Artificial Intelligence – A quick outline
In recent years, AI technology has quickly transformed from a commonly-used buzzword into a significant differentiation that creates value for companies.
Based on PwC, 40 percent of top-performing companies are investing more money in AI, and 25% expect an increase in revenues. The budgets set aside by businesses to fund AI & ML have also grown by an astounding 85percent year-on-year, and early adopters are the most successful.
The flywheel effect is particularly evident in areas driven by data, such as AI & ML, in that the efficiency of AI models is enhanced by analyzing the quality of data. With improved AI models come increased customers and data.
AI models stripped back to their fundamental essence are employed to carry out a few tasks that can be extremely important –
- Pattern detection is based on using data to learn
- Foresight is the ability to extrapolate patterns that we have learned
- Customization, through the generation of rules and optimizing the results
- Making decisions through the creation and testing of rules
- Interactions, through studying human-based communication
By combining the pattern detection and decision-making abilities of trained AI, businesses can employ AI & ML algorithms to spot fraud, improve customer service and increase the efficiency of their processes.
Artificial Intelligence-powered onboarding integrates all the applications mentioned above to enhance and secure industry-specific processes for onboarding and verification.
The function of AI and the role of ML to assist in the process of digital onboarding
The onboarding process is typical for a wide range of industries and businesses. It involves gathering identifying data from a prospective customer employee, vendor, or customer, confirming the data, and in certain instances, making risk-based decisions using the information.
The main issues associated with this method are that it’s challenging to scale, susceptible to fraud and mistakes, and difficult to standardize because of many regulations governing the procedure.
Utilizing AI & ML in the onboarding process can help solve these issues.
The ability to detect patterns and make decisions of AI models enable ID document to be authenticated and scanned with high accuracy in minutes. Similar capabilities help stop fraudulent transactions by identifying fake documents and profiles. It also helps decrease the chance of manual onboarding mistakes because of the higher-quality decision-making.
Additionally, the capabilities to learn about AI models can help businesses automate the process of compliance onboarding by creating a rules-based framework.
According to studies in businesses that leverage AI, 57% use it to enhance their CX, 46% use it to spot fraud, and 49% to automatize their processes.
Use cases to enable AI Digital Onboarding.
As mentioned, AI-powered digital onboarding has applications across all industries and sectors. Here are a few examples to demonstrate the wide-ranging application of AI to onboarding.
● Banking and finance ID fraud and compliance are significant challenges for banks in onboarding customers. AI-powered onboarding allows banks to utilize filters for profile and document verification techniques and facial recognition to eliminate fraud and improve their onboarding procedure.
● Insurance Insurers have the same issues as banks in their onboarding process and the emergence of insurance fraud because verification techniques are susceptible to attack. AI helps insurers secure their onboarding process while making predictive analytics possible.
● HR HR – The HR industry is already increasing onboarding processes by using AI-powered instant document verification and facial pattern matching to quickly and securely onboard employees for less than the original cost.
● Gaming – With legitimate risks of money laundering and poor CX for onboarding, Gaming is now using AI to automate the verification of documents and filter out fake profiles and geo-tag users to stop financial crimes and finish the process of onboarding seamlessly without any hiccups.
Benefits of AI-powered digital onboarding
The advantages of using AI & ML models in onboarding are many and very tangible. Here are some.
- Enhanced Customer Experience AI enhances the user experience and improves customer service by reviewing customer interactions.
- Improved decision-making: AI models can learn from past decisions to improve execution capabilities and decrease mistakes.
- AI-driven business and product breakthroughs: The use of AI in business and product development allows high-level automation and the creation of risk-based business models that boost your business’s value.
- Save money AI-powered automation delivers substantial cost savings across all levels.
- Efficiency and productivity increase – AI enhances efficiency in operations by automating and optimizing crucial processes and increases productivity by discovering and solving problems.
- Reducing turnaround times-enabled automation decreases the number of bottlenecks that occur during the onboarding process.
AI & ML play a massive part in making onboarding completely error-free, fraud-proof, and fully automated.
Digital onboarding powered by AI allows businesses from all sectors to confirm employees, customers, or suppliers accurately, to onboard them safely, and streamline the onboarding process to increase savings and increase efficiency.