Babu Sivadasan is the co-founder and CEO of JIFFY.aia no-code AI platform that enables businesses to create delightful user experiences.
Recent research from Deloitte reveals that 86% of AI users in financial services say that AI will play a very important, even crucial, role in their company’s success over the next two years. The study highlights that AI can help improve efficiency, enable a growth agenda, strengthen differentiation, manage risks and regulatory needs, and positively influence customer experience.
Having worked closely with pioneers in this sector for some time, I have seen forward-looking companies focus on business value-driven use cases and invest in various AI capabilities instead to focus on limited AI solutions.
Consider consumer onboarding, which is a critical touchpoint for shaping customer experience and driving organizational growth. Surveys show that banks and financial institutions (FIs) are difficulties with integrationbut most transformation standard bearers seem to be debating within their organization or among peer groups about where and how to start using AI more effectively for this function.
What the collapse of the SVB taught us
Last year, the spinoffs of Silicon Valley Bank and Signature Bank highlighted the importance of onboarding experiences. The aftermath was marked by a seismic shift in deposit patterns, as big banks found themselves grappling with an unexpected influx of business, overwhelming their operational capabilities. The repercussions went beyond simple operational challenges and had a profound impact on financial health and revenue streams.
However, the effects of slow integration processes are not limited to commercial giants alone. Retail banks too faces challenges, as manual onboarding processes triggered a wave of dissatisfaction among customers. Delays, lack of transparency and security breaches cast a shadow over the customer experience, tarnishing reputations and eroding trust. The resulting impact rippled through customer acquisition, retention efforts, and ultimately financial performance.
The Impact of AI-Driven Onboarding
One way banks and financial institutions can address these challenges is through digital onboarding, which uses technologies like AI, ML, and natural language processing to integrate automation, personalization and security in the integration process. Here’s how AI can impact the onboarding process:
Stay compliant with KYC and ID verification
AI algorithms can quickly analyze large amounts of data to perform KYC and AML checks, reducing the time required for manual reviews while ensuring accuracy and compliance with regulatory standards. This can speed up the onboarding process while simplifying the process of identifying and mitigating potential fraud.
Simplify data capture from complex documents
AI-based integration can reduce manual data entry. AI tools can also be used to guide consumers through the onboarding process, answer their questions in real time, and help them fill out forms and upload documents.
Likewise, AI can help behind the scenes by optimizing data integration between systems, ensuring that consumer data is accurately captured and stored.
Provide a flexible and personalized user experience
The AI-powered integration allows consumers to open accounts or access banking services from anywhere, at any time, without the need to visit a branch. Automated systems can quickly verify information, reducing wait times for account activation.
Banks can also add interactive elements such as support via chatbots and personalized product recommendations. This may be particularly appealing to tech-savvy generations, those with busy schedules, or those with limited access to physical bank branches.
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The AI-powered onboarding process generates a wealth of data that banks can analyze for insights into consumer behavior, preferences and needs. Predictive analytics allows banks to offer personalized products and services. This data can also be used to improve cross-sell and upsell opportunities and drive consumer engagement.
Challenges related to digital integration
Despite the benefits, financial institutions face several challenges in adopting digital onboarding, ranging from technical implementation to regulatory compliance.
One of the main challenges is ensuring the security of personal and financial data while preventing fraud. With the integration of AI, organizations must implement robust security measures, including encryption, multi-factor authentication and fraud detection algorithms, to protect against identity theft, phishing and other forms of cybercrime.
The integration must also comply with a host of regulations including Know Your Customer (KYC), anti-money laundering (AML), data protection laws such as GDPR (in Europe) as well as electronic signature standards. Navigating these regulations and ensuring compliance can be complex, particularly for organizations operating in multiple jurisdictions.
At the same time, banks may face integration challenges, as integrating digital integration solutions with the many existing systems (core banking systems, account processing, loans, mortgages, payments, asset management assets, TAMP systems, identity management systems, CRM or ERP) can be difficult. technically difficult. Many banks rely on legacy IT systems that do not easily integrate with new digital onboarding technologies because they may not support the seamless data flows needed for effective digital onboarding.
While the path to AI adoption is fraught with challenges, the technology can also provide opportunities for growth and innovation. By focusing on the adoption of AI to achieve end-to-end digitalization of onboarding and other business-critical processes, such as account management and customer engagement, banking and financial institutions can strive to deliver personalized experiences and pave the way for new revenue streams.
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