Mastercard and BOK Financial Corporation announce expanded payments agreement

Instead, WTW used a combination of RPA and a cloud-based NLP service to scan files and remove personal data. The bank also used the intelligent automation platform to expedite its document custody procedures. Consider, for example, the laborious paperwork that is typically required to refinance homes. In an attempt to combat this, more and more banks are using AI to improve both speed and security. Take data science company Feedzai, which uses machine learning to help banks manage risk by monitoring transactions and raising red flags when necessary. It has partnered with Citibank, introducing AI technology that watches for suspicious payment behavioral shifts among clients before payments are processed.

We cannot guarantee the accuracy or applicability of any information provided with respect to your individual or personal circumstances. Please seek Professional advice from a qualified professional before making any financial decisions. We link to various third-party websites, affiliate sales networks, and to our advertising partners websites. When you view or click on certain links available on our articles, intelligent automation in banking our partners may compensate us for displaying the content to you or make a purchase or fill a form. To make things simpler for you to identity or distinguish advertised or sponsored articles or links, you may consider all articles or links hosted on our site as a commercial article placement. We will not be responsible for any loss you may suffer as a result of any omission or inaccuracy on the website.

For Better Decision Making

The financial services sector is an early adopter of intelligent automation and is encountering its governance challenges sooner than most. One of the ways in which the banking sector is meeting this ask is by adopting new technologies, especially those that enable intelligent automation (IA). According to a 2019 report, nearly 85% of banks have already adopted intelligent automation to expedite several core functions.

First, it is crucial to identify the appropriate use cases such as repeatable and structured processes then prioritizing these based on alignment with business objectives. Data retrieval from bills, certificates, and invoices can be automated as well as data entry into payment processing systems for importers so that payment operations are streamlined and manual processes reduced. There are many manual processes involved with the reconciliation of invoices and purchase orders. Intelligent automation can be used to identify various invoice structures to retrieve the necessary data for triggering the next steps in the process and/or enter the data into the bank’s accounting systems. Some institutions have had success in using machine intelligence to understand and optimise their business processes, says Grant Thornton’s Murphy. Process mining and intelligence can help organisations identify opportunities for automation and, in some cases, run A-B tests to see which process design works most effectively, he says.

What obstacles prevent banks from deploying AI capabilities at scale?

Executives and managers are already showing a strong interest in automating routine tasks, with a recent study discovering 83 percent of business leaders identified bank statement processing as a high priority for workflow automation. As financial leaders carry through on these plans, automation will enable human workers to focus on more meaningful work, engaging with customers, contributing to performance targets and building strategies for future success. There are many possibilities for automation in the healthcare industry outside of AI. Robotic process automation (RPA) technology can serve healthcare companies with various use cases involving data transfer and clinical documentation.

To innovate fast, your business needs a different kind of software engineering that is transparent, connected, fast and intelligent. EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. A global automation Center of Enablement (CoE) will help prioritize time-consuming processes and continuously identify areas of improvement.

Regulatory compliance

As automation in banking and financial services programs scale and grow, issues of governance and control become crucial. Center of Excellence initiatives (CoEs) seek control over the entire automation program, IT seeks governance over technologies being acquired, and both of those teams want the business side to capture value, but with the proper oversight (theirs). As we showed people at the conference, centralized automation solutions like WorkFusion’s answer these concerns and simplify shared ownership. The emerging set of new technologies that combine fundamental robotic process automation and artificial intelligence is Intelligent Process Automation (IPA).

The insights and quality services we deliver help build trust and confidence in the capital markets and in economies the world over. We develop outstanding leaders who team to deliver on our promises to all of our stakeholders. In so doing, we play a critical role in building a better working world for our people, for our clients and for our communities. The EY and Microsoft Alliance helps to connect businesses with EY services and solutions, reducing risk and accelerating business outcomes. Extend the Microsoft Power Platform across legacy applications and tools to make legacy processes intelligent, boost business productivity, improve organizational KPIs and increase operational resiliency. Capital One is another example of a bank embracing the use of AI to better serve its customers.

The bank’s mobile platform uses a machine-learning-based chatbot to assist customers with questions, transfers and payments as well as providing payment summaries. The chatbot is both text and voice-enabled, meaning users can simply speak or text with the assistant to take care of their banking needs. Blanc Labs helps banks, credit unions, and Fintechs automate their processes. Banks are already using generative AI for financial reporting analysis & insight generation. According to Deloitte, some emerging banking areas where generative AI will play a key role include fraud simulation & detection and tax and compliance audit & scenario testing. The current most noteworthy use of blockchain technology is cryptocurrency and Bitcoin.

A report entitled ‘Good Bots and Bad Actors‘ by IT consultancy Accenture identifies a number of security risks emerging from intelligent automation. Many of these relate to AI security threats, such as tampering with machine learning models or their training data to influence outcomes. Intelligent automation is a broad term, representing a range of possibilities for integrating AI and machine learning into process automation. This stretches as far as AI-powered decision making, but so far most use cases exploit AI’s potential to process unstructured data, such as text and images, to automate steps in a process that would otherwise require human perception. Financial institutions have adopted a range of use cases for intelligent automation, from simple integrations of cognitive services into RPA systems to, in a few cases, AI-powered decision making.

First, banks will need to move beyond highly standardized products to create integrated propositions that target “jobs to be done.”8Clayton M. Christensen, Taddy Hall, Karen Dillon and David S. Duncan, “Know your customers ‘jobs to be done,” Harvard Business Review, September 2016, hbr.org. Further, banks should strive to integrate relevant non-banking products and services that, together with the core banking product, comprehensively address the customer end need. An illustration of the “jobs-to-be-done” approach can be seen in the way fintech Tally helps customers grapple with the challenge of managing multiple credit cards. Arguably the most sophisticated applications of intelligent automation seek to replace human decision making with AI.

• Effective balance sheet merging involves decisions on retaining, restructuring or selling parts of the loan portfolio.
• Some banks are pushing ahead in the design of omnichannel journeys, but most will need to catch up.
• Here are several ways automation can help banks during M&As and best practices for using it.
• The company offers an automation hub for managing the automation opportunities pipeline.

Banks can use AI to transform the customer experience by enabling frictionless, 24/7 customer service interactions — but AI in banking applications isn't just limited to retail banking services. The back and middle offices of investmentbanking and all other financial services for that matter could also benefit from AI. McKinsey sees a second wave of automation and AI emerging in the next few years, in which machines will do up to 10 to 25 percent of work across bank functions, increasing capacity and freeing employees to focus on higher-value tasks and projects. To capture this opportunity, banks must take a strategic, rather than tactical, approach. In some cases, they will need to design new processes that are optimized for automated/AI work, rather than for people, and couple specialized domain expertise from vendors with in-house capabilities to automate and bolt in a new way of working.