Data accessibility is a major challenge for all financial institutions

By André Casterman, Chief Marketing Officer at INTIX, the data management fintech.

Whilst transaction data is firmly established as a new economic asset, financial institutions are facing several challenges to utilise and monetise the vast amount of transaction information going through their systems.

Challenges impeding data monetisation

Following regulatory requirements, most financial institutions (FI’s) have taken greater care at organising their “data”. The archiving, reporting and screening obligations have created many dependencies on their ability to search through and report on transactions, whether residing in long-term archives or in production systems. Implementations have however mostly been achieved at department or system level in a rush and as part of the regulatory objective, thereby often missing the big picture.

The real opportunity for bankers though is very different and calls for taking a more strategic approach. Whether leveraging new “Artificial Intelligence (AI)” capabilities or not, financial institutions have realised that monetising the vast amount of transaction data ought to be their next ambition level. Pro-actively for business development rather than reactively as done so far for regulatory reasons.

Financial institutions have realised that monetising […] transaction data ought to be their next ambition level.

In order to get there, financial institutions need to become aware of four types of “Data” challenges: accessibility, visibility, infrastructure and delivery. Practical issues are usually reported as follows:

  • Accessibility: the high number of internal systems processing transactions is a typical roadblock to access transaction data in a timely and cost efficient way
  • Visibility: the complexity to aggregate transactions stored in various formats and using different semantics makes it very hard to produce a comprehensive view on transactions and related events
  • Infrastructure: addressing “big data” requirements within existing transaction processing systems and technologies drastically increases the cost of the implementation, with a low chance of success
  • Delivery: mixing data-related development priorities with those aimed at improving transaction processing systems is only a guarantee for delays and failure.

Taking a “Data Management” focused approach

The importance of monetising data as well as the challenges that lie ahead call for taking a focused approach as outlined below. By handling your data management implementation separately from your transaction processing priorities, FI’s will increase their chances of success.

As depicted below, the first step is to define your own data-centric strategy (step 1) and to then acquire a separate budget and infrastructure for addressing user requirements (step 2). In order to get there in a pragmatic way, defining a minimum viable product (step 3) as initial deliverable will prove useful. This is usually considered as a preliminary step before embarking on the set-up of a production-level data management infrastructure (step 4) to handle additional requirements.

Specialised data management technology is required

Data management solutions designed specifically for the financial services industry help financial institutions address above mentioned challenges. They do so by combining the appropriate high-performance technology with a deep know-how of the various transaction types and data sets. When assessing available solutions, FI’s should revisit them against the four types of challenges as proposed below:

  • Accessibility challenge: the data management technology must enable to connect with hundreds of internal systems seamlessly across legacy and modern technologies
  • Visibility challenge: the technology needs to be provided jointly with deep expertise in financial messaging in order to be able to handle all industry standards. This is key to shield end-users from the complexity of navigating through various messaging formats and semantics
  • Infrastructure challenge: the ideal solution must provide a dedicated high-performance data management layer to address all reporting, tracking, measurement, monitoring and alerting requirements
  • Delivery challenge: upgrades to such data management solution are to be prioritised, developed and rolled out independently from those applied on transaction processing internal systems. FI’s must avoid integrating “data” requirements within existing processing systems.

As depicted on below diagram, the specialised data management layer or solution should be implemented separately from the plethora of internal systems. A Google-like data indexation method ensures transaction data evolving in the processing systems is continuously kept in sync with the data management layer.

The specialised data management solution should be implemented independently from the plethora of existing and future transaction processing systems

With INTIX, the high-level set-up looks as follows:

INTIX makes it happen

By combining advanced big data technology and expertise in financial messaging infrastructures and standards, INTIX brings the appropriate set of capabilities to deliver a comprehensive data management solution. Business requirements related to transaction reporting, tracking and metrics as well as exception monitoring and alerting can all be addressed in a successful and efficient way.

INTIX will help you design and implement your data management strategy in order to accelerate the monetisation of transaction data. As depicted below, the INTIX solution brings a unique mix of capabilities:

  1. Specialised data management technology which delivers high performance on large data sets at a reasonable cost and which avoids impacts on legacy systems
  2. Exclusive focus on financial services industry which brings deep and up-to-date expertise as well as a complete library of all messaging formats and semantics
  3. Independent Infrastructure which ensures data management priorities are implemented as part of a separate infrastructure and managed independently. This avoids any interference with the priorities driving the upgrades of transaction processing systems
  4. Agility and scalability during both implementation and maintenance phases.

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