ARTIFICIAL INTELLIGENCE (AI): AUTOMATION FOR FINANCIAL SERVICES

Updated: Jul 23, 2021

It is no longer a question that Emerging technology, such as robotic process automation (RPA) and, cognitive computing will have great impact on our businesses in years to come and, will undoubtedly transform the workforce of the future across the financial sector. Today, RPA is at the forefront of human-computer technology and promises to provide those in the financial services industry with a virtual workforce that is rules -based and able to connect with a company’s systems similar to the way users do.


RPA is expected to be part of the hybrid workforce of the future. Robotics Process Automation (RPA), a characteristic of intelligent process automation are logic-driven robots that can execute pre-programmed rules on structured and unstructured data. Overtime, robots are able to learn from prior decisions and data patterns to make decisions by themselves at machine-speed and, to perform a great number of repetitive operational functions 24 hours a day, seven days a week. Recent reports have highlighted that RPA will result in more productive relationship between people and machines through deeper analytics and recommendation engines, strengthening client services and product needs.

Looking back; when the internet was created there was no way to predict some of the impact to Financial Services and other industries that we take for granted today. As an example, over the past decade we have seen quality improvements with speech recognition which has led to the creation of digital assistants Siri and Alexa. “speech is expected to replace touch-typing for input…” recently said Ruhi Sarikaya, director of Amazon Alexa. For Financial institutions the key is to embrace the next wave of robotics technology to drive business outcomes and, to use these tools to automate a wide range of activity.

With robotics, automation of recurring functions is possible at the front office and, back office freeing people to focus and work on high value tasks that are more complex. These functions are achieved through software bots that interface in the same ways humans do with the same sets of applications. Applying AI to front-office client interactions, such as client on-boarding - documentation requirements verification, compliance, legal and credit checks, portfolio allocation and rebalancing, operational activation of account in trading and settlement systems will significantly increase processing speed.


Financial services institutions aiming to utilize RPA need to think differently. One of the great advantages of RPA is the speed and relatively low cost of implementation. However, Institutions that are considering implementing RPA must first select the process candidates for automation and ensure that the operating model for RPA can be supported. Having an effective governance in place that covers as example the standards, organizational buy-in from individuals and internal groups that will be affected by automation at the onset is critical to maximize value, placing a focus on developing the metrics, execution strategies and, change management are necessary. Financial Institutions that are able to adjust their organization and culture to take in intelligent automation as collaborators, rather than “people replacements”, could achieve significant success.


 Recent marketplace research have identified areas for consideration for automation in Financial Services. The following are some initial examples. Each organization will have unique additional processes.

Banking

Capital Markets

  • New account entry across systems – moving data and doing multiple entries

  • Fraud detection

  • Account reconciliation – duplicating and moving data

  • Entitlement engine

  • Report generation across systems and generated

  • Reconciliation - user defined rules to generate alerts on chargeback, retrieval

  • eForm extraction

  • Automated scheduling of reconciliation activity

  • Accrual support – making and updating entries

  • Multi-level reconciliation across international & domestic networks

  • Mortgage approval. Refinancing processes for initial entry and updating records

  • Receive/track dividend, interest, and amortized principal payment information

  • Notification of delinquent loans – emails and letters to clients

  • KYC/AML authentication: collection and analysis of basic identity information

  • Credit card order processing

  • Audit support and validation

  • Fraud detection – tracking of activity

  • Account cleansing – inactive account purging




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