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With technological advances accelerating incredibly rapidly, artificial intelligence (AI) is playing a larger role in a range of business sectors. One industry harnessing the power of AI tools and techniques is the financial services industry. This article examines how AI helps financial service organisations elevate their game by delivering personalised experiences.
Introduction to AI in Financial Services
What is AI?
The term artificial intelligence, often abbreviated to AI, refers to the ability of machines or software to mimic human intelligence and responses in tools to enhance accuracy, productivity and efficiency. From predictive analysis and natural language processing to robotics and machine learning, there are limitless possibilities for the application of AI.
Benefits of AI in Financial Services
In an era where personalisation is key, AI offers many benefits for financial companies striving to excel in fiercely competitive markets.
- Increased Efficiency: By automating tasks, it gives staff more time to spend on strategy.
- Enhanced Accuracy: Risks associated with human errors are reduced substantially.
- Better Decision-Making: With advanced analytic capabilities at hand, businesses can make better-informed decisions.
- Superior Customer Experience: Enhanced insights enable companies to provide customised solutions tailored individually to users.
Types of AI Used in Financial Services
There are a number of applications that can boost delivery of services.
- Robotic Process Automation (RPA): This is an efficient technique used specifically for automating repetitive operations, from managing customer data to generating reports.
- Virtual Assistants: This is a form of conversational AI assisting agents by understanding and analysing customer requirements that can perform 24/7.
- Machine Learning: Machine learning algorithms identify patterns in structured datasets enabling prediction-based solutions, which can deliver immense value.
There are additional areas where intelligent algorithms can assist with delivering custom solutions to meet specific needs.
How AI Can Help Financial Services Organisations Deliver Personalised Experiences
Data Collection and Analysis
We live in an era where data is the lifeblood of any business. For financial services organisations to deliver personalised experiences, they need reliable data about consumers. Fortunately, AI means organisations can gather massive amounts of raw data efficiently.
Raw data can be gathered from transaction histories, browsing patterns on websites or mobile apps, geographic locations, and social media activity. Once this information is sourced and compiled using AI capabilities, it’s ready for further examination.
Recognising your clients’ preferences from this assorted information can be quite a daunting task. AI has made this simpler by providing comprehensive ways to analyse vast sets of data quickly and accurately. The result is knowledge that empowers financial institutions to better understand their customers’ habits and needs.
Machine Learning Algorithms
Under the broad umbrella of AI solutions for financial organisations you’ll find machine learning algorithms. These tools help predict future outcomes based on historical information meticulously collated over time. Because these algorithms continuously learn from new inputs without requiring further programming, they can play a pivotal role in easily creating personalisation at scale.
Machine learning models are capable of analysing multiple variables, such as purchase trends, frequency and timing of interactions, to dissect and understand individual customer behaviours. They then use these insights to anticipate future actions and to provide tailored recommendations that cater specifically to individual customers.
An example of this is how some companies utilise predictive analytics – a product of machine learning – to assess personal loan applications or credit ratings swiftly and accurately.
Customised Products and Services
Customers across all service industries increasingly expect personalised products tailored expressly for them – and the financial sector is no exception. In response to this growing trend, AI presents unparalleled opportunities in delivering bespoke offerings aligned with consumers’ evolving needs.
AI-powered customisation manifests itself within the financial space in ways such as unique investment suggestions based on an individual’s risk tolerance levels or tailored insurance policies matched with specific lifestyle choices. Even everyday banking has seen innovation, such as personalised pricing strategies or tailored promotions based on deep understanding of customer profiles.
At Cirrus, we’ve helped Premium Credit align their resources with customer demand. Our AI-powered solutions have assisted them to meet the needs of their customers in a more efficient way by reducing their reliance on manual processes and providing real-time insights to aid contact centre agents in offering the right solutions.
A key feature of AI finance solutions comes in the form of real-time support enabled by geenrative AI. These digital assistants make consumer-facing roles easier by assisting customer service agents with in-depth analysis for fast and accurate response to customer inquiries.
Cirrus’ Copilot enables agents to provide an enhanced experience by helping them more efficiently manage the numerous customer requests arriving through their channels. In addition, digital assistants can access relevant documents or even offer machine-generated responses based on customer queries.
Jason Roos, CEO of Cirrus, says: “In customer service, every second counts. Our AI-powered platform gives agents the tools they need to answer customers’ questions with confidence. We see this as a real game changer, as the complexity of financial products and services can make it difficult for agents to answer customer queries not only quickly but also accurately.”
Continuous Evaluation and Improvement
This investigation isn’t truly complete without looking at the ongoing improvements that can result from AI’s self-learning capabilities. Every interaction offers more data which in turn helps refine subsequent operations moving the entire operation towards greater efficiency.
Not confined to augmenting user journey, AI solutions enable organisations to identify bottlenecks and allow for prompt corrections.
Examples of AI-Driven Personalised Financial Solutions
Artificial intelligence has generated unique solutions tailored to individual customer needs in several areas.
Personalised Investment Advice
AI has significantly changed the scope of investment advice. It facilitates personalised input by analysing various data points pertaining to a user’s financial history, risk-taking capacity, and long-term objectives.
Robo-advisors are excellent examples of this shift. These platforms leverage intelligent algorithms to offer personalised investment strategies without human intervention. This innovation is made possible by superior computational prowess and comprehensive data analysis.
Customised Financial Planning
Planning for the future can be daunting with considerations such as retirement planning or saving for children’s education to take into account. Financial planning is essential, but a one-size-fits-all approach doesn’t work and customisation is needed.
AI can understand patterns from customers’ past behaviours and is able to anticipate future needs accurately. This helps to provide tailor-made financial plans that cater precisely to requirements and aspirations.
Tailored Loan Solutions
Today, lenders evaluate loan applications based on traditional credit scores and new criteria generated by AI systems. This utilises machine learning algorithms that analyse alternative data sources like educational background or utility bill payments, enhancing decision-making processes while providing a personalised experience.
Further advancements have led to implementation of dynamic interest rates, tailoring loan repayments based on an individual’s paying capacity. This can improve overall business-customer relations in this segment too.
Customised Insurance Solutions
Insurance companies have been quick to adopt AI-driven personalisation thanks to telematics-based policies. These policies determine premiums based on monitored driving habits as well as standard parameters like age or vehicle type.
When helping AND-UK improve their contact centre operations it became clear that AI-powered solutions can not only help call centre agents deliver better and faster customer service, but also improve processes, reduce agent training time, and minimise operational costs.
From data collection and analysis to customised product recommendations, machine learning has revolutionised the finance industry. The effectiveness of AI lies in its ability to learn patterns and its game-changing capability for continuous evaluation and improvement.
Highlighting examples such as personalised investment advice or loan solutions shows the boundless potential ahead. While generic solutions were once the norm, now every solution offered could very well be tailored to someone’s unique situation.
At Cirrus, we can help you leverage the full potential of AI and its associated technologies to deliver better customer experiences. With us, you’ll have a reliable partner on every step of your journey. Contact us today to unlock the possibilities with AI and take your business to new heights.