Digital transformation trends that are shaping banking
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.

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.For the latest fintech news and events sent straight to you inbox sign up to the FINTECH Circle newsletter