employee using an AML Lending and Financing Software Solution

AML Compliance for
Lending and Financing

Simple. Fast. Easy.

Whether you are a lender, a mortgage broker, or providing financing to businesses, you are expected to maintain the same commitments to AML compliance as other financial institutions. But AML is likely only one of many compliance responsibilities you have right now. So how do you meet your AML obligations and still provide an exceptional customer experience?

 

The right AML solution should make your life easier.

 

Alessa’s powerful, integrated platform is designed make it easy for you to take a risk-based approach to AML compliance. From providing a daily report of your riskiest clients, to automating many of the tasks and workflows to help complete investigations and reporting, Alessa can make AML compliance the easiest part of your day.

Why Compliance Professionals Prefer Alessa

One Integrated Platform

A complete AML compliance program on one integrated platform, Alessa provides you with seamless compliance functionality – from the first red flag to the final regulatory report.

Get a Daily Update of Client Risk

Alessa provides you with a comprehensive update on client risk, highlighting the customer whose risk scores have surpassed your establishment’s risk threshold in the last 24 hours.

A 360° View of Each Client

Alessa 360 provides a complete view of client information and activities, making suspicious activity easier to investigate and resolve.

Expedited Results Through Automation

We've streamlined and automated many of the time-consuming AML tasks, making it easier and more efficient for you detect, investigate and report suspicious activity.

Meets Unique Needs

Alessa has developed a unique AML platform to help simplify compliance specifically for mortgage and lending companies.

Alessa’s Integrated AML Platform for Lending and Finance Offers You

Easier Due Diligence

Client onboarding with Alessa allows you to verify identities and search sanctions, PEPs, OFAC, and proprietary lists in real-time. Once onboarded, you’ll have tools to better understand the nature and purpose of client relationships for enhanced anomaly detection.

Avoid Risky Clients With Sanctions Screening

Using sanction, OFAC, law enforcement, PEPs, adverse media, and internal high-risk lists, Alessa highlights the potential risk associated with a client during onboarding. Screening can be done in real-time, periodically or on-demand.

Detect Suspicious Patterns With Transaction Monitoring

Alessa analyzes all of your transactions in real time using an extensive library of analytics and generates alerts for suspicious activities. These alerts are sent to the appropriate personnel via text or email for investigation and/or reporting.

Risk Scoring You Control

Using data from various sources, Alessa allows you to develop a risk scoring model that matches your establishment’s risk tolerance so you can easily assess of the risks of doing business with an individual or business. Alessa also reviews an organization’s customer base and updates their risk level based on their activity and third-party data.

Simplify Investigations With Automated Workflows

Configured for your organization needs, Alessa’s automated workflows make it faster and easier to investigate, escalate and resolve suspicious activity alerts.

Automate Regulatory Reporting

With Alessa, your regulatory reports (CTRs, SARs, LCTRs and STRs) can be auto-populated, validated, and electronically submitted across multiple jurisdictions.

Schedule a
Free Demo

Learn how Alessa can simplify your compliance processes and make AML the easiest part of your day.

 

Book your complimentary demo of our AML Lending and Financing Software Solution today.

Latest Insights

OFAC sanctions lists being used for AML compliance

An Overview of OFAC Sanctions Lists

An overview of the key OFAC sanctions lists, including the SDN, NS-MBS, and SSI lists, and learn how to overcome common OFAC sanctions screening challenges.

Please fill out the form to access the webinar: