In today’s competitive landscape, hyper-personalisation differentiates wealth managers, attracting and retaining customers while driving growth… Ultimately, hyper-personalisation improves customer experience, loyalty, competitive advantage, and profitability, ensuring long-term success.

TWM: Please tell us a bit more about yourself?

Roger Portnoy: I am the Chief Strategy Officer for Objectway, leading corporate development, mergers and acquisitions and new strategic projects in wealth, asset management and core banking. I am a board member of a number of WealthTech and FinTech companies headquartered in the US and UK, and from time to time provide strategic advice to private equity and sovereign wealth investors looking to acquire and invest in wealth management, asset management and digital banking. In my career, I have been a CEO on a number of occasions, including building, scaling and selling businesses in the capital markets and financial information sectors, and have been a board member and advisor in more than a dozen successful scaling and exit scenarios over the past 25 years across a range of financial technology businesses. I am most often based in the UK, but my career has taken me to Australia, Singapore, Japan, Thailand, South Africa, the USA and Switzerland.

TWM: Tell us in the first instance – what is hyper-personalisation in wealth management?

Roger Portnoy: Hyper-personalisation has emerged as a transformative force impacting numerous facets of the customer journey in wealth management today, especially through AI and GenAI. It entails tailoring product recommendations and content and aligning these with individual customer preferences and behaviours. This ensures that customers are presented with offerings that are relevant to them, and that these resonate with their unique needs and goals, thereby increasing the likelihood of ongoing engagement.

TWM: Which parts of today’s customer journey can be hyper-personalised through technology such as AI and GenAI?

Roger Portnoy: As mentioned previously, the power of AI allows for the delivery of personalised messages, offers, and experiences through targeted communication channels. Whether through e-mail, mobile apps, or social media platforms, financial service providers can leverage AI to craft tailored communications that resonate with each customer, thereby increasing engagement and brand affinity.

When it comes to the purchase stage, AI offers financial institutions the possibility to leverage past interactions and predictive analytics, to in turn offer customised proposals tailored to individual customer profiles.

AI can also be used effectively further down the line in customer support, where it can play a crucial role in offering personalised assistance and recommendations to address specific inquiries or issue routing or management through chatbots, virtual assistants, and automated response systems, with the goal again of improving customer satisfaction and reducing resolution times.

Finally, in the retention phase, AI can enable the implementation of personalised reporting and proactive outreach strategies by anticipating then quickly and effectively addressing customer needs.

TWM: Why is hyper-personalisation essential for a firm’s growth strategy?

Roger Portnoy: This year, the financial services industry has been put under pressure due to a slowing global economy and a divergent economic landscape. Simultaneously, disruptive forces are reshaping the industry, driven by factors such as higher interest rates, reduced money supply, regulation, climate change, and geopolitical tensions. Amidst this transformation, organic growth will be modest, compelling institutions to seek new sources of value. Hyper-personalisation is, therefore, vital for firms’ growth strategies, as it focuses on enhancing customer loyalty and retention.

TWM: What are the benefits firms can expect by making the move to hyper-personalisation? Is there a need to lay the foundations with hyper-automation first?

Roger Portnoy: First, let me frame what hyper-automation is: within a financial institution’s value chain, it refers to the comprehensive use of advanced technologies such as robotic process automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), natural language processing (NLP), and others to automate and streamline various processes. Since hyper-personalisation in financial services relies heavily on data-driven insights and the ability to efficiently process and analyse vast amounts of customer data, hyper-automation – which involves the use of these technologies – plays a crucial role in laying the foundations for hyper-personalisation.

From customer onboarding to risk management, hyper-automation is revolutionising diverse aspects of business functions.

