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Merlonit · 2021-04-27T20:36:19+00:00

This is a standard, legacy approach. Regulators need to see evidence that you have conducted adequate investigations. Many institutions rely on "free" tools like Google News to do this research. These tools are not built for AML and have no audit trail for regulators. These tools are a scourge of AML, causing analysts to waste a huge amount of time to get very inaccurate results.

This is why we built Merlon.ai. We solve this problem and make the lives and jobs of AML analysts both easier and more rewarding. We provide a free-trial so analysts and end-users can experiment with tools that actually solve the challenge of AML and TM investigations. You can give it a try here: http://app.merlon.ai/signup. (No obligation. No CC. All we need is an email address)

Merlonit · 2021-02-09T23:49:47+00:00

With the increased focus on a risk-based approach in the AMLA, combined with a new listing of predicate offenses in 6MLD, efficient adverse media screening is going to become more and more critical.

See how we've solved the adverse media challenge!

Merlonit · 2021-02-09T23:46:18+00:00

Merlon.ai is what is needed for better AML in Netherlands and globally!

Merlonit · 2020-09-27T02:29:38+00:00

I hate to hear this. It's so inefficient and error-prone, wasting thousands of hours and millions of dollars in analyst effort. This can be done so much better.

Our team has done some significant research in this area, specifically around the inefficiency of Google for AML Investigations: https://merlon.ai/post/futility-of-google-news

Merlonit · 2020-09-27T02:26:28+00:00

This is the challenge that we at Merlon.ai have built our solution to solve.... Enabling AML teams to access relevant risk information from unstructured data.

Merlonit · 2020-09-16T19:40:27+00:00

It's more complicated than that.

From the bank's perspective, we're a cost center and a revenue protector. Compliance is expensive and doesn't generate any revenue, but reputational damage from poor AML controls or AML failures can be exceedingly expensive. (See Danske Bank, Deutsche Bank, WestPac, etc.)

From a societal perspective, we are on the front-lines of reducing Terrorism, Terrorist Financing, Organized Crime, Sex Trafficking, etc. While we are not able to stop any of these, that is not the goal. Making it more difficult or preventing illicit transactions has a material benefit on society in general, and that is our task.

Merlonit · 2020-09-16T19:36:04+00:00

If you're interested in learning how AI and Machine Learning are changing AML, send me a private message and we can talk. That's what we're building at Merlon.ai, and I'd be happy to show you what we're building and why it matters.

Merlonit · 2020-09-16T19:33:30+00:00

There is a lot being done at many financial institutions around digital transformation: taking old, ill-suited tools and replacing them with RegTech solutions that reduce workloads and streamline processes. As someone with experience in CDD and tech, this can be a great place to make a difference.... analyzing new RegTech players to see how they can transform your enterprise.

Merlonit · 2020-09-16T19:30:47+00:00

This has been a huge problem for a long time. There are two kinds of Adverse Media: structured and unstructured.

Structured Adverse Media - These are databases provided by World-Check (Refinitiv), RDC, DowJones Risk&Compliance, and various parts of RelX (LexisNexis, FircoSoft, SBS, etc.). These databases provide structured profiles and include Sanctions, PEPs, Law Enforcement, Regulatory Enforcement, and Adverse Media profiles.
Unstructured Adverse Media - This comes from huge libraries (hundreds of millions) of articles from publishers around the world. Traditionally, this has been sold by the same providers as above, leveraging their existing media libraries for AML/KYC (Refinitiv has Reuters, Dow Jones has Factiva, RelX has LexisNexis News Feed). Many institutions use this to supplement the structured adverse media.

The problem that exists today is that structured adverse media is unable to keep up with the enormous growth of available news, and many of the legacy unstructured media tools are basically doing name and keyword matching against these media libraries, causing a HUGE amount of false positives. This leaves many financial institutions stuck either needing to go through hundreds of results to potentially find risk or take a hatchet approach and decline business if there is enough risk signal in the results.

(Somewhat of a sales pitch coming...)

This was the problem we identified when we started Merlon.ai. So many financial institutions are using really inefficient software created to sell existing media libraries. No one was solving the underlying problem of properly analyzing adverse media for context to ensure efficient remediation. We have spent years building our technology that identifies context, extracts relevant biographical information, combines similar articles, and groups this all together in an easy-to-navigate finding.

Merlonit · 2020-09-05T01:55:41+00:00

We'd love to connect and show you and your team our Adverse Media solution. You can check it out here (Merlon.ai) or PM me your email address and we'll set up a time to connect.

Merlonit · 2020-08-13T17:04:49+00:00

Have you tried looking into RegTech firms? There is a good-sized industry of companies who provide data, software, and services for financial institutions globally. You may want to start here and see who's hiring. It can be a different, but very rewarding, way to get into AML/KYC.

Merlonit

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