7 possible ways AI will change the CX game for financial services

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Customer experience (CX) is a key factor that influences customer loyalty, retention, and satisfaction in any industry. In the financial services sector, CX is especially important as customers expect fast, convenient, and personalized services that meet their needs and preferences. However, delivering high-quality CX can be challenging for financial institutions, as they have to deal with complex regulations, legacy systems, data silos, and security risks.

How AI defines CX in financial services now

This is where artificial intelligence (AI) can make a difference. AI is a broad term that encompasses various technologies that can perform tasks that normally require human intelligence, such as natural language processing, computer vision, machine learning and deep learning. AI already helps financial services providers improve their CX in various ways, such as:

Automate repetitive and mundane tasks, such as data entry, verification, compliance checks, and customer service inquiries. This can free up human resources for more complex and creative tasks, as well as reduce errors and costs.

Analyze large and diverse data sets, such as customer behavior, preferences, feedback, transactions, and market trends. This can provide insights into customer needs, wants, and expectations, as well as identify opportunities and risks.

Personalize products and services, such as recommendations, offers, pricing, and advice. This can increase customer engagement, loyalty, and satisfaction, as well as generate more revenue and profit.

Enhance security and fraud prevention, such as biometric authentication, anomaly detection, and risk scoring. This can protect customer data and assets, as well as comply with regulations and standards.

Areas for AI Improvement in Financial Services CX

However, AI is not a silver bullet that can solve all the CX challenges in financial services. There are still some areas that need improvement, such as:

Data quality and availability.

AI relies on large and diverse datasets to learn and improve its performance. However, many financial institutions lack the data infrastructure and governance to collect, store, access and share data across different systems and departments. Moreover, data privacy and security are paramount in financial services, as customers entrust their sensitive information to the providers. Therefore, financial institutions need to ensure that their data practices comply with the relevant regulations and ethical standards.

– Human-AI collaboration.

AI cannot replace human judgment and expertise in complex and nuanced situations. Therefore, financial institutions need to ensure that their AI systems are transparent, explainable, and accountable. They also need to train their employees on how to use AI effectively and responsibly, and how to communicate with customers who may have questions or concerns about AI.

– Customer trust and acceptance.

AI can offer many benefits to customers, but it can also raise some issues such as bias, discrimination, manipulation, and loss of control. Therefore, financial institutions need to build customer trust and acceptance by providing clear and accurate information about how AI works, what data it uses, and how it affects their decisions and outcomes. They also need to offer customers the option to opt out or switch to human agents if they prefer

7 Potential AI trends that could skyrocket Financial Services CX

AI is a powerful tool that can transform the CX game for financial services. As technology continues to advance, AI is paving the way for innovative solutions that cater to our evolving needs and preferences. In this exciting era, several AI trends are poised to reshape the landscape of CX, offering enhanced personalization, convenience, and security. From personalized virtual financial advisors to augmented reality banking experiences, let’s explore some of the potential AI trends that could be invented or further developed in the future, promising a new era of seamless and intelligent interactions between customers and financial services providers.

      • 1. Emotion detection and sentiment Analysis:

AI systems could be developed to analyze customer emotions and sentiment during interactions, such as through voice tone or facial expressions. This could help financial institutions gauge customer satisfaction, identify potential issues, and provide personalized solutions based on emotional cues.

      • 2. Virtual Reality (VR) financial experiences:

Future advancements in VR technology could enable customers to have immersive financial experiences. They could virtually explore investment portfolios, simulate real-time market conditions, or attend personalized financial education sessions, all within a virtual environment.

      • 3. AI-powered financial wellness coaches:

AI could be employed to create virtual financial wellness coaches that assist customers in managing their finances effectively. These AI coaches would provide personalized financial guidance, help with budgeting, offer recommendations for savings and investments, and monitor progress towards financial goals.

      • 4. Hyper-personalized Customer Experiences:

AI algorithms could leverage extensive customer data, including transaction history, browsing behavior, and social media activity, to deliver hyper-personalized experiences. Financial institutions could use this data to offer tailored product recommendations, customized offers, and personalized pricing structures.

      • 5. Augmented Reality (AR) for in-person banking:

AR technology could be utilized to enhance in-person banking experiences. Customers visiting physical bank branches could use AR-enabled devices to access real-time information, receive personalized assistance, and navigate complex banking processes more efficiently.

      • 6. Proactive financial insights:

AI systems could analyze customer financial data and patterns to provide proactive insights and recommendations. For example, if an AI algorithm detects that a customer is regularly paying high fees for a specific service, it could suggest alternative options with lower costs.

      • 7. Cognitive robotic advisors:

In the future, AI-powered robotic advisors could combine cognitive capabilities with physical robotics to provide interactive and empathetic customer support. These robotic advisors would be capable of understanding complex financial queries, offering detailed explanations, and even physically assisting customers with tasks like filling out forms.