Banking master class: part two

How AI is revolutionizing today’s banking industry

AI-powered technology is still gaining traction in the financial services sector, but it already has far-reaching impact. Banks and credit unions are leveraging AI technology in a variety of ways, including: 

• Cybersecurity
• Conversational assistants and chat bots
• Data & analytics
• Compliance management
• Fraud detection
• AI-powered advising
• Document automation
• Tracking trends 

According to David Rose of Amazon Web Services (AWS) AI-driven opportunities fall into two categories. “AI can improve foundational activities that every bank is already doing, like credit risk management, fraud detection, and even marketing and personalization,” he explains. “But developments like generative AI (GenAI) are also enabling financial institutions to carve out entirely new products, services, and business models.” 

In this early stage of AI adoption, Suman Chakraborty of Cognizant says that most financial organizations are experimenting with well-defined AI use cases that can drive specific outcomes with minimal risk. “Personalizing customer journeys is a good example of this. A user logs into the bank app, and it can make product recommendations tailored to that individual,” he says. “We’re also seeing some banks roll out virtual assistants that can respond to customer requests and improve the overall experience. And on the back-office side, developers are using GenAI tools to increase productivity and accelerate software development.”

It's no surprise that AI adoption is growing in the banking industry. McKinsey estimates that AI technologies could potentially deliver up to $1 trillion in additional value per year. And Business Insider reports that the aggregate potential cost savings for banks from AI was estimated at $447 billion in 2023. 

Risks and challenges of AI in banking

Financial services experts are predicting swift and expansive adoption of AI in the banking sector—but all opportunity comes with risk. Some of the primary challenges facing banks as they implement AI solutions include:

• High cost of implementation
• Data privacy and fraud concerns
• Data quality and accuracy
• Deep expertise 

To succeed with large-scale adoption of AI technology, Suman believes banks much align two critically important aspects: 

1. Security and data privacy. Guardrails must be established around how data can be accessed, how it will be used, and how it’s stored. Regulations related to GenAI are still being developed, but the foundational principles of security, transparency, and accountability must be established now.  
2. The human element. Full adoption of microprocessors took about 20 years, but AI adoption is happening much quicker. It’s important to help users develop the skills they’ll need to work with AI confidently. 

Adopting AI in any banking organization will require executive sponsorship. Getting executive support for AI adoption in any given organization requires applying AI technology to real business problems, as Conga’s Anthony Bear tells us. “Most institutions don’t think AI will incrementally grow top line revenue, but it can absolutely address bottom line costs,” he says. “Within a portfolio of thousands of contracts, AI can quickly determine where things like risk exposure, noncompliance, and missed opportunities exist.” 

The bottom line is, responsible use of AI means controlling for all the possible risks and negative outcomes—like managing what data can and can’t be used in training models, maintaining data traceability, and mitigating unintended biases in AI outcomes. David explains, “As AI continues to get bigger, more and more companies will invest in managing toward responsible AI.” 

Mitigate risk by integrating document automation alongside AI

It’s undeniable that implementing AI-powered technology brings many challenges and risks. Webinar attendees reported in a real-time poll that regulatory compliance, cybersecurity, and integration with legacy systems are some of their biggest concerns.  

One smart way to address the risk of using AI throughout your business workflows is by pairing document automation with AI technology. Combining document automation and AI can streamline countless banking use cases, like creating contracts, customizing account proposals, expediting onboarding processes and communications, managing statements, delivering investor documentation, and more.  

The natural pairing of document automation and AI provides three fundamental benefits, which combine to deliver a Revenue Advantage:

• Enhanced accuracy: A document automation solution streamlines both paper and digital documents to improve data validity and reduce human errors.
• Automated workflows: Document automation increases efficiency by freeing up human resources for high value tasks.
• Intelligent analysis: With document automation, you have the insights to make data-driven decisions, personalize the customer experience, and make research-based recommendations. 

Integrating document automation into your AI initiatives lets you receive data from anywhere, generate any type of document, and deliver your documents everywhere. Seamless document generation and eSignature capabilities can be embedded anywhere to elevate your brand.  

Calculating the business impact of automated document workflows

The success or failure of any technology implementation lies in its business impact—and AI technology is no different. Determining the true ROI of applying AI and document automation to your business workflows involves five key factors:

• The number of financial documents your organization creates each year: This includes a variety of financial documents such as loan agreements, customer onboarding materials, statements, and more.
• The time it takes to generate these documents: Depending on how your organization creates these documents, this is a rough estimate of how long document generation currently takes.
• The number of data sources used: Your organization may have multiple systems of record like customer relationship management (CRM), enterprise resource management (ERP), etc. Each one is used to store data and populate financial documents.
• The number of signatures captured each year: Signatures are required on countless banking documents and must be captured from all relevant parties.
• The number of staff members involved with creating and sending documents: Your organization needs a variety of staffing roles to support your documentation needs. 

Watch the webinar recording to see an example illustrating how these five factors are used to calculate the business impact of document automation in your banking workflows. 

Stay ahead of banking innovation

Looking for more resources to help transform your banking operations? We’ve got you covered:

Past webinar recap: Banking master class: part one

In our first session of Conga’s Banking Master Class, our industry leaders uncovered the 6 dimensions of the Revenue Advantage, highlighted common roadblocks that make up what Conga defines as The Revenue Friction Zone, and discussed the business impacts of automating critical financial documents like loan agreements and account openings. We highlighted three key features of document automation that drive immediate ROI and showcased a live demo by Conga’s Product Marketing Manager, Brad Brochocki, creating, sending, and eSigning a document—all in under 60 seconds! In case you missed it, get the full recap or watch the recording.