How AI Can Enhance Financial Services
No matter where you look, artificial intelligence (AI) is increasingly looking like the future. It has already transformed numerous enterprises and continues to evolve at high speed. Organisations across numerous industries are prioritising AI as a key part of innovation, and this is no less true for financial services.
The ability of financial services organisations to adapt and transform their business models has become absolutely paramount in this uncertain and unpredictable environment. There is a pressing need to ensure firms are delivery across the board, transforming everything from customer experience and customer service, to sales, investment performance, fraud detection, cyber resilience and more. Generative AI is already demonstrating how it is positively impacting every element of the aforementioned areas with studies from . For example, both an exciting set of capabilities and challenges.
As a Microsoft Inner Circle partner, financial services specialist, and an organisation that has deployed AI-driven Microsoft Copilot across our own practice, Xpedition is well versed in guiding organisations on the of AI in strategic implementation of AI in financial services to transform productivity and efficiency, and customer and employee engagement.
AI Explained
Despite the unprecedented advances and interest in generative AI in recent years, AI’s development stretches back decades. The term was first coined 1956. Under the leadership of John McCarthy, along with Marvin Minsky, Nathaniel Rochester, and Claude Shannon, these researchers in language simulation, complexity theory, neuron nets and learning machines convened what would be known as the first conference on ‘artificial intelligence’.
Given the extraordinary leaps in the capacity of electronics and computers, their ambition was to investigate ‘how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves’.
Despite their foresight, the rapid advancements in AI we’ve since seen more recently would no doubt still surprise them. Moreover, AI today is no longer the domain of specialists. In fact, it would be easier to keep track of the sectors where AI is not being at least tested, let alone implemented.
AI in Financial Services
The rise of financial technologies (fintechs), is transforming the finance industry. Established banks are grappling with their own legacy systems while smaller and more agile innovators emerge on the market. Even without sector competition, when it comes to digital transformation, financial services lag behind other consumer-centric industries. Decision making challenges in the financial services industry include improving predictability and extracting maximum value from vast swathes of data, as well as continually adapting to keep with both customer expectations and a evermore stringent regulatory environment.
Investing in AI may well be the key to solving this, but how, exactly?
In the words of the Alan Turing Institute, ‘the adoption of AI in financial services is underpinned by three distinct elements of innovation: machine learning (ML), non-traditional data, and automation’. Unsurprisingly, the most widespread and influential AI-enabled tools in financial services are machine learning, alternative data, and automation.
Machine Learning
ML describes how computer systems can perform tasks based on their ‘learning’ process drawn from data. Unlike older software that encodes explicit rules and logical statements, ML systems can adapt with no additional instruction input from humans. Instead, they use algorithms and statistical models to recognise and analyse data patterns.
As we explore later on, machine learning in financial services is now considered essential for risk assessment, fraud detection and other vital measures.
The Benefits of AI in Financial Services
AI is not new to the financial services industry. As with numerous other industries, AI’s integration into financial services is significantly influencing competitive positioning and transforming dominant business models within the industry.
With the rate of innovation accelerating, there are a few key examples of where AI is transforming financial services for the better:
Delivering Personalised Customer Experiences
Across financial services, winning new customers, and keeping them loyal, is increasingly important. The value of personalisation in the customer journey cannot be ignored. The latest generative AI and data analytics solutions are instrumental in creating memorable, tailored customer experiences. And with next-gen AI such as Microsoft Copilot being infused across Microsoft Dynamics 365 sales, marketing and customer service solutions, it’s the FSI’s that are able to leverage AI to it’s fullest that will be the ones that are able to best power industry leading customer experiences.
For example, Microsoft Dynamics 365 Customer Insights is a transformative tool for financial services, enabling institutions to unify disparate customer data and extract actionable insights that power personalised customer experiences. Utilising the latest in generative AI, financial institutions can dig deeper than ever for meaningful insights, and uncover intelligent analysis derived from vast amounts of data, such as transactions, demographics and customer behaviour, to compile customer profiles for targeted, personalised marketing.
Revolutionising Sales to Drive Revenue
With customers expecting personalised experiences, and ever increasing competition from challenger banks and fintechs, it’s imperative that sellers and sales leaders identify and close opportunities at speed. With Microsoft Dynamics 365 Sales, sales professionals can reduce time spent on mundane, manual tasks and instead, focus on leveraging the powerful insights and reporting that streamlines lead management and accelerates pipeline revenue.
Furthermore, Microsoft Copilot for Sales leverages AI to leads with the highest potential, surfacing next-best actions. For example, Bain and Company estimate that 29% of labor time for sales roles can be automated with generative AI.1
Transforming Customer Service
As part of the wider customer experience, customer service is becoming an increasingly important differentiator for firms looking to stand out in an increasingly crowded market.
With AI-driven insights, FS firms can also leverage Microsoft Copilot for Service to empower service agents to respond at speed, and personalise customer interactions to improve customer satisfaction and loyalty.
Microsoft Copilot for Service is a product that transforms the way agents deliver customer service. By integrating CRM data, natural language, and AI into Microsoft 365 Teams, Outlook and other service solutions, AI-powered Microsoft Copilot for Service helps agents enhance customer service by diagnosing and solving issues more efficiently. Integrating seamlessly with CRM systems for accurate data management, and enabling effective multi-channel communication. it also provides agents with instant, context-aware responses and automatically summarises conversations for efficient resolutions.
Examples of other areas benefitting from AI
Risk Assessment
A number of AI adoptions in financial services are in credit risk analysis. AI algorithms are used to calculate the probability of customer loan defaults, and even the severity of losses. However, it remains the case that many banks’ legacy IT systems are limited to those rule-based AI systems that still require a great deal of human input.
A report from McKinsey suggests that banks need to prioritise machine learning tools across the customer life-cycle, including credit decision-making. In fact, those ‘AI-first banks’ can streamline lending journeys with real-time analysis of data to help a range of business models execute quicker credit decisions.
At Xpedition, we have created the FS Xcelerator, a series of bespoke suite of app built on the Microsoft Power Platform. For credit risk assessment, there is the Know Your Client (KYC) app that enables firms to conduct comprehensive checks during the onboarding process, preventing the oversight of critical client information.
Fraud Detection
As computer technology has become more sophisticated, so has cybercrime and other fraudulent activities. Banks and financial institutions follow strict regulatory frameworks, but AI models allow them to better fight fraud through (among other methods) advanced data collection, identifying abnormalities and assisting investigators through iterative learning.
Conclusion
Digital transformation and the reimagining of the customer experience in financial services is an urgent priority. And it’s the organisations that recognise the inherent benefits of AI that will ultimately be the ones that succeed in this brave new world. In the era of generative AI, staying ahead of the competition demands even more creativity, agility, and experimentation, as well as ethical and responsible use of AI to generate value for customers and stakeholders.
To learn how Xpedition and AI-infused Microsoft business applications can help FS firms accelerate the transition to AI, contact us or register for a cost-free, innovation workshop to discover how we can guide you on your AI journey.
