AI innovation in financial services

Summary

The next big thing in tech – generative artificial intelligence – is promising to change everything from the world economy to our personal lives. The hot topic was discussed in depth in several sessions at the Asset Finance Connect Summer 2023 Conference.

Sulabh Soral, AI Officer at Deloitte said: “At its most basic, AI is software that mimics and generates human behaviour – planning, generating ideas, understanding speech and visuals. Its ability to scale human intellect will have a profound impact.”

Forms of AI in use today include digital assistants, chatbots and machine learning amongst others. As humans and machines collaborate more closely, and AI innovations come out of the research lab and into the mainstream, the transformational possibilities are staggering.

As a source of both huge excitement and apprehension, AI and its limitless potential operates at a superhuman level. While the applications of generative AI are in the early stages, the capacity of these AI models is doubling every three months.

There is huge investment potential in this complex and highly intelligent technology. PwC’s Global Artificial Intelligence Study: Exploiting the AI Revolution describes AI as: “the key source of transformation, disruption and competitive advantage in today’s fast changing economy.”

According to PwC, AI can transform the productivity and GDP potential of the global economy with global GDP rising to 14% higher in 2030 because of the accelerating development and take-up of AI. However, strategic investment in different types of AI technology is needed to make that happen. 

ChatGPT is a generative AI model developed by OpenAI and is at the forefront of this revolution. It is nearly on par with the human brain and it is only getting smarter.

Shaping up to be the most revolutionary technology since the internet, the full implications of generative AI are still untold. This latest innovation in AI will drive an explosive growth and value creation in the technology sector over the next couple of years and vast potential implications for the financial services sector.

Generative AI

The launch of ChatGPT, an example of a Large Language Model (LLM), has sparked an explosion of interest in AI technologies. The development of LLMs allows the access of natural languages, unlocking vast amounts of information, for example, scientific, historical accounts, literature.

Generative AI is not just about linking data and databases but trying to behave like humans to create responses that make sense with, for example, conversation and human-like dialogue; instantaneous responses; and being able to act in a nuanced way with cultural references and adapt to the tone of the conversation.

ChatGPT can be trained to operate within a particular industry knowledge foundation. For example, in retail, AI language models have a number of benefits including accessing a lot of information, interacting in a natural way, assisting with complex data tasks, and solving a number of problems and issues.

New findings from Deloitte’s 2023 Digital Consumer Trends research found that a third of those who have used Generative AI in the UK have done so for work, equating to approximately four million people.

Paul Lee, partner and head of technology, media and telecommunications research at Deloitte commented: “Generative AI has captured the imagination of UK citizens and fuelled discussion among businesses and policymakers. Within just a few months of the launch of the most popular Generative AI tools, one in four people in the UK have already tried out the technology. It is incredibly rare for any emerging technology to achieve these levels of adoption and frequency of usage so rapidly.

“Generative AI technology is, however, still relatively nascent, with user interfaces, regulatory environment, legal status and accuracy still a work in progress. Over the coming months, we are likely to see more investment and development that will address many of these challenges, which could drive further adoption of Generative AI tools.”

Implications for UK businesses

As generative AI further develops, more and more services can become automated. AI can understand mass amounts of data so can reduce the workload of humans, make speedier decisions, and be more personalised.

In the business world, AI can be used in:

• Customer service – enhance customer service and increase customer loyalty
• Fraud detection – AI can be used to detect intent
• Tax service – improve customer service and help file taxes
• Process optimisation – credit and loan decisioning, process automation, internal document tagging. AI can help accelerate slow application processes, improve loan collectability and user experience, personalised loan collection communication, segment credit users.
• Improve decision making – in areas such as portfolio management, asset allocation and investment strategy. Roboadvisors are widely touted as one of the highest potential technologies involved in AI in fintech.
• Regulatory compliance – ensuring transparency and security, anti-money laundering, KYC systems, compliance mentoring.

AI provides the potential to enhance quality, personalisation and consistency, and save time.

In a recent analysis of the potential long-term impact of automation – Will robots really steal our jobs? – PWC determined that almost 30% of UK financial services jobs could be replaced by automation by 2030, offering big gains in productivity and customer experience. However, the report also predicted that the nature of some occupations would change rather than disappear. It added that automation could create more wealth and additional jobs elsewhere in the economy.

