• Barath Narayanan, Global BFSI and Europe Geo Head at Persistent Systems


• 30.10.2024 12:00 pm
#GenAI #Precision

Financial organizations have elevated their GenAI efforts from experimentation to scaling and value creation. With its ability to address Europe's ongoing shortage of skilled workers and provide companies with competitive advantages in both the short and long term, GenAI has the potential to increase Europe’s annual GDP growth by 0.4% to 0.7%, resulting in an additional $1 trillion in GDP by 2030. While this impact will vary by industries, organizations will reap GenAI benefits based on the strategic alignment of GenAI programs to their business priorities, tech investments into enabling GenAI applications, quick adoption by users, and how well they leverage the ecosystem.   

UK-based financial institutions are facing rising cost pressures, disintermediation of lending and growth of private debt, regulatory scrutiny, and shifting customer expectations. Leaders are hence prioritizing three key pillars: Customer Experience and Growth, Operational Efficiency, and Regulatory Compliance and Risk. GenAI solutions aligned to these strategic imperatives, can add billions in value to the banking and financial services industry through newer sources of revenue and increased productivity.  

Focusing on the first pillar, financial organizations are witnessing a broadening spectrum of customer profiles—diverse age demographics, businesses ranging from single-person micro-enterprises to mega corporations, bargain hunters to cross-generational loyalists, and the inclusion of underbanked populations—all demanding hyper-personalized offerings delivered anytime, anywhere. Successfully catering to these varied customer profiles puts immense pressure on relationship managers. GenAI can act as a trusted sidekick to generate custom marketing messages and recommend sales strategies based on customer persona, historical interactions, company offerings, buying tendencies, etc. After a meeting, GenAI sales assist applications can generate notes, action items, trigger follow-up workflows, etc. 

GenAI can help traditional banks level the field with niche players and private lenders by creating tailored offerings that suit the customer’s needs, accelerating underwriting and processing, generating precise assessments of risks, and helping detect frauds. It is not just about keeping pace with competitors—it’s about anticipating the future, where boundaryless transactions, open finance, and embedded finance have become the norm.

For wealth managers, GenAI can generate investment advice based on market macro, investment target analysis, customer risk appetite, current exposure to investment vehicles, and financial goals. The manual analysis of business news and financial updates is time-consuming and limits scalability, leading to delays in delivering critical information to investors, which can impact timely decision-making. Manual methods also increase the likelihood of errors and the dissemination of outdated or incorrect information, potentially misleading investors and reducing their trust in the advisors’ reliability and competitiveness. AI augmentation enables a wealth advisor to provide precise and personalized advice on how much, when, and where to invest to maximize capital returns. We helped one of the investment companies use GenAI to generate proposal memos and pitch decks for credit decisioning and underwriting, boosting analysts’ efficiency and improving investment decisions by over 40%.

To improve efficiency and risk management, GenAI solutions can parse natural language reports—such as annual reports, performance summaries, filings, contracts, and medical image scans—and synthesize summaries. These summaries help speed up decisions on loans, insurance coverage, claims processing, and recovery actions. This GenAI augmented automation adds precision, personalization, and speed to the backend processing tasks. Each application can be verified in detail, using base information at a scale that humans alone cannot match. On the risk management side, financial institutions are implementing GenAI to address regulatory compliance, financial crime, credit risk modelling and analytics, cyber risk, and climate risks.

GenAI is an enabler, not a silver bullet. Organizations need to adhere to a few key tenets to make the GenAI programs successful - clean and relevant data, process alignment, cross-functional talent both in-house and via partnerships, ecosystem approach, right tools and technology layers, avoiding bias in generated content, ensuring data privacy, security, observability, and cost control.

I believe we are just beginning to explore what's possible. As our understanding deepens and we become more familiar with the applications, limitations, risks, and regulations of the technology, there is a huge potential to be tapped.