It’s November 2024 and the current state of KYC compliance looks like this..
- 61% of compliance professionals report that excessive workloads are forcing them into reactive firefighting instead of proactive risk management, with 55% confessing they’ve rejected potential clients due to lack of risk visibility in a recent Dun & Bradstreet study, 2024.
- 50% of customers report abandoning an account-opening process due to poor onboarding. Meanwhile, a McKinsey study finds that a high customer experience translates to a %15% revenue increase and a 3% growth rate for firms.
- 75% of firms consider their level of KYC sophistication to be either ‘poor’ or ‘mediocre’ a 2024 Moody’s study finds.
All this to say that it’s almost 2025 and with so much talk around ground-breaking innovation and artificial intelligence (AI) we expected to have flying cars by now – but at the very least, if we can’t have flying cars, could we at least have futuristic processes?
How AI Can Elevate KYC Processes
When it comes to KYC, AI can support the automation of KYC data collection and verification, speeding up customer due diligence processes and increasing accuracy as manual interventions and human errors are reduced. It can be employed to identify transaction patterns, text in unstructured documents and match data points to wealth of data.
Specifically, for banking and financial services, AI can expedite account opening and loan applications by implementing task automations and AI-powered analytics into identity verification, creditworthiness checks and risk-scoring. These procedures are made much faster, while ensuring compliance with regulations, thus increasing revenue and promoting growth for financial institutions.
1. Alleviating Manual Workload to Promote Proactive Compliance Officers
61% of compliance professionals report that excessive workloads are forcing them into reactive firefighting instead of proactive risk management.
One of the greatest challenges faced by compliance professionals are false positives and the excessively manual labor that is needed to swift through the alerts. In a recent study by Dun & Bradstreet, 56% of compliance officers reported that an overload of false positives has occasionally forced them to reject customers due to time constraints; 55% have confessed to rejecting potential clients due to lack of risk visibility.
AI models are able to alleviate this burden by learning from past false positives. Over time, the number of unnecessary alerts are reduced and flagging only genuine threats, allowing human compliance officers to focus where necessary and ensuring that customers are not unnecessarily rejected.
Besides creating operational efficiencies through automation of repetitive tasks, such as data entry and ID verification, saving resources, AI can also effectively increase risk visibility. For example, dynamic risk profiling leverages AI to analyze diverse customer attributes, such as transaction history, geographic location, profession and income, to assign a risk score. The customer profile is then continuously updated based on new information and transaction patterns, and automatically checked against new or updated lists, reducing false positives and ensuring risk-accuracy.
High-risk customers are flagged for further investigation and low-risk customers are swiftly onboarded.
2. Improving Customer Experience for Increased Revenues
50% of customers report abandoning an account-opening process due to poor onboarding. Meanwhile, a McKinsey study finds that a high customer experience translates to a %15% revenue increase and a 3% growth rate for firms.
Considering the potential for revenue growth, improving customer onboarding should be a high priority. Firms can leverage AI tools for increased automation in identity verification, data prepopulation and database cross-checking, thereby creating a faster onboarding process and improving customer satisfaction.
Additionally, AI offers opportunities for greater personalization in a variety of different ways:
- For the customer, AI can offer personalized guidance to assist the customer while they go through the onboarding process, to ensure that any queries that may arise are overcome to achieve successful onboarding, reducing drop-offs;
- Dynamic workflows that adapt to the customers responses and data input further reduce the time spent on onboarding and ensure that no excess data is collected, thus respecting data protection and privacy regulations;
- AI can contribute to tailored risk assessments based on customer behavior and profile, reducing unnecessary intrusive checks for low-risk customers and resulting in greater operational efficiency for financial institutions.
3. Integrating AI for Greater KYC Sophistication
75% of firms rate their level of KYC sophistication as ‘poor’ or ‘mediocre’, a recent Moody’s study finds, which asked executives to evaluate their KYC digitization on a 10-point scale – 1 being manual and paper-based, and 10 being automated and digital.
Traditional banks make up the majority of those evaluating their digital transformation journeys as ‘poor’. These institutions are burdened with manual processes, paperwork and fragmented legacy systems. Moreover, their teams suffer as senior management is often hesitant to believe that digital change can improve the KYC challenges they face.
This is a stark difference from firms, predominantly FinTechs, that report greater levels of KYC sophistication. These companies adopt a different mindset, harnessing a strong belief that KYC can help them to differentiate. Τhey have integrated IT systems, connecting KYC processes with client lifecycle tools to create a unified customer view.
