Banking is undergoing a profound shift…
Surging Demand for Digital Banking
Consumers have come to expect mobile and online banking services available 24/7. A Salesforce survey found that over 50% of customers prioritize convenience as the most important factor when choosing a bank. Chatbots deliver digital banking on demand.
According to Juniper Research, over 2 billion banking customer interactions will be handled by chatbots worldwide by 2025 – a 400% growth in just 5 years. North America and Europe continue to lead adoption with over 50% of tier 1 banks having already deployed conversational assistants.
Several interlinked factors are fueling these investments…
What Can Banking Chatbots Do?
AI banking assistants handle an expanding range of customer needs conveniently. The latest solutions even offer human-like conversations using advanced neural networks and NLP.
Some key functions include…
Personal Finance Tips
Based on a customer‘s transaction history and profile, banking chatbots provide timely, personalized finance tips on budgeting, savings goals, paying bills, avoiding fees and more. Advanced analytics furthers relevance by understanding changes in customer behavior over time.
For example, Spain‘s Santander bank provides digital cash management advice through its popular banking bot. Over 50% of customers find the finance guidance highly useful.
New Account Opening
Through conversational workflows, chatbots guide prospects through new account applications, collecting necessary customer data. Back-end integrations with banking systems then facilitate near-instant account openings fully digitally.
Authentication procedures via OTPs also verify identities. Such digitization of previously manual processes expands banking access while reducing branch traffic and costs.
According to Business Insider Intelligence, over 25% of banking chatbot conversations in North America will be for new account openings by 2025.
Of course, today‘s banking chatbots have limitations which banks must acknowledge…
Banking Chatbot Success Stories
Industry trailblazers highlight the customer experience and efficiency gains possible by deploying conversational AI assistants.
For example, Singapore’s DBS Bank introduced a finance tips messenger chatbot which has handled over 500,000 conversations to date – a 50% increase in just the last year. Session duration metrics also indicate high levels of customer engagement.
The volume of queries handled has reduced call center traffic by over 30%. Combined with rising digital user satisfaction scores, DBS has seen over 20% ROI on its chatbot investment to date.
As part of a larger digital transformation strategy at BBVA Spain, chatbot Lola has answered over 100 million customer inquiries with 92% accuracy. The launch has lifted key CX metrics for BBVA as digital users continue to grow 30% year-over-year.
The returns chatbots offer banks can be significant, but realizing success takes planning and discipline.
Here are 5 essential practices for banking bot launches…
Latest Advancements in Banking Chatbot Capabilities
While today‘s banking chatbots optimize a wide array of customer interactions, new use cases leveraging cutting-edge AI capabilities are emerging:
Video-Based Engagements
Chatbots equipped with computer vision can parse visual customer data like documents, pay slips or product labels to auto-fill applications or provide tailored assistance. Video chat also enriches conversations with facial expressions and tonal analysis.
For example, HSBC‘s chatbot integrates with video KYC verification for seamless remote account opening.
Voice Biometrics for Security
Banks like Australia‘s ANZ allow customers to authenticate high-value transactions on chatbot channels using voice recognition, which is more secure than passwords or PINs alone.
Augmented Analytics
Backend connectivity with data platforms allows next-gen chatbots to provide personalized, proactive recommendations leveraging analysis of historical usage patterns and transactions.
Machine learning models can continuously improve targeting as more customer data flows through chatbot interactions.
As conversational AI adoption accelerates across banking channels in coming years, analytics-driven hyper-personalization will be the key to differentiation.
Now let‘s assess some leading enterprise-grade platforms for delivering advanced banking chatbots.
Evaluating The Top Banking Chatbot Solutions
While many vendors now provide conversational AI software, the sophistication required for secure, reliable and extensible banking implementations narrows the field. Here is a comparative analysis:
Mature solutions like Creative Virtual’s V-PersonTM lead across critical functionality areas like hybrid AI capabilities for accurate natural language interactions, bank-grade security protocols, scalability to hundreds of banking endpoints, and out-of-the-box integrations with mainstream systems.
Creative Virtual also stands out for its pre-built expertise in financial services use cases, having powered assistants for leading banks worldwide, including Standard Chartered and Fidelity Investments. Industry specialization accelerates deployments.
Both Creative Virtual and Nexa offer tailored banking chatbot packages beyond their base platforms. This helps maximize outcomes for defined digital transformation objectives around customer experience, cost optimization and revenue goals.
For large banks, choosing such a strategic partner is advised over opting for do-it-yourself tools.
Let‘s now walk through what‘s entailed in executing banking chatbot rollouts effectively.
Implementing Chatbots Successfully – A 6 Step Framework
While the business case for AI-assisted banking is compelling, thoughtfully planning implementations is key to managing risks and driving optimal ROI across digital touchpoints.
Here is a phased approach:
1. Define Scope and KPIs
Rather than automating all interactions in one go, banks should start with a narrow bot focus area like new account opening for credit cards. Target success metrics must also be established upfront aligning to business goals on customer experience, channel cost savings or revenue.
2. Develop and Integrate MVP
Working with the platform vendor, an initial chatbot MVP can be built targeting core functionalities like conversational flows for data gathering.
Rigorous integration testing follows before going live to a test group.
3. Test and Refine Iteratively
Monitoring chatbot performance daily across metrics like contained queries, escalations and user feedback is vital for ongoing capability enhancement. Any issues found are quickly addressed.
4. Expand and Scale Usage
With model stability and reliability achieved, the chatbot is gradually rolled out to wider customer segments through additional digital touchpoints.
5. Promote Adoption Internally
Getting contact center and branch staff aligned on chatbot objectives is crucial for reinforcing user awareness. Enable teams via training on scenario-based customer handovers.
6. Enhance Personalization
Leveraging aggregated chatbot-customer data and intrinsics, next-best-action logic and machine learning continuously refine interactions to boost value.
Budgeting approximately $200,000 for an enterprise-wide implementation covering critical phases of planning, builder licensing, backend integration, testing and launch-year operations is recommended.
Allocate another $100,000 annually for sustained platform access, change requests, upgrades and campaign administrative expenses.
Staffing needs typically involve:
- Project manager with chatbot implementation expertise
- Conversational designer to frame dialog flows
- 2 developers for integration and tech support
- Business analyst to drive analytics and optimization
Factoring in both budget and cross-functional resourcing is prudent.
In closing, AI-powered chatbots represent a pivotal opportunity for retail banks to meet intensifying digital customer service mandates cost-efficiently even as human-like conversational capabilities continue maturing rapidly.
Conversational AI will undoubtedly remain an enterprise priority for bank CXOs through the decade. Getting chatbot adoption right early on is key to staying ahead of rising consumer expectations in the age of digitally-native financial experiences.
