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Home > Finance > Why AI isn’t enough in Financial Services

Why AI isn’t enough in Financial Services

Published by Jessica Weisman-Pitts

Posted on March 22, 2022

5 min read

Last updated: January 20, 2026

Data scientists. Programmer team using laptop analyzing and developing in various information on futuristic virtual interface. Algorithm. Marketing and deep learning of artificial intelligence.

By Dr. Dorian Selz, CEO and co-founder of Squirro, which works with organisations to bring them greater insight from their data.

When the volume of data started increasing so drastically in Financial Services (FS), businesses turned to technology to help them manage this data, make sense of it and get valuable insights from it. Data analytics, Business Intelligence (BI) data modelling, data warehousing, and Artificial Intelligence (AI) were all used for this purpose.

AI was especially effective and played a significant role for FS firms in automating various processes, saving time on previously manual tasks, gathering data and much more. However, AI does have its limitations. For FS organisations to truly reap the benefits of the data they hold, AI must be further enhanced, and augmented intelligence is the answer.

The limitations of AI

There is no doubting AI’s impact on many banks and other FS institutions. Yet there are some limitations that have given way to the need for augmented intelligence. Human input is still hugely important, especially in areas of FS such as real estate and institutional asset management.

These sectors have traditionally relied on relationships when it comes to deals. AI can help empower this process, providing information to relationship managers, but there is no instinct, creativity or ethics with AI. It presents information dispassionately and without intent, which limits its usefulness.

There are also issues around AI and access to data. Much of any organisation’s data is siloed, stored in many different systems and repositories, which makes it much harder to view it in context and its entirety. Furthermore, the most insightful data in banking is invariably the unstructured data – the call notes, client emails, news alerts and premium data sources that help build up a comprehensive 360-degree view. Yet most organisations and their AI solutions cannot work with unstructured data scattered across different systems, meaning these insights are left unused. AI can take an organisation so far before its limitations become apparent.

The insight era

While big data is potentially rich in value to any FS firm, much of that potential goes unrealised without a way to extract the value from data – particularly the unstructured data. We live in the insight era, and without insight, data is virtually worthless.

Augmented intelligence – which combines the power of AI with the imagination, intuition and intelligence of humans – delivers that insight. Cognitive search for example, can improve access to information and business efficiency but augmented intelligence goes even further, marrying data with the user’s content and intent to deliver even better results. Augmented intelligence can also offer vertical-specific solutions to address concrete challenges, rather than using the more common ‘one size fits all’ approach of AI.

Augmented intelligence can provide tangible benefits to any bank. The European Central Bank, for example, uses augmented intelligence for risk assessment. It connects all its data sources, applies Natural Language Processing (NLP) and Machine Learning (ML) to them, and uses that insight to monitor all potential risk factors. It then provides users with next-best-action recommendations to help actively assess and mitigate ongoing risk levels.

The Bank of England deploys Cognitive Search to provide unified search across data sources, delivering a new way of visualising the available data. In addition to faster and more accurate results that draw on all data stored on any platform, the application uses self-learning algorithms to enhance relevance.

The future of sales

Business development, sales, retention and acquisition – in corporate FS, these are all of the highest importance and augmented intelligence can play a significant role in powering them. Digital-first is becoming the new normal for B2B buyers, who have less time to interact offline with suppliers.

Gartner has predicted that by 2025, ‘80% of B2B sales interactions between suppliers and buyers will occur in digital channels.’ This clearly impacts traditional ways of selling in FS, which have been dependent on customer-facing interactions, and clears the way for a brand new future of sales.

Anyone with a sales remit in FS needs to adopt a digital mindset and focus on multipipeline selling via digital channels. This will exponentially increase the number of touchpoints and interactions between buyers and sellers, creating interdependencies and interconnections that will be hard to manage without the right data and analytics tools.

This is where augmented intelligence will prove so valuable by enhancing sellers’ experience and intuition with data-driven insights. Intuition and knowledge are not enough for the new virtual selling. A sales team’s talents need to be enhanced with technology that can gather and process data from disparate sources to provide highly valuable information to the sellers for effective customer engagements.

Augmented intelligence and a deeper insight

While AI can be impactful, human intelligence is still imperative to many elements of FS. AI can help gather data sources but augmented intelligence solutions allow a bank far greater access to information and deeper insight collected from unstructured data. This is presented to the user in the form of insight-based recommendations, which can mean more effective risk management/mitigation, improved CX and quicker adaptation to the future of sales.

For any bank that wants to differentiate and adopt an insight-based approach to data and technology, augmented intelligence is undoubtedly the way forward.