In traditional banking especially, the lack of IT integration translates into data fragmentation, resulting in repeated data or document requests, unnecessarily pestering customers and driving up costs.
Therefore, one of the simplest but most game-changing AI implementations in KYC processes has to do with data accuracy and consistency, or otherwise the maintenance of good data quality.
AI can be utilized during onboarding for data extraction where Optical Character Recognition (OCR) technology is used:
- to automatically extract text from documents to prepopulate datafields, thus avoiding human error from manual entry;
- to automatically cross-corroborate against names, addresses, and other submitted information, lists or databases.
AI identifies inconsistencies and errors in data, ensuring KYC customer files are kept up-to-date, flagging genuine threats, and minimizing the potential of fines for non-compliance.
Sancus AI modules
At norbloc we have been closely following developments in the AI space and how these are relevant to our platforms. One can get carried away with the different features that recent advances in this space are making possible so we tested our own ideas with our Clients and Advisors. The resulting AI functionalities that made it through endless review sessions are currently being implemented and are to be launched in the following months within our KYC orchestration solution, Sancus.
Data Extraction from unstructured official documents
If we had a penny for every time a client mentioned the need for advanced text extraction and cross referencing, we would not need to charge for our platforms!
For the customer, data extraction is a functionality capable of improving customer experience by boosting the pre-population of data fields as the customer glides through the onboarding journey, or even during remediation.
For the compliance officer, leveraging machine learning to extract data from documents is at the center of reviewing signatory powers assigned to individuals in companies as well as Directorship awards. Reviewing compliance officers will not have to go through endless documents to extract and cross reference data. Reducing issues surrounding poor data quality and inaccuracies, which account for up to 26% of operational costs according to a McKinsey study, will not only lower operational expenditure but also compliance pitfalls.
Our platform Sancus will offer these functionalities in Q1 next year for a number of documents and data points that we have prioritized together with our clients, allowing automated complex data extraction and cross referencing.
Automating compliance manuals
Since we won’t be seeing flying vehicles in 2025, at least we get to have a co-pilot. The compliance officer AI-powered co-pilot is a module that will offer a number of functionalities in two phases
Phase 1 (Q1 2025): Creating compliance manuals…
At the center of our onboarding orchestrator Sancus is a powerful workflow engine that allows for zero-code user journey creation. While these user journeys cover the customer journey, they also include the steps of checks that happen in the background or by the compliance officer as well as the data collected at each step and its mapping on the company risk matrix.
Compliance officers are very eager to edit user journeys without IT department support but also less eager to spend time revising the Standard Operating Procedures and Compliance manuals of their organization. Hence, we are creating a module that will provide a text description of a user flow designed in our workflow editor so that it can be used to automatically update compliance guidelines of our clients.
Phase 2 (Q2 2025) 2: For the Compliance Professional…
For the compliance professional, the co-pilot is a useful companion that assists in the creation of optimized KYC workflows, taking into account the risk appetite of the firm, the jurisdiction, source of funds and the financial solutions concerned. The guidance will be centered around selecting the right sequence of steps for the customer, completeness around foreground and background checks and alignment of reviews to the company’s risk scoring matrix
So, is AI that relevant to KYC? Yes…
The integration of AI into KYC processes is redefining how financial institutions approach compliance, efficiency, and customer experience. With capabilities like automated data collection, verification, and dynamic risk profiling, AI is reducing the human errors and excessive manual workload that hinder compliance professionals. These tools are enabling a shift from reactive problem-solving to proactive risk management. By streamlining onboarding, enhancing risk visibility, and minimizing false positives, AI supports compliance teams in making better decisions while reducing operational inefficiencies. The result? Updated customer profiles, faster processes, and more accurate risk assessments.
On the customer side, AI is helping to address a critical pain point: time consuming and endless onboarding processes. By offering faster, more personalized, and seamless experiences, AI is significantly improving customer satisfaction and reducing drop-offs during account openings. Tools like norbloc’s Sancus platform exemplify how advanced functionalities, such as document data extraction and automated compliance manuals, are not only reducing operational costs but also enhancing sophistication in KYC processes.
These developments are creating opportunities for financial institutions to differentiate themselves, combining regulatory compliance with superior customer experiences. AI isn’t just a futuristic ideal—it’s an essential element in reshaping KYC for a more efficient and customer-focused future.
