Letting AI Take on the Heavy Lifting for Financial Businesses
By Johan Fantenberg, Director at Ping Identity�
Similar to how cranes are used in construction to lift huge items that are difficult or impossible for humans to move, artificial intelligence (AI) can process vast amounts of data and carry out repetitive operations swiftly and effectively. AI can help financial institutes do the “heavy lifting” when it comes to data processing, sifting through enormous volumes of information, and carrying out standard duties like transcription of interviews or producing simple news stories.
IDC predicts a sharp increase in the application of generative AI (Gen AI) in the financial services industry which is expected to grow at an astounding 96.7% CAGR to reach $4.3 billion by 2027. GenAI is being used to improve internal operations efficiency, automate tedious tasks, and streamline back-office functions like fraud detection and complex document preparation.
Singapore was one of the first few countries to launch a national AI strategy (NAIS). The second version of the strategy, NAIS 2.0, budgeted to spend Over SGD1 billion over the next five years to drive AI activities in Singapore. In recent efforts, the Monetary Authority of Singapore (MAS) has committed up to $100 million to support quantum and AI capabilities in the financial sector. The Central Bank of Singapore will support financial institutions in establishing AI innovation centres in Singapore for a range of functions including AI model building and training, deployment of AI models for high-impact use cases, governance and risk management, as well as testing and monitoring. This shows the nation’s firm commitment to strengthening the ecosystem.
Rather than completely rethinking their strategy, decision-makers might adopt a more pragmatic approach and consider what AI has to offer about the current issues that their organisation is facing.
Combating cyberattacks driven by AI
With the rise of Generative AI, financial institutions have begun piloting the technology’s opportunities and assess risks across a range of use cases. ChatGPT and other generative AI systems can help teams with marketing briefs, website content, and documentation, as noted by Forrester with 85% of decision-makers in APAC integrating AI tools into business processes.
Aside from the ethical concerns of employing AI, hackers are increasingly using AI to spot trends in computer systems that point to flaws in security or software, giving hackers access to take advantage of these recently found vulnerabilities, making cyber threats more dynamic and dangerous than ever.
While awareness and training of the workforce are necessary to respond to cyber threats, organisations must adopt a proactive approach by adopting identity security, and other identity and access management (IAM), solutions which incorporate AI to improve security controls. This helps organisations to prevent identity fraud and unauthorised access by utilising real-time surveillance, behavioural analysis, and automated response to suspicious activity.
Decentralised identity (DCI) is another key solution that financial organisations need to consider. By distributing identity verification across a decentralised network, the risk of data breaches is significantly mitigated. This proactive approach makes AI a vital ally in the ongoing fight against cybercrime since it strengthens defence systems and simplifies the management of security operations. In addition, DCI can help financial institutions comply with Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations. Using robust identity verification mechanisms creates an immutable record that reduces the risk of identity fraud and improves the accuracy of compliance checks.
Personalising experiences with AI
Over the years, chatbots have become seamlessly integrated into our day-to-day lives. Thanks to AI-driven chatbots, these customer interactions have evolved from feeling like a cold-blooded human replacement to something better and more conscious. But to achieve the bigger picture, AI must work in tandem with human agents rather than instead of them, as some clients are still apprehensive.
Organisations should concentrate on how AI allows for more comprehensive analytics in addition to chatbots. Streaming giants like Spotify, for instance, conceive of personalised omnichannel experiences for listeners by embedding subscriber’s data into algorithms. This, then, powers recommendations and also allows users to move their listening experiences seamlessly between multiple devices. Using AI to customise digital experiences allows businesses to provide frictionless and seamless digital experiences with this orchestration capacity. This level of personalisation creates a more enjoyable and efficient experience for customers.
Transferring menial chores to AI
AI primarily shines behind closed doors for teams in the finance sector, which are working on products and consumer experiences. These groups are using AI to automate workflows and accelerate operations to increase efficiency and productivity. This guarantees more secure access control and lessens the human labour that IT personnel must perform. AI may be used by teams in practically any kind of organisation, from creating graphics for a PowerPoint presentation to creating documentation and website content.�
The use of advanced AI and machine learning to manage identity governance ensures that identities have the appropriate level of access, automatically adjusting permissions based on user behavior and organisational policies.
Enhanced Business Performance
Artificial Intelligence (AI) is emerging as a transformative force for the financial sector, reshaping industries and redefining the way organisations operate. Analysing the effects closely is crucial to the final success of any new strategic endeavour. People are ultimately responsible for a good AI-driven consumer experience. Building a strong security posture that safeguards identities throughout the company is essential to this. This gives financial organisations the assurance they need to verify AI generated output, improve the accuracy of customer experience & identity threat detection models with the goal to continuously enhance customer experiences.