By Erin Nicholson, Global Head of Data Protection and Privacy at Thoughtworks
Long gone are the days of keeping a physical piggy bank in your bedroom cupboard or struggling to remember to pay in a cheque at the bank. Digital transformation in finance has made life easier, pushed along by fast growing fintechs. The latest strides in digital transformation of the banking sector is thanks to artificial intelligence, ensuring convenience of use and keeping our money safe. By fully embracing digital transformation in banking, we can ensure the AI revolution benefits not just a select few, but everyone’s finances.
Generative AI’s powerful impact is reshaping the way we all interact with money. The most transformative uses of AI often lie not in flashy new toys, like sci-fi reminiscent AI assistants and chatbots(although they are fun and have their uses), but rather in the diligent and smart work of integrating AI into existing processes.
The chatbot use case dominates headlines, but is not where the real impact will be with AI. True AI impact lies in harnessing existing frameworks to empower individuals and make digital financial services safer and more secure.
To assist with the adoption of AI, the tools we have in our arsenal, such as Data Protection Impact Assessments, transparency statements, data flows, and legal departments assessing IP and confidentiality issues, are still in play. Trying to reinvent the wheel could lead to a slowing of innovation and adoption or missing key risks which could have been easily overcome with tried and tested methods.
Every finance player in the game wants a chance to score
Recognised flagship banks to canny fintech scale-ups are now building faster, more scalable and future ready organisations. At the frontline of this data revolution are emerging players who are using AI to lower cost and deliver more innovative offerings. And with more data, generative AI can be used to create personalised payment experiences, such as suggesting ways to cut down on household bills, aid in fraud detection, and to help supercharge customer loyalty and satisfaction.
For example, the proliferation of digital payment methods is pushing us towards a post-cash world, for better or worse. Today, Apple Wallet and its peers have become commonplace, seamlessly woven into the fabric of our everyday existence.
This quick widespread adoption underscores the power of digital payments, not just in terms of convenience when you forget your wallet, but also for a more data-driven financial world.
Balancing innovation with careful consideration
It is vital to remember the privacy and security needs of both sensitive customer data and proprietary and confidential data. At the forefront of this is creating a well-functioning digital infrastructure – sustainable and safe AI depends on it. For example, when a bank representative might want to quickly analyse long legal documents, could we empower them to safely use GenAI or AI systems to find information quickly and make a decision with AI assistance?
Generative AI and privacy engineering together allows an innovative approach to any business model, looking at trends and surfacing risks and opportunities which were buried in the data before, this is especially true for fraud detection. Secure multi party computation and federated learning would allow for analysis on data sets without infringing on an individual’s privacy. Risk management can be substantially enhanced by AI’s automation capabilities and greater understanding of customer profiles. With understanding profiles comes the ability to, in an automated fashion, pick out anomalies which could be fraud or a reaction to phishing. We can do this at the personal level, but also use it to analyse trends, such as new types of fraud, and alert people to it before it has had a chance to cause damage.
It’s like replacing a spade with an excavator – same job, just a completely different level of speed and ability. The ability of completely changing the manual time consuming processes that are often prone to human error, means we can see far more accurate and data-driven processes driven by AI. AI can transform the way organisations generate reports, identify risk from large volumes of data and automate previously manual processes.
Financial organisations face significant hurdles in AI adoption. The sheer volume of sensitive and proprietary data they manage and process means it can be challenging to gain value and counteract new privacy risks. The solution lies in embracing emerging privacy technologies to help manage this process.
Businesses who champion and tactically invest in AI and data to deliver long-term growth will beat those chasing short-term wins. Everyone wants their money in the safest place, especially in seamless processes without constant alerts or laborious authentication or fraud management methods. It is a careful balancing act, and one that AI is poised to help with.