PwC’s Global Artificial Intelligence Study: Sizing the Prize highlighted just how big a game changer AI is likely to be, and how much value potential is up for grabs. AI could contribute up to US$15.7 trillion to the global economy in 2030. Of this, US$6.6 trillion is likely to come from increased productivity and US$9.1 trillion is likely to come from consumption-side effects.

According to the study, the adoption of ‘no-human-in-the-loop’ technologies will mean that some posts will inevitably become redundant, but others will be created by the shifts in productivity and consumer demand emanating from AI, and through the value chain of AI itself. In addition to new types of workers who will focus on thinking creatively about how AI can be developed and applied, a new set of personnel will be required to build, maintain, operate, and regulate these emerging technologies.

In the near-term, the biggest potential economic uplift from AI is likely to come from improved productivity. This includes automation of routine tasks, augmenting employees’ capabilities and freeing them up to focus on more stimulating and higher value-adding work.

More and more businesses are turning to automation, investing in AI to replace staff and cut costs. The 2023 McKinsey Global Survey – The state of AI in 2023: Generative AI’s breakout year found that one-third of survey respondents said their organisations are using gen AI regularly in at least one business function and 40% of respondents said their organisations will increase their investment in AI overall because of advances in generative AI.

Recently, telecoms giant BT announced it will be shedding about 10,000 jobs by the end of the decade as it digitises and relies more on AI automation.

However, the ultimate commercial potential of AI is doing things that have never been done before, rather than simply automating or accelerating existing capabilities.

The potential for advances in artificial intelligence will be one of the areas researched at the recently launched Gillmore Centre for Financial Technology at Warwick Business School. The aim of the Centre is to spearhead cutting-edge research and innovation for the UK’s financial and technology sectors, with leading research on AI development and machine learning.

Ram Gopal, Director of the Gillmore Centre for Financial Technology, said: “The Gillmore Centre for Financial Technology will act as a beacon for industry leading research across fields such as AI, blockchain and machine learning, helping to elevate government policy, inform regulators, and guide businesses through the safe development of these areas.”

AI: Not a new concept in the business world

We are seeing a proliferation of AI tools and applications in the business world, including digital assistants, chatbots and machine learning amongst others.

Despite recent advances in generative AI and the explosion of public interest in AI with the launch of ChatGPT, the AI data modelling concept including machine learning and statistical models has been around in UK businesses for many years, developing further since the emergence and development of Cloud technology, a key component for AI allowing it to evolve due to the need to store and process large volumes of data.

AI is already being used by retailers for metrics for pricing, writing advertising copy, and service booking systems, for example.

Fintech Innovator presentations

The Fintech Innovator session at the recent Asset Finance Connect Summer 2023 Conference provided four use cases for artificial intelligence in the auto and equipment finance sectors.

AI in onboarding: In auto finance, AI can use browser behaviour data to predict car brand and buying intent. AI will enable the ability to segment customers by data and enable better customer journeys in a real-time solution.

Currently, there is a revolution in the way cars are being sold which could be enhanced by incorporating AI in all ecommerce platforms.

AI in manual underwriting: AI can be used to predict the outcome of manual underwriting. There are many opportunities and challenges of using AI to progressively automate credit decisions to reduce cost to service and decision times. AI has the power to automate the majority of the manual underwriting process, reducing time, saving costs and enabling growth.

AI in origination: Generative AI solutions based on ChatGPT allows customers to ask detailed questions about their finance contracts. AI can be used as a copilot to take away drudgery and unlock a new wave of productivity, without losing the human element. AI can be used to solve a communication problem across the industry.

AI in retention: AI can be leveraged for enhanced customer retention and OEM success in the auto finance sector, and can be used to optimise the timing and offer for auto finance customers at the end of finance contracts and ability to retain the customer mid-term.

By incorporating AI into various aspects of the customer journey, retailers and financiers can improve customer satisfaction, anticipate and address customer needs, and ultimately enhance customer service and retention.

Limitations

With the unprecedented growth in AI technologies, it is essential to consider the potential risks and challenges associated with their widespread adoption, for example, security, privacy, bias, hallucinations, and repetition.

