As a highly customer-oriented industry, banking, financial services, and insurance (BFSI) has always been a prime candidate for digital transformation. COVID-19 catalyzed the adoption of digital technologies in this otherwise conservative sector, says Deloitte in their 2021 banking and capital markets outlook. Moving away from in-person interactions created challenges, forward-thinking financial services firms viewed those challenges as opportunities to create better experiences through automation.
To fully realize the digital promise, BFSI firms can use a variety of levers to elevate process efficiency and customer engagement. These can include creating an optimal mix of digital and human interactions, using data intelligently to better shape experiences, and incorporating artificial intelligence (AI)-based solutions to automate processes and free up capacity to focus on strategic activities.
Intelligent automation aided by AI and cognitive technologies can help to accelerate processing time and reduce the number of errors in complex processes end-to-end, removing the sector’s reliance on legacy methods like spreadsheets to get jobs done. This is a massive opportunity! According to McKinsey, AI could deliver up to $1 trillion in additional value for the banking sector.
Where to start using intelligent automation?
Even with all the digital transformation it underwent, the BFSI industry is poised to take further advantage of the technologies that can expand its field of vision and open even more opportunities, including intelligent automation.
Though the first wave of automation improved some financial service providers’ basic functions by employing robotic process automation (RPA) for repetitive tasks, there are many organizations that are still in need of far more sophisticated and intelligent applications of automation for their evolving business processes. Firms that are already scaling their intelligent automation efforts are leading with improved experiences across the value chain while reducing their operating expenses and driving better margins through significant process evolution.
These automations have proved to perform iterative tasks at scale. They ingest data from third-party sources, populate digital platforms, trigger notifications and initiate actions without human intervention, so the firms can virtually operate 24/7 without overburdening employees.
Forward-thinking firms continue to streamline their automation-readiness. These organizations are seeing the benefits of intelligent automation unlocked across multiple operating areas through use cases that have a significant, positive ROI. For instance, we recently helped automate redemption request processing for a US-based financial services leader, transferring metadata between the front-end and back-end systems, eliminating staff involvement altogether. Our customer continues to see recurring expense reduction, saving thousands of person-hours of resource expenditure with this engagement.
Based on our experience and expertise working in this industry, we have shortlisted a few similar business use cases where intelligent automation has been creating fast and incisive impact.
1. Letting customers open accounts remotely
AI is an integral component of intelligent automation and sets it apart from stand-alone, traditional RPA. Using AI, you can leverage technologies like Optical Character Reading (OCR) and cutting-edge facial recognition, blended with an integrated intelligent automation platform, to help fully automate and accelerate the account opening process. Customers need only to initiate a video call, and the facial recognition solution evaluates features to verify identity. Post the verification, the intelligent automation solution can then take over to extract the necessary details from remotely shared data to populate the fields in your enterprise resource planning (ERP) or core system.
2. Saving effort, costs, and time in data migration
Any digital transformation activity, where you are modernizing applications that have existed for decades, involves complex data migration. Lenders, credit assessment firms, insurance companies, and similar service providers rely on data as a key asset. Traditional migration of data would involve at least six stakeholders (a business user, a data custodian, a systems specialist, a database specialist, a product specialist, and an extract, transform, and load specialist). An intelligent automation solution that reads the legacy source, applies transformation/reformatting procedures, and loads the data into the new schema can significantly cut down the human effort, operational costs and turnaround time involved in this process.
3. Making credit risk assessment more accurate and scalable
The analytics technology needed to accurately screen prospective borrowers and assign risk scores already exists. However, human employees still need to go through this data, which can be cumbersome and prone to errors, especially when it comes to processing small-to-micro retail loans. An intelligent automation solution can connect with the analytics engine on one end, and the underwriting system on the other, to automatically process risk assessments and loan applications below a certain threshold.
4. Detecting fraud and setting up timely alerts
By mapping and continuously monitoring real-time transactions against data from ERP, business intelligence, and third-party providers, your anti-money laundering (AML) and fraud detection teams can detect suspicious behavior and signs of misappropriation. An intelligent automation solution can not only help them by keeping a constant watch for these tell-tale signals (purchase order mismatch, split transactions, payments made at unusual hours) but also alert the necessary parties in real time. Leveraging this, you can set up an automated workflow for low-value transactions, where suspicious behavior can be approved or blocked automatically.
5. Processing and validating applications while maintaining data integrity
Manual application validation processes – whether for banks, insurance, or asset management firms – are painfully error-prone and tedious. When done using spreadsheets (which is still a staple for the BFSI industry), there are the added risks of data inconsistency, inability to track lineage across multiple systems, and duplication. An intelligent automation solution, on the other hand, can extract and store data involved in all these processes, so it can be easily accessed, tracked, and used. Leveraging technologies such as OCR, Intelligent Document Processing (IDP), Machine Learning (ML), and Natural Language Processing (NLP) in the solution, your business users can process complex applications from large commercial entities within no time, and customize the solution to suit emerging process changes as and when needed, without depending on the IT team.
But does that mean you have to disrupt your existing IT landscape to build an intelligent automation system afresh? The best part is, it can be integrated /added into / onto your IT infrastructure seamlessly adding more value to it, and enabling bidirectional data flow with ERP, content management systems, regulatory databases, and custodian data portals.
These five use cases are just the tip of the iceberg. The potential use cases for intelligent automation in financial services are vast, including business-critical processes such as KYC/Re-KYC, card activation, audit processes, customer engagement, and reconciliation in wealth management.
Discover more ways that intelligent automation can enable you to unlock these hidden opportunities in our eBook How Intelligent Automation is Propelling Banking & Financial Services: Top Ten Use Cases Reimagined. The eBook also explains how JIFFY.ai’s integrated platform-based approach can help realize exponential returns from your automation investment.
To learn more, visit https://jiffy.ai/solutions/banking-and-financial-services/
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