KYC Solutions
AI-powered KYC solutions streamline KYC procedures while improving name-match rates and reducing the need for manual investigation.
Are you looking for easy AML and KYC solutions?
We have bad news for you: There are none. In financial institutions and the fintechs that serve them, complex verification-and-review processes merge with evolving anti-money laundering mandates to create challenging know your customer (KYC) environments. That won’t change. However, AI-powered identity risk intelligence solutions can help streamline KYC procedures while significantly improving name-match rates and dramatically reducing the need for manual investigation.
The importance of KYC
The United Nations estimates that criminals worldwide launder between $800 billion and $2 trillion each year, representing anywhere from 2% to 5% of the world economy.[1] The money both stems from and funds heinous crimes. These include terrorism, human trafficking, weapons trafficking, the drug trade, and the creation and distribution of child sexual abuse materials. Legislators worldwide believe that when the flow of money stops, instances of these crimes plummet. That’s why most nations have implemented stringent anti-money laundering laws.
To comply with these laws, financial institutions and fintechs must meet demanding KYC requirements — mandatory processes for verifying a customer’s identity at account opening and periodically thereafter. These requirements aim to reduce crime, ensure transparency, and safeguard the integrity of the financial system.
KYC/AML processes consist of:
- Customer identification — Financial institutions (FIs) verify and identify customers using documents such as passports, national IDs, drivers’ licenses, or other government-issued identification.
- Risk assessment — FIs use various risk assessment tools and processes to evaluate and manage the risks posed by a customer, potential customer, or transaction.
- Enhanced due diligence — Banks apply a higher level of scrutiny (called “enhanced due diligence”) to high-risk prospects, customers, and transactions.
- Ongoing monitoring — To comply with AML laws, FIs periodically monitor customer accounts.
- Record keeping — Know your customer bank requirements demand that FIs maintain comprehensive records of customer identification, transactions, and any communications related to KYC checks.
- Updating KYC compliance efforts — Banks need to understand evolving AML measures and adapt their KYC procedures accordingly.
Coping with evolving mandates
The need to stay abreast of evolving AML mandates makes KYC processes challenging.
Currently in the United States, the Financial Crimes Enforcement Network (FinCEN) and other banking agencies have proposed modernizing AML/countering the financing of terrorism (CFT) requirements. The proposal would necessitate strengthening AML programs across financial institutions subject to the Bank Secrecy Act.[2] In 2024, the European Union adopted a comprehensive legislative package to strengthen AML/CFT rules across member states. This package, which replaces a previous patchwork of county-by-county directives, strengthens AML requirements by establishing new rules for enhanced customer due diligence.[3]
These are just two examples of an AML regulation cycle that shows no sign of easing. Legislators write new mandates to align with evolving money laundering techniques. No matter how hard FIs work to meet AML mandates, they are caught in a vicious cycle of new crimes begetting new laws leading to ever-more-demanding KYC requirements.
The situation challenges FIs. But AI-powered identity risk intelligence can help FIs not only more easily meet AML mandates but improve business.
The KYC challenge
The problem: Despite rapidly increasing adoption of AI for compliance processes, many banks have yet to deploy the right type of identity intelligence solution for KYC. Instead, these financial institutions typically rely on rules-based processes. These processes are time-consuming, error-prone, and require significant manual intervention.
In rules-based KYC processes, an AML specialist compiles and codifies a set of conditions that, if met by a particular transaction, cause the system to alert an investigator to potential money laundering. Transactional dollar limits are a classic example of this: AML systems note all transfers over a given amount, then alert an investigator to follow up. While a small fraction of these alerts may indicate criminal activity, by many estimates up to 95 percent of the millions of alerts sounded in financial institutions annually are false positives.[4] These false positives make AML detection vastly more expensive and time consuming than it needs to be: human investigators must review each alert.
Learn the basics
eBook
The Complete Guide to Name Matching
The concepts around name matching, including what it is, how it’s used, and why standard search is inadequate when it comes to names.
eBook
Matching Software Surmounts Four Major AML/KYC Challenges
Babel Street helps FIs improve AML/KYC by more quickly analyzing, matching, and scoring the names of individuals and corporations.
eBook
AI Helps Financial Institutions Comply with Emerging Regulations
Current perspectives on regulations and the value that AI delivers to the financial sector for AML/KYC compliance.
Data Sheet
AI Solutions for Transforming Financial Compliance
How the AI-powered name matching capabilities of Babel Street help financial institutions comply with AML/KYC regulations.
AI-powered solutions improve KYC
Identity risk solutions can help institutions combat threats and improve compliance. Their multilingual name matching, entity resolution, and relationship-discovering capabilities can rapidly identify people, companies, and organizations — then map connections among them. From state and federal IDs to legal documents to customer emails, the best of these solutions scour structured and unstructured data in a broad array of languages; create reports; generate detailed relationship visualizations; and tell you how confident they feel in the matches made. In doing so, identity risk intelligence systems slash KYC costs, while dramatically reducing the chance of FIs running afoul of AML laws and incurring associated fines.
Business benefits
While FIs typically deploy identity risk intelligence solutions to meet AML mandates, these same solutions can be used to improve business.
