AI/ML for Small and Midsize Banks
A guide to getting started.
- Banks are aggressively adopting AI/ML, but your bank hasn’t started yet. AI/ML is all the industry is talking, but you aren't sure where to start.
- There is a lot of concern about the use of AI/ML, but other banks seem to be moving forward. What are the challenges and how are others overcoming them?
- Senior leadership wants a plan for AI/ML, but even they are not sure exactly what it is or how to use it. They are looking to IT for leadership and insight.
Our Advice
Critical Insight
- You aren't sure which AI/ML use cases are right for your organization. Selecting the right early use case is critical. Do you choose internal or client-facing use cases first?
- You lack clarity about regulatory and privacy issues. Banking is subjected to high regulatory and privacy requirements, and you are unsure about the impact AI/ML will have in these areas.
- You aren't sure how to implement AI/ML. Do you choose an AI/ML provider first? What about data? How does the new AI/ML fit into your existing infrastructure?
Impact and Result
- Apply the six core benefits that AI/ML can deliver to your customer experience to help you determine where you should deploy it within your bank.
- Understand the six capabilities that AI/ML can bring to your bank's internal operations to maximize the return on your AI/ML investment.
- Mature your AI/ML approach to combine both customer-facing and internal benefits to achieve exponential outcomes and returns.
- Use our AI/ML scorecard tool to evaluate the suitability of your use cases.
AI/ML for Small and Midsize Banks
A guide to getting started.
Analyst Perspective
Artificial intelligence is a critical technology for small and midsize banks
The use of artificial intelligence and machine learning (AI/ML) in retail banking is rapidly accelerating. Early-adopter banks are establishing themselves as industry leaders and are redefining the experience and expectations for all banking customers.
Customers are responding positively to the ease of use, accessibility, and personalization delivered by an AI/ML-powered experience. It is vital that banks modernize their customer experience (CX) using these new techniques or risk losing their customers to banks that do.
Senior leadership inside banks are acknowledging the critical importance that AI/ML plays within their organizations. Many are asking their technology leadership for a specific AI/ML plan.
Larger banks have been using AI/ML for over a decade. Small and midsized banks are still in the early days of adopting these technologies, and regulatory compliance and risk management challenges have limited their use in banks. As these challenges are overcome, their growing adoption is inevitable.
David Tomljenovic MBA LL.M CIM
Head Of Financial Services Industry Research
Info-Tech Research Group
Executive Summary
Your Challenge
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Common Obstacles
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Info-Tech’s Approach
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Info-Tech Insight
Your bank’s investment into customer-facing AI/ML capabilities will positively impact your internal operations. Using the six-part external and internal framework will provide a holistic view of AI/ML within your bank. As your AI/ML maturity grows and you can connect external and internal AI/ML benefits, your bank will achieve an exponential ROI.
Banks are rapidly adopting AI/ML
Customer expectations are evolving quickly to include these new capabilities.
AI is important to financial institutions
77% of financial services organizations expect AI to possess high or very high business importance within two years.1
Financial institutions are implementing AI
60% of banks said they had implemented at least one AI capability.2
AI will power future interactions
95% of interaction between businesses and customers will be AI-powered by 2025.3
Info-Tech Insight
Banks and financial service companies will rapidly adopt new AI capabilities to differentiate themselves and improve operational efficiencies. Those left behind will struggle to catch up.
1 Globant Reports, 2023
2 McKinsey, 2020
3 Insider Intelligence, 2023
AI/ML are transforming how banks serve clients
The adoption of AI/ML will change the service landscape
AI is expected to drive profitability
75% of companies believe that AI, automation, and chatbots will drive profitability.1
AI will free up support agents
75% of survey respondents report that AI is instrumental in freeing up support agents, allowing them to spend more quality time with customers. 2
Generative AI (Gen AI) is seen as a top emerging technology
35% of financial services organizations identify Gen AI as a top emerging technology over the next three to five years.1
Info-Tech Insight
AI/ML are reshaping the CX in banking, enabling customers to get their own answers how and when they want. Banks are redeploying resources to better service more complex customer needs.
1 “LLMs,” Master of Code, 2023
2 “Conversational AI,” Capacity, 2023
AI/ML provide enhanced benefits for banking
Customer-facing benefits
AI has already had a dramatic impact on CX in banking, and the use cases are rapidly developing.
Six components are being affected by AI:
- Human-like engagement
- Multilanguage support
- Deploying complex logic
- 24/7 availability
- Omnichannel capability
- Increased accessibility
Internal/business benefits
Senior leaders may be more interested in AI/ML’s internal impact beyond external benefits such as higher revenues and lower costs.
Six internal AI/ML benefits are derived from:
- Fraud detection
- Enhanced compliance
- Intelligent automation
- Advanced analytics
- CX
- New business models
Customer and internal benefits build on each other
Exponential benefits can be achieved when customer-facing and business benefits are strategically planned and implemented.
Source: “Generative AI in Banking,” Master of Code, 2022
AI has significant CX potential
Customer-facing AI benefits for retail banking
- Provides intuitive and simplified customer engagement
- Ability to target and service multiple languages
- Ability to enable/enforce complex business rules
- Deliver consistent service regardless of the time or day
- Implementation can be delivered through all channels
- Enhanced customer accessibility
Source: “Generative AI in Banking,” Master of Code, 2023
Banks are accelerating internal AI/ML adoption
It’s driving higher productivity and revenues while reducing costs
AI is expected to increase productivity
Banks who adopt AI/ML expect to achieve a 74% productivity increase.
AI is increasing bank revenues
67% of banks that have adopted AI/ML have reported an increase in revenues.
AI is decreasing costs
79% have reported a decrease in costs due to AI/ML adoption.
Info-Tech Insight
AI/ML is driving net income after taxes (NIAT) growth through improved CX processes and more streamlined operations.
Source: “Unveiling the Risks,” Master of Code, 2023
Internal AI benefits for retail banking
There is broad internal applicability throughout banks
- Large data-handling abilities can identify new fraud patterns
- Advanced data-driven intelligence can help reduce false positives
- Reduction in manual/repetitive effort can save time/costs
- Multivariable, iterative models can drive deeper insight/value
- Transforms almost all elements of the CX
- Low-cost, high-volume, insight-driven CX can drive new models
Source: Software Group, 2023
Customer-facing and internal AI should work together
An integrated AI approach should deliver exponential benefits to banks
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