By NXTsoft
Robotic process automation (RPA) has proven to reduce costs and employee workloads, and significantly lower the amount of time it takes to complete manual tasks for various industries. But in order for intelligent automation to work effectively with fintechs and financial institutions, application programming interfaces (APIs) need to connect them with enterprise systems.
The adoption of RPA — which comprises the usage of adaptable, reusable and non-intrusive software elements, or robots, which interact with and manage systems and applications — is growing rapidly.
According to a 2018 Capgemini study 56% of organizations had deployed automation in IT and over a third had implemented automation solutions in the middle office, which includes customer service, account management, and customer experience.
Leading analysts also forecast a sharp increase in the market size of RPA technology: Gartner, estimated RPA solutions to reach $2.4 billion by 2022; Research and Markets found the RPA market valued at $2.039 billion in 2020 and headed to a compound annual growth rate of 31.5% from 2021 to 2026; Forrester, projected the RPA market to surpass $2.9 billion this year; Fortune Business Insights estimated the global RPA market size to reach $6.81 billion by the end of 2026.
FIs Adopt RPA through API
From taking over repetitious data entry to answering simple customer service queries, RPA continues to evolve in reducing the amount of time financial workers spend on many monotonous, labor-intensive tasks. Some fintech companies are empowering credit unions, and banks, with intelligent solutions for improving the customer experience, fighting financial fraud, and increasing operational efficiency.
Some financial institutions leverage RPA to increase accuracy, boost productivity and grow the bottom line. More than a third of financial institutions surveyed by Capgemini in 2018 attributed a 2-5% growth directly to an intelligent automation strategy.
Financial institutions use RPA to perform repetitive tasks like data entry and to automate customer service and back-office workflows. RPA enables financial institution staff to focus on more complex tasks, while bots takeover the routine activities. Artificial intelligence (AI) and machine learning (ML) can also supplement RPA to handle sophisticated processes with higher accuracy and efficiency.
RPA can also help financial institutions improve their customer experiences by quickly analyzing and providing answers to many common customer challenges, problems and queries. The financial institution staff can then focus on handling more complicated customer issues. Additionally, robots provide 24/7 availability to handle customer issues, which significantly improves customer satisfaction.
RPA Use Cases in Financial Services and Fintechs
Many financial institutions have started to rethink their operational models to leverage intelligent automation and RPA. While in many cases complete automation often is the ultimate goal, targeted automations using RPA can bring substantial help rapidly if applied toward specific use cases in banking operations.
Some banking RPA use cases include:
- Loan application processing and validation including extracting pertinent information from the customer documents.
- Customer service comprising many tasks such as onboarding, account closures, fraud and loan requests.
- Accounts payable for digitizing vendors invoices and validating information;
- Credit card processing for validating applications, application processing and handling online card-on-file replacement and management issues.
- Fraud detection such as allowing financial institutions to methodically check each transaction and identify potential fraud patterns.
- General ledger to help financial institutions collect, update, and validate large amounts of information from different systems efficiently and accurately.
- Contact center optimization such as utilizing virtual personal assistant banking systems, which include a hosted, dynamic interactive voice response system for personalized customer interactions.
- Conversational voice banking solutions in self-service areas that work with popular virtual personal assistants, such as Amazon Alexa and Google Home.
- Automated report generation including enhancing data extraction from internal and external systems, standardizing data aggregation, developing templates for review and reconciliation.
Opening the Fintech Door to Robot Banking
Robotic process automation provides financial institutions with the basics needed to automate system processes as they seek to implement more intelligent automation — through artificial intelligence, and its subset machine learning — as they seek to improve customer satisfaction, reduce inefficiencies and fight fraud.
Implementing RPA in banking requires limited infrastructure. Financial institutions and fintech vendors can leverage existing IT infrastructure and bridge the gap between enterprise systems, and intelligent automated solutions by taking advantage of APIs, which allows them to connect.
In order to capitalize on the shift toward more open banking, many credit unions and banks seek a fintech partnership to improve their mobile banking and payment channels, personal digital assistants, saving and investment tools, fraud mitigation, payment processing, and AI and machine learning augmented capabilities. They also want upgrades to their digital banking platforms to provide real-time and same-day banking services, big data access through open banking to provide customers with personal and actionable insights; and robotic process automation to power existing processes.
Partnerships between fintechs and financial institution are mutually beneficial. For credit unions and banks, an open-banking solution tapping into new technology can extend their market reach, connectivity to customers, provide new revenue opportunities and better utilize current resources. Meanwhile, partnering with financial institutions by gaining access through open banking APIs allows fintechs to strengthen their RPA offerings. An API marketplace — which includes an API manager, gateway, security, publisher and developer — helps bring the financial institutions and fintechs together.
NXTsoft’s OmniConnect product line that provides API connectivity has been facilitating a form of RPA for financial institutions and fintechs for the past 25 years. Anytime a fintech company wants to connect its application to a financial institution’s core system they would have to have software engineers on staff at a cost of $100k + annually per developer to write integrations and then continue to rely on those personnel as the core processor authors 4-6 enhancements and upgrades per year. Similarly, the financial institution would have to rely on personnel on their end to keep the connectivity updated. Via RPA NXTsoft’s OmniConnect removes that entire burden from fintech and financial institution employees and facilitates it through API connectivity significantly reducing costs and personnel time.