Jochem van der Veer, CEO of TheyDo
Data underpins practically every industry, but few industries are as data-driven as financial services. Advancements in data processing and analysis in recent years has transformed the business models of banks, insurers, mortgage providers and other FS providers, helping improve the accuracy of pricing, increase agility, and better pinpoint fraud and customer challenges.
Today, some organisations are already enlisting the help of AI to improve how quickly and effectively they are processing data, unlocking more insights than ever before. AI is currently the fastest-growing segment of technology hires for banks worldwide, with the use of AI tech expected to increase banking industry revenue by $1 billion as early as 2026.
But while data analysis has brought with it a wave of benefits, organisations are at an inflection point. TheyDo research found 61% of financial services leaders feel overwhelmed by the sheer amount of data and dashboards they rely on daily. Leaders are going blind to data and dashboards, and organisational siloes mean many worry they are missing opportunities or making decisions based on partial or inaccurate data.
How can financial service leaders turn data overload into data-driven advantage?
The Data Dilemma in Financial Services
The rapid growth of data analysis tools in the last decade, especially in an industry that is so data-driven and craves accuracy, has been both a blessing and a curse.
As data usage and reliance increases across organisations, common data management strategies such as spreadsheets, dashboards and manual reporting processes have lacked scalability. Departments often operate independently, analysing a narrow view of information and making decisions without collaboration or interrogating these in relation to the bigger organisational picture. Leaders are faced with an ever-growing number of insights, but struggle to piece together the trends and act on them.
Business leaders estimate just 45% of business data is fully utilised in decision-making, meaning nearly half a company’s data is not used when making strategic decisions. No matter how many data points are consulted, it’s ultimately like driving with one eye closed.
AI is a double-edged sword when it comes to this challenge too – at the same time as it unlocks more valuable insights and can improve efficiency, it also risks exacerbating underlying issues around insights overwhelm.
All of these issues contribute towards slower decision-making, missed opportunities, and inefficiencies.
The Solution: Smarter Data Strategies
Breaking down these data siloes is not just going to be solved by improving team collaboration and adding more meetings. Collaborative meetings and shared dashboards can help, but the root problem of data overwhelm is fragmented workflows. This is where journey management steps in – it is a structured, data-driven approach to decision-making that aligns teams around the full customer journey. It connects insights across the businesses in real-time, creating a single source of truth by consolidating dashboards, and ensuring insights can turn into action that ultimately ties back to bigger organisational goals.
For those working in financial services, this approach empowers everyone within the organisation to work from a shared, holistic view of operations. The key change is that insights are placed within context, enabling any business leader to make more informed decisions and identify pain-points and opportunities to enhance the customer journey like never before.
In short, journey management in financial services enables processes to become easier, faster and more human-focused.
From Overwhelm to Data-Driven Success
Financial services is a hugely emotive and volatile business by nature. Wrong decisions in sensitive moments have even more detrimental consequences to customers, while missing crucial information leaves financial services employees potentially making the wrong decisions that can be costly.
As organisations continue to grow and AI tools help unlock more insights, the divide between disjointed teams will only widen. But more data doesn’t have to be dreaded. When managed effectively and channelled in the right way, it’s an invaluable asset for teams to drive efficiency and growth.
Forward-thinking financial services brands are already looking at journey management to improve business operations and ensure investments in more AI automation doesn’t simply contribute to greater data overwhelm and blindness. Embracing journey management is going to be essential to staying agile and truly reaping the benefits of the data-driven age.