First, these solutions improve fraud detection. Fraud is a complex crime with a direct impact on an FI’s bottom line. Financial institutions need every technological resource available to fight it.
Identity solutions are powered by artificial intelligence — and AI excels at pattern recognition. This capability is particularly valuable in fraud detection. In fact, AI can identify fraud patterns human analysts would not have found on their own.
Second, identity intelligence solutions can improve the customer experience. Stringent customer due diligence processes may leave prospects and customers frustrated by the amount of time it takes to open a new account or receive funds. Rather than waiting, these customers may choose to open an account at a different, faster FI. By hastening onboarding, funds transfers, and other services, AI-powered systems help keep customers happy.
Consider the following scenario
Consider the following scenario. A large fintech company offers consumers full-service accounts for spending and savings. These accounts provide customers with reloadable cards that enable them to easily pay bills and receive funds — including payroll direct deposits. But name matching proves a challenge. Sometimes, a customer name on record at the fintech varies slightly from payee names. The system cannot recognize that its customer “Rebecca Hockenbury” is the same person as the payee named “Rebecca Haukenbury,” “Becky Hockenbury” or “Hockenbury, Rebecca.” As a result, each of these payee names must be manually investigated and matched to the Rebecca Hockenbury on record. This process dramatically increases the amount of time it takes for Ms. Hockenbury to access her funds, and she leaves this fintech for a speedier FI.
An AI identity intelligence solution would improve the banking experience for this customer, since it considers degrees of truth when making determinations. When used in name matching, AI can identify similar names and rank the likelihood of these names referring to the same person — bypassing the need for human investigation.
Financial institutions can also improve the customer experience by using a risk intelligence platform to develop a single view of individual customers, then targeting products and services to meet those customers’ specific needs. This process improves customer acquisition and retention efforts.
Why Babel Street?
Delivering mission-grade risk intelligence quickly and at scale, Babel Street sets a new standard for AML compliance. Our Risk Intelligence Platform provides all the capabilities discussed above. We also offer:
Conclusion on KYC Solutions
Too many existing KYC systems inadequately address pressing needs for fast, automated, name matching and entity resolution. They are slow, unsuited to the examination of massive data sets, and prone to human error. The Babel Street Risk Intelligence Platform helps FIs better comply with AML mandates while improving business.
We provide the name-matching and entity resolution capabilities needed to meet stringent AML requirements and improve business by:
- Streamlining onboarding, verification, and screening processes
- Reducing instances of false positive matches by up to 90% while concurrently missing fewer matches — thereby reducing investigative time
- Obtaining a single view of each customer to both better comply with AML mandates and improve sales and marketing efforts.
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KYC Platform FAQs
KYC, or Know Your Customer, is a process used by businesses, especially financial institutions, to verify the identity of their clients. This process involves collecting and analyzing information such as identification documents, proof of address, and financial history. KYC is crucial for preventing fraud, money laundering, and other illegal activities. By ensuring that customers are who they claim to be, businesses can protect themselves from financial and reputational risks, comply with regulatory requirements, and foster trust with their clients.
Endnotes
1. United Nations, “Money Laundering Overview,” 2022, https://www.unodc.org/unodc/en/money-laundering/overview.html
2. Congress.Gov, “S.2669 — Digital Asset Anti-Money Laundering Act of 2023,” 2023, https://www.congress.gov/bill/118th-congress/senate-bill/2669/text#:~:text=Introduced%20in%20Senate%20(07%2F27%2F2023)&text=To%20require%20the%20Financial%20Crimes,assets%2C%20and%20for%20other%20purposes.&text=A%20BILL-,To%20require%20the%20Financial%20Crimes%20Enforcement%20Network%20to%20issue%20guidance,assets%2C%20and%20for%20other%20purposes
3. World Economic Forum, “Forging New Pathways: The Next Evolution of Innovation in Financial Services,” 2020, https://www3.weforum.org/docs/WEF_Forging_New_Pathways_2020.pdf
4. Deloitte, “Why artificial intelligence is a game changer for risk management,” 2016, https://www2.deloitte.com/content/dam/Deloitte/us/Documents/audit/us-ai-risk-powers-performance.pdf
5. Basis Technology, “What Can AI Do for Risk Technology Today?” 2018, https://www.basistech.com/honest-ai/what-can-ai-do-for-risk/
6. Financial Action Task Force, “The FATF Recommendations,” February, 2023, https://www.fatf-gafi.org/en/publications/Fatfrecommendations/Fatf-recommendations.html
7. Directive (EU) 2015/849 of The European Parliament and of the Council of The European Union. May 20, 2015. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32015L0849&rid=2
8. Finance Crimes Enforcement Network, “Joint Statement on the Risk-Based Approach to Assessing Customer Relationships and Conducting Customer Due Diligence,” July 6, 2022, https://www.fincen.gov/sites/default/files/2022-07/Joint%20Statement%20on%20the%20Risk%20Based%20Approach%20to%20Assessing%20Customer%20Relationships%20and%20Conducting%20CDD%20FINAL.pdf.
Disclaimer
All names, companies, and incidents portrayed in this document are fictitious. No identification with actual persons (living or deceased), places, companies, and products are intended or should be inferred.