Artificial Intelligence: Regulatory Pushes and Consumer Pulls

In today’s on-demand world, the new generation of consumer expects services to be available 24/7, to be intuitive, instantaneous and catered to them. For banks, this means providing services that cater to an individual’s spending patterns, device preferences and current life situation. It’s a tall order for businesses to provide manually, but all the data on customers is there to provide those kinds of services. Banks just need to find a way to access it.

The Demand for Artificial Intelligence

Successfully accessing, and then analyzing, data will lead to more streamlined services for customers, and quicker time to insights for businesses means quicker service delivery to customers. Banks can also capitalize on their insights around customer spending patterns to provide tailored recommendations on financial well-being to clients – boosting their customer experience.

At the same time, legislation changes are adding additional complexity, including regulations that have had a global impact, like the General Data Protection Regulation (GDPR). GDPR requires “single points of truth,” on customer personal data. Implementation for many organizations has proved to be an exceptionally onerous tasks, if not outright impossible, to complete manually; and banks need some sort of system that can intelligently pull together all the insights into one, clearly representative, report of compliance.

If Artificial Intelligence (AI) is a necessity for consumer personalization and legal compliance, why aren’t banks everywhere simply investing and deploying it? It has emerged that, while there is great appetite for more analytics, more AI and more insight in general, all of these require banks to overcome significant legacy infrastructure hurdles. You can’t plug Al into an old system like a USB drive and expect it to churn out the results you want; instead, you need to get your data into a more searchable, agile framework before you can add AI over the top.

In addition to compliance demands, by 2030, traditional financial institutions can shave 22% in costs, says Autonomous in an 84-page report on AI in the financial industry. Here’s how they break down those cost savings:

• Front Office – $490 billion in savings. Almost half of this ($199 billion) will come from reductions in the scale of retail branch networks, security, tellers, cashiers and other distribution staff.
• Middle Office – $350 billion in savings. Just simply applying AI to compliance, KYC/AML, authentication and other forms of data processing will save banks and credit unions a staggering $217 billion.
• Back Office – $200 billion in savings. $31 billion of this will be attributed to underwriting and collections systems.

How about my systems and applications and what do I need to think about?

To achieve a state of “single points of truth” you need to have the right technology and infrastructure in place, including an agile and scalable integration platform that will help connect all “data sources” in an efficient and reliable way. Modernization of legacy integration platforms such as Managed File Transfer (MFT) and Business-To-Business (B2B/EDI) is a time consuming and costly exercise. It involves reaching out to potentially thousands of customer and business  partners, updating business contact lists, coordinating technical and business teams, performing acceptance testing and migrating the partners to a new platform, one by one. This causes disruptions to business and impacts services provided to customers and business partners, resulting in dissatisfaction.

SEEBURGER’s Migration Suite was developed to solve business pains surrounding legacy modernization,  enable a controlled migration within the corporate architecture with the end goal of having an agile business integration architecture in place to enable innovative business services. Migration Suite eliminates the need to contact customers, corporates and business partners, making the migration process seamless, and customer service left uninterrupted. SEEBURGER’s best practice for legacy migration includes a methodology, tools and solutions which simplify importing master data from legacy MFT/B2B applications, thereby reducing cost of migration and improving customer satisfaction.