Digital transformation trends that are shaping banking   

digital transformation banks

PUBLISHED: 12 NOVEMBER 2019
AUTHOR: FINTECH CIRCLE

Cultural adaptation is the step zero of digital transformation. Encouraging an entrepreneurial spirit by dedicating internal groups to find digital solutions has become the new normal for financial institutions. Banks are striving to become technology companies by automating back office work flows and increasing customer satisfaction with low friction interfaces and lower cost services.

Incumbent intrepreneurs look to transformation trends that will keep banks future proofed while challengers and tech giants move in on a fintech market where banks have lost a quarter of the payments franchise to new players. Data has fuelled the growth of fintech with open banking starting to take a lead role in developing game changers such as AI and cloud.

Andy Warren, Open Banking IT Lead, Santander UK, explains: “Banks have all been under major pressure to deliver the regulatory roadmap, now that is more or less complete they will have the capacity to focus on hardening their implementations.”

Chris Michael, Head of Technology at The Open Banking Implementation Entity (OBIE) adds: “2020 is a big year for open banking. In the UK, we are heading towards 200 authorised third party providers that are bringing opportunities to consumers and businesses to help them manage and improve their finances to transforming how they interact with the wider industry.

“Open banking is not just about developing a great API Standard. It requires firms to implement this correctly, with a high level of reliability and a great user experience. From the beginning, open banking has been ‘customer-first’, this means creating an environment that is secure, but also provides consistency to customers.

“As more consumers and businesses begin to reap the benefits of open banking, there is a realisation that we can begin to extend the APIs to other financial products such as loans, savings and investments that will allow consumers to see all their financial information in one place.”

Open banking 

Open banking is creating a network effect by building a collaborative ecosystem of partners. Financial service companies can seamlessly integrate new products and services into their customer experiences enabling businesses to co-create value with external stakeholders.

Accounting, finance and money transfer services are just some of the latest third party integrations customers have been benefiting from. As financial services collaborate with fintechs new lines of business are becoming available to previously underserved markets.

By strongly partnering with IT for the adoption of new technologies a data driven culture can be achieved to leverage the potential of an applications network for a connected customer experience.

Public cloud 

In recent news a long time hold out between banks and cloud services may have come to an end with Bank of America and IBM who are launching a public-cloud computing service for banks while meeting regulatory compliance. This heralds a new era where previously banks have been reluctant to store data on the cloud with both privacy and security a primary concern.

Regulators are working with providers such as AWS to understand work flows that can include the best cloud security experts as opposed to on location servers belonging to non tech organisations. As with BoA the billions saved a year on infrastructure is not the only motivation for banks to migrate to cloud. Software development and big data technology used for applications such as machine learning becomes quicker to deploy.

Artificial learning and machine learning

Banks and financial services are increasingly investing in AI capabilities for applications such as voice recognition, recommendation engines, predictive analytics and process automation.

Traditional credit scoring can be enhanced using the objectivity of non-bias algorithms. Using machine learning with customer data can bring more accuracy to credit decisions on applicants without extensive credit history.

Risk assessment and management can be further automated analysing huge data sets in minutes. AI can help banks review and report risk without human error for both operational and financial processes.

Customers want both safety, privacy and personalised financial services. Machine learning models can detect and predict which tools and services a customer might need at any given time. The expectation of AI is to provide a more personalised approach helping customers to keep track of their finances.


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