Artificial Intelligence – A brief overview
In recent times, AI technology has quickly turned from a frequently parroted buzzword to a key differentiator that drives value for businesses.
According to PwC, 40% of all top-performing businesses are increasing investment in AI, and 25% are expecting to see increases in revenue as a result. The average budget set aside by companies for AI & ML has also increased by a whopping 85% year on year, with early adopters being the biggest winners.
The flywheel effect is highly pronounced in data-driven areas such as AI & ML, as the efficacy of AI models improves based on data quality & with better AI models comes more customers and more data.
AI models, when stripped down to their bare basics, are used to perform just a handful of tasks that turn out to have enormous consequences –
- Pattern detection, by learning from data
- Foresight, by extrapolating learned patterns
- Customization, by generating rules & optimizing outcomes
- Decision-making, by generating & testing rules
- Interactions, by learning from human-based communication
By combining the pattern detection & decision-making capabilities of well-trained AI, businesses can apply AI & ML models to detect fraud, improve customer experience & boost process automation.
AI-powered digital onboarding combines all these applications to optimize, safeguard & automate the industry-agnostic processes of onboarding & verification.
The role of AI & ML in digital onboarding
The onboarding process is common to a variety of sectors & businesses. It involves collecting identifying information from a customer, employee, or vendor, accurately verifying this information, and in some cases, making risk-based decisions based on this information.
The problems inherent to this process are that it’s hard to scale, vulnerable to fraud, prone to errors & difficult to standardize due to numerous regulations governing the process.
Leveraging AI & ML in the onboarding process ameliorates these problems.
The pattern detection and decision-making capabilities of AI models allow for ID documents to be scanned & authenticated to a high degree of accuracy instantly. The same capabilities prevent instances of fraud by recognizing fake documents & fraudulent profiles, and reduce manual onboarding errors due to superior decision-making.
Finally, the learning capabilities of AI models enable businesses to automate the compliance process for onboarding by creating a rule-based framework.
According to surveys, among companies leveraging AI, 57% use it to improve their CX, 46% to detect fraud, and 49% to automate their processes.
Use cases for AI-enabled Digital Onboarding
As previously mentioned, AI-powered digital onboarding finds applications across sectors and industries. Here are a few to illustrate the broad applicability of AI in onboarding.
- Banking & finance – ID fraud & compliance are massive issues for banks during the customer onboarding process. AI-enabled onboarding allows banks to use profile filters, document verification techniques & facial recognition to root out fraud & scale their onboarding process.
- Insurance – Insurers often face the same problems as banks during their onboarding process, with insurance fraud getting its start due to verification techniques being vulnerable to attackers. AI enables insurers to secure their onboarding process while also enabling predictive analytics.
- HR – The HR sector is already scaling up onboarding operations by leveraging AI-enabled instant document verification & facial pattern matching to rapidly and securely onboard employees at a fraction of the original cost.
- Gaming – With legitimate money laundering risks & poor onboarding CX, the gaming sector is now leveraging AI to automate document verification, filter out fraudulent profiles, geo-tag users to prevent financial crime, and complete the onboarding process seamlessly with no hitches.
Advantages of AI-enabled digital onboarding
The benefits of leveraging AI & ML models in the onboarding process are numerous and quite tangible. Here are a few.
- Improved CX – AI boosts customer experience by learning from customer-system interactions.
- Better decision-making – AI models learn from older decisions to improve execution capabilities & reduce errors.
- AI-driven product & business innovations – Leveraging AI enables high-level automation & the creation of new risk-based business models that boost value creation.
- Cost savings – AI-powered automation drives massive cost savings across the board.
- Increased efficiency & productivity – AI boosts operational efficiency by automating & optimizing key processes and boosts productivity by identifying & solving pain points.
- Reduced turnaround times – AI-enabled automation reduces bottlenecks in the onboarding process.
Conclusion
AI & ML play a massive role in making the onboarding process fraud-proof, error-free, and completely automated.
AI-powered digital onboarding enables businesses across sectors to verify customers, employees, or vendors to a high degree of accuracy, onboard them securely, and optimize the onboarding process to boost savings and efficiency.
You may be interested in: 6 Tips for Improving Your New Hire Onboarding Process
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