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Automate Reporting to Drive Value

Automate Reporting to Drive Value
Financial services are in the midst of an assumption revolution. Accelerated by the global pandemic, many of the strongly held views of what is, and what is not possible have not only been challenged but shattered. In the ‘front office’ these are widely reported, as just one example, the FT reported that in Q3 2020 Santander completed 80% of its transactions digitally in the UK, and NatWest had seen the use of video calls with customers jump from just 100 per month to 9,000. But all these digital applications put immense strain on the back-office functions needed to support them. Automating not only the provision of these services, but the reporting and governance needed to satisfy regulatory demands has become a pressing requirement.  At the same time, the increasingly real-time nature of financial services, and the transformation of risk, are leading many regulators to call for more data more often. But banks should see this as an opportunity to modernise and automate expensive, labour-intensive processes. 

After more than two decades of increasing layers of regulation imposed after 9/11 and the banking crisis of 2008, many institutions were cautiously optimistic that they had managed the regulatory reporting burden and could switch attention and investment to other areas. However, Brexit and then COVID changed the game once again with demands for more granular and more frequent data on risk and performance. This new environment demands more than a new set of reports and data sets – it requires a fundamental rethink about how to work with regulators.

The old approach was to create new reports for every new requirement imposed. This made some sense in the ‘old world’ of regulations with long lead times to implementation and enforcement – but it was still labour-intensive and expensive to comply. In today’s world with almost constant incremental change, it makes no sense at all. Using armies of accountants to juggle Excel sheets and build new reports based on custom data sets every time is an unsustainable nightmare for banks already facing extreme margin pressure in a low-interest global economy.

Automation of reporting provides a solution and an opportunity to improve the quality, granularity and speed of reporting. To successfully automate reporting, banks must take three fundamental steps; Create a single, trusted enterprise data platform that supports all regulatory reporting requirements; build flexible analytic models to replace inefficient manual processes; catalogue and share these models as ‘data products’ that can be re-used, re-combined and re-deployed to meet changing requirements. 

In many cases banks already have the foundations for single sources of shared data. The Teradata systems that sit at the heart of many banks represent the perfect platforms for a single trusted view of all the data needed for reporting. Rather than extracting and creating silos of data for reporting, advances analytics including machine learning and AI models can be written to run in these data warehouses. Not only does this allow models to leverage the speed and scale of Teradata to process millions of queries against billions of records, but it provides the most granular, up-to-date and complete set of data to drive reports. 

Our Analytics 123 strategy allows data scientists to use the modelling languages of their choice to build and test models and simply deploy them to score live data. Crucially, the approach emphasizes re-use and repurposing of the data features that demonstrate utility, massively reducing the heavy lift of data wrangling and allowing data scientists to be far more productive.  Instead of building every report from scratch, teams can quickly assemble, or enhance models to meet new requirements using previously tried and tested elements. Storing and cataloguing these features in an Enterprise Feature Store makes them easily discoverable and re-usable to support new models to meet new reporting requirements. 

Which brings us to another assumption long overdue a challenge. Regulatory reporting does not have to be a time and resource intensive cost. Automation of reporting removes the need to tie up large teams of accountants simply to find, prepare and produce reports. These individuals can instead be better deployed in value-driving roles. Plus, working from a common, comprehensive view of real-time data will also improve the accuracy and quality of regulatory reporting. Not only will this meet regulator’s demands for more timely information without increasing costs, but it will help multi-jurisdictional banks handle the nuances of individual regulators’ demands more efficiently. Core data products that meet the majority of requirements can be simply tailored to deliver the exact data requested. Finally, automation reduces mistakes from data transcription and human error which in turn saves time and improves reputation with regulators as revised, corrected and updated reports are avoided. For too long change has been resisted, using the assumptions that it is too hard, too costly and too risky to change existing processes. Today’s environment has made these processes untenable whilst simultaneously demonstrating that change is needed and possible. Automating for value is a requirement and an opportunity that banks must embrace. 
Portrait of Simon Axon

Simon Axon

Simon Axon leads the Financial Services Industry Consulting practice in EMEA. His role is to help our customers drive more commercial value from their data by understanding the impact of integrated data and advanced analytics. Prior to taking up his current role, Simon led the Data Science, Business Analysis & Industry Consultancy practices in the UK & Ireland,  utilising his diverse experience across multiple industries to understand our customer’s business and identify opportunities to leverage data and analytics to achieve high-impact business outcomes. Before joining Teradata in 2015, Simon worked for the Sainsbury's Group and CACI Limited.

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