Recently, I had the opportunity to attend the 10th anniversary reception of Accenture Fintech Innovation Lab. Unsurprisingly, one of the hottest topics of 2023, Generative AI, was covered during the event. Generative AI algorithms analyze massive amounts of data to detect patterns, make predictions, and uncover valuable insights, enabling banks to better understand customer behavior, tailor personalized recommendations, and mitigate risks more effectively. Accenture prepared a highly insightful presentation on the topic, outlining the following key benefits of Generative AI: productivity boost, creativity unleashed, cost optimization, and equalized opportunities.
Accenture presented several use cases where they are delivering Generative AI solutions to their financial services clients:
1) Re-inventing customer onboarding process for a bank: they are working with a fintech in the emerging markets to make customer facing lending operations Gen AI enabled. Starting from the customer needs assessment for product recommendation, KYC and application form auto-fill, underwriting, offer negotiations & disbursement ops all in one window. This will include orchestration of models, BREs and core system entries.
2) Working with a CRO to build financial crime utilities: they are working with a multinational bank CRO to enhance their Financial Crime (Fraud and AML) capture rates by synthetic data generation, transaction monitoring, co-pilot of routine tasks – analysis, report generation, filings, creation of dynamic risk profiles augmenting publicly available information. Leverages all core capabilities of LLMs.
3) Model risk management: they are working with a large bank to build a Model Risk Management capability which provides impacted models, list of variables impacting the model, re-run model and generate new estimates, iterates for new features from catalogue validates model across samples & prepare model documents and deployment code for approval
4) Helping an Asian regulator build use cases for bank & tech consortium: they are leading the setup of a bank and tech consortium for an Asian Regulator. Training for CDOs of all leading banks, defining use-cases, functional design and implementation of top use-cases across tech stacks. Use cases will include utilities that could be leveraged across banks like AML Assistant, Financial Literacy & Well-being, KYC etc.
5) Working with a Middle East central bank to build co-pilots: they are working with a middle eastern regulator to build supervisory specific use cases – Monitoring corporates with large exposures. Tagging related companies by tapping social media signals and news & build tracking reports. For Governance risk study board meeting and gather insights like participants, dissent, agent change, loan approvals after rejection etc.
6) Build a fraud co-pilot with a Middle East clearance house: they are working with a middle eastern clearance house to build a fraud co-pilot that helps investigate potential frauds reported from banks, identifies similar transactions across transaction from other banks, builds and tests new rules to be implemented, generates synthetic data usage of the larger community
7) Helping a European banking group to search better: they are working with a European banking group to transform its knowledge base and make it easier for users to quickly find right information for their needs. Built with Microsoft’s Azure architecture and a GPT-3 large language model, employees can use a web-based app to ask specific questions.
8) Simplifying a multinational bank’s email system: they are working with a multinational bank to transform how it manages high volumes of post-trade processing emails every day and reduce the effort involved with communicating with customers. They are using generative AI and large language models to automatically route large numbers of emails daily to the relevant teams.
9) Personalizing marketing creatives and copy: they are working with a large bank to deliver truly personalized marketing content & creatives for its digital campaigns. They are using LLMs and image generating modules to help campaign executives and designers create customer specific copy and creatives at scale.
During the presentation, only a few use cases of generative AI in the banking industry were covered. However, there are other potential uses as well. For instance, generative AI can optimize investment portfolios, predict market trends, and prevent fraud, leading to streamlined operations, increased efficiency, and better outcomes for banks and their customers. Moreover, this transformative technology is breaking down barriers and making banking more accessible to underserved communities. It enables financial institutions to develop innovative solutions, such as AI-powered chatbots and virtual assistants, that offer personalized support and guidance to customers 24/7.
The possibilities are endless! Generative AI is propelling banking into the future, fostering financial inclusion, and empowering individuals and businesses to achieve their goals.