A 2023 Forbes article, highlighted the 15 biggest risks of artificial intelligence:

• Lack of transparency
• Bias and discrimination
• Privacy concerns
• Ethical dilemmas
• Security risks
• Concentration of power
• Dependence on AI
• Job displacement
• Economic inequality
• Legal and regulatory challenges
• AI arms race
• Loss of human connection
• Misinformation and manipulation
• Unintended consequences
• Existential risks

The article notes that, “To mitigate these risks, the AI research community needs to actively engage in safety research, collaborate on ethical guidelines, and promote transparency in artificial general intelligence (AGI) development. Ensuring that AGI serves the best interests of humanity and does not pose a threat to our existence is paramount.”

The AI industry is working to solve these problems in a number of ways including focusing on more specialised models, such as BloombergGPT^TM. This new large-scale generative AI model is a large language model that has been specifically trained on a wide range of financial data to support a diverse set of natural language processing (NLP) tasks within the financial industry.

Case study: Evolution AI

Evolution AI is using artificial intelligence in the financial services sector to assist with expedient, accurate lending decisions.

Set up in 2015, Evolution AI specialises in intelligent data extraction from business documents. Evolution AI rejected the traditional OCR (optical character recognition) technology as it failed to extract data from a lot of business documentation and is now using modern AI based methods.

Humans are no longer needed to read bank statements and balance sheets or go through business documents for underwriting purposes. Such boring repetitive manual work can now be fulfilled using AI algorithms.

Evolution AI’s CEO Dr Martin Goodson highlighted that you can’t 100% automate a process as you will always need people and human relationships, but you can automate elements of the process to reduce risk and drive efficiency.

Finance provider Novuna Business Finance and specialist commercial lending bank DF Capital both use Evolution AI software to simplify such business processes.

Novuna faced challenges with supplier invoices and extracting information using standard OCR technology. They decided to use Evolution AI software to extract data from business documents but had to address the orchestration of Evolution AI into Novuna’s system.

The successful implementation of Evolution AI’s software has allowed Novuna to extract from even more documents (for example, for sustainability reporting) and to use functionality during other stages of the process, such as with proposals earlier in the process.

Adam Crockford, Senior Change Manager at Novuna Business Finance said, “AI is not a threat but a tool to be used.”

DF Capital use Evolution AI software for the commercial lending side of their business with dealers and manufacturers. Previously DF Capital had to manually extract data from invoices and upload into their core banking platform. However, DF Capital wanted to scale up their business and use more automation going forward.

DF Capital are now taking the Evolution AI solution to the next level and are building API integration between Evolution AI and DF Capital’s core banking platform, linking to pre-existing automation from dealer and manufacturer portals. This allows for processing times to be reduced by 90%, increased even further by straight-through processing, an automatic solution for seamless electronic transactions and interactions without manual intervention.

For DF Capital, taking people on the AI journey with them is as important as bringing in the new automation technology.

Next steps

Artificial intelligence is constantly evolving. The financial services sector is planning to increase their AI investments across infrastructure, model development and deployment over the coming months and years. The industry therefore needs to look at AI use cases using a design thinking approach to enable financial service organisations to respond to this rapidly changing tech environment and to create maximum impact.

Are jobs at risk? This is always asked when a big technological change happens. While artificial intelligence will replace some human jobs as the technology advances, this evolving tech will in turn create new roles and new opportunities. AI can take away a lot of the repetitive drudgery, but it cannot take away all human roles.

With AI technology rapidly advancing, Evolution AI is further developing their use of AI for the future. Evolution AI’s Goodson commented that, in his 20 years in technology, there has never been a time when things have moved so quickly with weekly breakthroughs.

“AI combines excitement with anxiety in a shifting landscape of hands-on exposure to modern AI capabilities. Big changes are afoot,” concluded Goodson.

References:

More than four million people in the UK have used Generative AI for work – Deloitte | Deloitte UK

Will robots really steal our jobs? (pwc.co.uk)

Report – PwC AI Analysis – Sizing the Prize

The state of AI in 2023: Generative AI’s breakout year | McKinsey

The 15 Biggest Risks Of Artificial Intelligence (forbes.com)