Utilizing Data for Competitive Advantage

Utilizing data for competitive advantage

Macro-economic factors are raising the huge volumes of data already managed by banks to new levels. The pandemic has forced financial institutions to further digitize their operations, and government assistance programs have increased customer numbers as individuals and corporations need access to funds. For example, many businesses which might not have required support in the past have had to apply for extra funding and loans.  Homeowners have been re-evaluating their requirements as they adapt to the new realities and take out loans either to move or modernize their existing property.

The result is an influx of businesses and people newly interacting with financial institutions. With more and more data out there, banks have plenty of opportunities to gain valuable insights. However, they can struggle to make sense of it and leverage it for competitive advantage.

To really unleash those opportunities, banks need to ensure that they have secured data rights of use from customers and operate within a highly secure, compliant banking platform. There will then be endless possibilities to transform the data into valuable insights.

The Growth of Open Banking . . . finally

We’ve all been on an interesting journey with Open Banking. Back in 2018 there was great optimism, but enthusiasm slowed and some became cynical about the potential benefits. However, the pandemic has accelerated the digitization of the global economy and there is growing evidence to suggest that Open Banking is going to be a key driver of growth.

  • The value of the Global Open Banking market is estimated at $43bn in the next five years.
  • 87% of countries are now offering Open Banking in some form or another.
  • In November 2020, EY claimed that since the first lockdown they had seen a 72% rise in the use of fintech apps in Europe.

The idea that Open Banking has stalled is a fallacy, and the revolution is at last getting under way. There are two major considerations in using data to improve organizational performance; first, identifying clear benefits and secondly, identifying the barriers to success.

Commercial benefits in data management

The successful aggregation and analysis of masses of data will give financial institutions a deeper and broader view of performance and help them to understand how customers are interacting across channels. These connected experiences can be accessed via business intelligence dashboards and can help across many lines of business, including payments and lending.

In the case of Payments, Operators can see and analyze payments and foreign exchange transactions, to identify processing errors or better understand where bottlenecks exist. This can be across multiple product sets and channels.
These business intelligence tools can, for example, help loan analysts understand application problems and recommend improvements. Is the form too long or too complex? Are we gathering all the information needed to make a decision?

Data can also provide the basis for action, such as to include predictive and prescriptive analytics. These models provide banks with a much richer information source to guide their planning. Predictive analytics indicate what is likely to happen based on previous behavior while prescriptive analytics provide specific actions that a bank can take based on the findings.

Better understanding and application of the data available can have a positive impact on profitability.

More data means more powerful decision making

Imagine being able to aggregate the data from several institutions and understand even more about the behavior of consumers and businesses. How helpful would it be to compare your own data with that of your peers?

Being able to aggregate anonymized data across institutions builds a much more accurate picture of where transaction and lending processes are succeeding or failing. The data cannot be associated with individual customers so there is no operational or legislative risk. For example, dynamic peer group benchmarking is available in Fusion Mortgagebot Data Insights and enables clients to compare their performance across key metrics with their most similar peers, determined by a machine learning model. This helps the financial institution eliminate loan processing bottlenecks and enhance business strategy.

A financial institution can also use its own aggregated data to provide better results.  Finastra’s Fusion Retail Analytics allows banks to detect churn and identify the next best product to offer its existing customers. For example, by identifying the customer behavior that precedes churn, banks can spot the warning signs and intervene before a customer switches to another bank’s Savings or Current account. Innovative banks are regularly using data aggregation and peer comparisons, and making more use of cutting-edge open banking solutions, often developed by leading fintechs.

The data ecosystem

How do financial institutions find these effective solutions? A data ecosystem, which provides banks and fintechs with structured datasets, is the perfect option for the creation and adoption of new solutions. Through Fusion Data Cloud which is a part of Finastra’s FusionFabric.cloud Open Banking platform, fintech partners have already launched valuable data-driven market solutions. Some examples include:

  • BankBI – a cloud based out-of-the-box financial performance management application, enabling financial institutions to measure, monitor and manage their business in real time using industry standard ratios and dashboards.
  • Vector Risk - an app that aggregates trading book data to provide banks with greater insights and meet Fundamental Review of the Trading Book compliance requirements. This means that financial institutions spend less time gathering information and more time making decisions to help customers.

These applications range from consumer banking and treasury management to support for subject matter experts. The banking industry has much to gain from open, shared, yet anonymized data.

A new way of working

Direct collaboration with financial institutions and formal hackathons help identify common problems and develop potential solutions.  The ideas can be accessed via an open banking platform to enable those that are most promising to be built into a proof of concept that can be validated and pushed to production.

As we continue to foster innovation, more core banking data sets are enabling Finastra and our fintech partners to develop a constant flow of new solutions to extend the capabilities of banks still further. We believe that this trend will not only create new opportunities for banks to monetize a wide range of products and services, but will also herald a new era of customer service and profitability.

The great news is that access to this expertise, through an Open Banking platform, is the first step towards achieving a competitive advantage over those operating with the methods of the past.

Three years since PSD2 marked the start of Open Banking, the UK has built a world-leading ecosystem, OBIE
How COVID-19 has sped up digitisation for the banking sector, EY
Is It Finally Time for Open Banking’s Debut in America?, The Financial Brand
Open Banking Report, PYMNTS.com

Amber has more than 16 years of experience in marketing and product management and over 9 years of industry experience in data, analytics, and financial services. As Head of Data and Analytics at Finastra, she is focused on developing and launching new data products and scaling the Finastra business for data partnering and data commercialization. She loves working with the Finastra Innovation team to develop data-driven proof of concepts and turning those into production-ready solutions to drive business results for clients.

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