enhanced resulting in performance upgrades.

Connections are key to dependency management 

Financial institutions can of course use a number of best practices, notably best-in-class dependency management systems that tap into the power of graph technology. For example, one customer has instigated graph technology to enhance its investment trading platform established to support traders in a number of functions including currencies. It knew it had to upgrade as it was facing increased complexity and inefficiency through a lack of visibility into the effect of proposed changes to one of its core applications.

Hundreds of developers where involved in managing the transformation on this mission critical trading platform. The big challenge, as in all application change management, was to control what is known as the ‘ripple effect’, when one small revision can affect the work of other programmers in the team. In this scenario it is heightened by complex compliance workflows, continued legacy usage and in some cases, manual processes.

To manage the complexities of change and at the same time meet compliance objectives, a bespoke internal dependency management tool has been developed.

This new system enables developers to box any code change and relevant modules into a safe place. Whenever a change to a process is requested, a special release of the system is created for full testing first.

If the special release does not pass stringent testing and quality assurance procedures, the software requests the programmer revisit the process. This alert is repeated until the change passes all the tests.

This approach radically simplifies the change management process, while significantly contributing to overall programming quality. The solution also automates the entire process, recording all the information needed for monitoring and Q&A. This not only saves time, but limits errors.

Graphs take centre stage 

The only data framework found that could manage such a level of multiplicity in the banking arena was graph database technology, because of its innate power.

The graph-based platform has proven such a success in change management processes that the bank is now looking to roll it out to other departments across the banking group.

DX is no longer a choice for banks, it is a journey they must make to deal with increased competition from traditional and non-traditional players. A few banks have started to look at dependency management techniques, but there are many more that need to as part of their digitisation strategies. They will quickly see that the enhanced efficiency and growth it provides will also help them mitigate risk. This has to be a win-win situation.