Below, we list out some examples of key areas where hyper-automation is reshaping business processes and the metrics used to gauge its effectiveness:

• Customer Onboarding: One pivotal aspect of any business is the seamless onboarding of customers. By automating this process, companies can significantly reduce the time it takes to get new clients up and running. Through sophisticated systems that handle document verification, Know Your Customer (KYC) checks, and account setup, businesses aim to not only expedite onboarding but also ensure compliance and accuracy. Metrics such as the reduction in onboarding time per customer, the increase in the number of customers onboarded per unit of time, and the decrease in error rates in document verification and KYC compliance serve as tangible indicators of success in this area.
• Customer Support and Queries: The advent of chatbots and AI-powered systems has revolutionised customer support and query resolution processes. By leveraging these technologies, businesses can provide round-the-clock assistance, swiftly addressing customer inquiries, complaints, and support tickets. Metrics such as a reduction in average response time to customer queries, an increase in customer satisfaction scores, and a decrease in the workload of human customer support agents are indicative of the impact of automated customer support systems.
• Regulatory Compliance: Ensuring compliance with regulatory requirements is paramount for businesses operating in highly regulated industries. Automation streamlines compliance processes, facilitating timely reporting, audits, and adherence to data privacy regulations. Metrics such as a reduction in the time taken to generate compliance reports, a decrease in compliance-related errors, and an increase in compliance audit pass rates underscore the efficiency and effectiveness of automated regulatory compliance measures.
• Risk Management: In the realm of investment portfolio management within financial services, automated risk assessment models empower businesses to proactively identify and address risks. Through the analysis of extensive datasets and the utilisation of predictive analytics, companies can effectively evaluate different types of risk. Key metrics such as enhanced accuracy in risk assessment, decreased probability of financial losses stemming from risk events, and improved efficiency in implementing risk mitigation strategies serve as pivotal indicators of the efficacy of automated risk management systems in this context.
• Back-Office Operations: Routine back office tasks such as data entry, reconciliation, and report generation are ripe for automation. By automating these processes, businesses can minimise manual errors, expedite report generation, and optimise resource allocation to more value-added tasks. Metrics such as a reduction in manual data entry errors, an increase in the speed and personalisation of report generation, and a decrease in the time and resources required for reconciliation processes highlight the tangible benefits of automating back-office operations.
• Cross-Selling and Upselling: AI algorithms are increasingly being deployed to analyse customer data and behaviour, identifying opportunities for cross-selling and upselling products and services. By personalising recommendations and marketing efforts, businesses can drive additional revenue streams and enhance customer satisfaction and loyalty. Metrics such as an increase in the conversion rate of cross-selling and upselling efforts, growth in revenue from additional product/service sales per customer, and improvement in customer retention or NPS (Net Promoter Score) rates are key measures of success in automated cross-selling and upselling initiatives.

TWM: How would you recommend wealth management firms get started on the ‘hyper’ journey?

Roger Portnoy: Mastering hyper-automation requires, as a first step, the establishment of a cross-functional unit with a portfolio of complementary skills and knowledge.

Embarking on this journey necessitates the establishment of a leadership framework within the organisation. This unified team, drawing from various disciplines, must be empowered to identify key stakeholders across the value chain, thereby uncovering use cases with tangible returns on investment. Central to this endeavour is the recognition of business processes that have undergone automation, particularly within expansive value chains, serving as fertile ground for pinpointing metrics that quantify the advantages of transitioning from manual to automated methodologies.

Crucially, the unit’s members should possess a blend of technical, business, and analytical proficiencies, encompassing a deep comprehension of automation technologies, adept process optimisation skills, and robust data analytics capabilities. Given the transformative nature of hyper-automation, team members should also be guided to drive change management, continuous learning and adaptability to facilitate the adoption of automation technologies across the organisation. A reliable partner could help gaining innovation through the most appropriate technologies, enabling wealth firms to seamlessly embark on their digital transformation journey to drive automation and hyper-personalisation initiatives forward.

Financial institutions that embrace a steadfast digitalisation strategy from inception stand poised to distinguish themselves in the market. Those that infuse scalable technologies throughout their entire value chain will exhibit the agility necessary to adapt to evolving customer demands.