Automation in Banking and Financial Services

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A key enabler of digital transformation, RPA in banking and financial services has been shown to deliver faster process execution and reduced operational costs, while making it easier for organizations to safeguard sensitive data and stay in line with ever-evolving regulatory and compliance guidelines.

According to a 2020 McKinsey Report, approximately 60% of financial services firms have already embedded RPA and AI into their operations.

RPA bots can carry out the repetitive, high-volume, cross-system processes that banking and financial institutions rely on, and are able to do so with greater speed, capacity, and accuracy than human workers. For organizations, this means improved productivity, profitability, and operational efficiency. For employees, it means improved experience, greater team alignment, and more time to focus on critical high-value activities.

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Automating for Operational Efficiency

According to UiPath, as much as 80% of a banking or financial organization’s rule-based activities can be automated with RPA. Through implementing RPA and AI solutions, these backend processes can benefit from improved accuracy, timeliness, reliability, and a high degree of flexibility. This flexibility allows organizations to increase operations volume to continue improving ROI and profitability as operations scale.

RPA and Legacy Systems in Banking & Finance

RPA can be used to link disparate legacy systems in order to facilitate communication between them – whether it be marketing automation software, CRM tools, ERP systems, accounting systems, or any other systems or databases. This streamlines cross-system data collation so organizations can conduct operations faster without entirely overhauling their existing systems.

Ensure Compliance with RPA

Financial institutions are tasked with handling heightened levels of institutional activities associated with compliance, including control testing, loan requests, and customer onboarding – all of which can result in a major loss of resources when poorly managed. Banks and financial firms can leverage RPA bots to access databases, watchlists, and other sources to locate and organize critical data; and machine learning-powered analytics to discover relationships and hidden risks.

Bots Improving the Customer Experience

Automation can help deliver better service to customers and clients by accelerating the deployment of customer self-service options, allowing back-end application access and secure access for users to create and maintain their personal login credentials. Desktop bots, or Robotic Desktop Automation (RDA), can also be used to gather customer data during calls, enabling your reps to better focus on customer and eliminating lengthy wait times.

Popular Use Cases in Banking and Financial Services

Mortgage Lending

The cyclical and highly regulated nature of the mortgage industry directly affects the level of consistency in mortgage technology investments. The mortgage origination process also differs based on the size of the lenders and the current state of the secondary market’s regulatory environment. Due to such challenges, it isn’t always feasible for mortgage firms to make technology investments where implementations span multiple years before business is able to reap the rewards of such investments. This is where RPA and AI can solve for some of the most common challenges.

Use Cases:

  • RPA Bots enable 3rd party data push/pull (employment/asset verifications, credit reports, tax returns, appraisals, OFAC)
  • Using RPA instead of traditional time-consuming SDK/API for systems integration where real-time, high-speed integrations may not be required. For example, capturing loan application data using various channels and running automated batch processes in the back-end to push/pull data into various systems
  • Bots assisting call center reps with case management by collating data from various systems without requiring manual intervention
  • Post-close loan QC reviews

Credit Card Operations

Use Cases:

  • Capturing credit card applications from multiple channels and processing them into the bank’s core systems of records
  • Streamlining lost or stolen card case management – Bots can assist agents with gathering data from various systems of records to get the case processed quickly

Core Banking Operations

Use Cases:

  • Bank account maintenance, customer data updates, address changes, rate and status changes
  • Accounting reconciliations
  • Routine check validation procedures
  • Overdraft protection involving third-party system integration and the organization’s internal processes

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