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The Fenergo Document Agent is an AI-powered, SaaS-native solution that transforms how financial institutions process, validate, and manage client documentation across onboarding, KYC, and compliance workflows. Traditional document handling is slow, manual, and prone to human error, especially when dealing with multi-document uploads, unstructured formats, or repeated requests for missing information. The Document Agent resolves these challenges by automating document splitting, classification, data extraction, related-party ingestion, requirement mapping, and task completion, enabling faster, more accurate document handling at scale. The solution identifies and separates multiple documents within a single file, classifies each document based on content, and links it directly to the correct requirement. It extracts regulatory, entity-specific, and product-specific data, maps relationships found in trust and corporate structures, flags conflicting values, and offers intuitive controls fo

As financial institutions prepare for a new year of regulatory evolution, the need for proactive compliance strategies is growing. Fenergo’s Regulatory Horizon Scanning 2026 webinar brought together leaders from Fenergo and PwC to discuss the key regulatory changes to be aware of and the crucial steps organizations must take to future-proof their operations. This year’s conversation centered on the most significant trends expected to influence operations in 2026, including sanctions evolution, AI governance and regulatory harmonization.  North America: Legacy Regulation and New Approaches  The discussion opened with a deep dive into the North American regulatory environment. The panel reflected on the symbolic milestone of 55 years since the U.S. Bank Secrecy Act (BSA) came into force. Despite the Act’s long-standing role, the current regulatory climate signals towards de-regulation. The speakers explored why this shift is emerging now and what risks and opportunities it presents for r

In the ever-evolving world of financial crime compliance, staying ahead of technology trends is no longer a nice-to-have, it’s a necessity. The recent webinar by Fenergo, we revealed the results of our 2025 FinCrime Operations Benchmark survey by Fenergo offered a high-impact overview of how leading financial institutions are adapting to new operational pressures, technology imperatives and cost constraints. Drawing on data from our annual survey of senior decision makers in operations, compliance and technology roles at global banks, asset managers and asset servicers, the session unpacked the status quo of mid-office transformation and where firms must focus next to increase efficiencies, reduce risk and drive growth.  A Snapshot of Operational Realities Financial crime operations remain costly and complex, with many firms still dealing with slow, inefficient onboarding, outdated systems, fragmented data and manual KYC reviews. These challenges have real consequences: 70% of firms lo

The Fenergo FinCrime Operating System (FinCrime OS) is presented as a unified, AI-powered platform designed to modernize how financial institutions detect, prevent, and manage financial crime across the full client lifecycle. The brochure opens by highlighting key industry challenges: increasing compliance costs, rising alert volumes, fragmented data sources, and the operational strain caused by manual or “swivel-chair” processes. Compounding these obstacles is an increasingly complex global regulatory landscape, where the demand for speed, accuracy, and strong risk controls continues to grow. FinCrime OS extends Fenergo’s established Client Lifecycle Management capabilities into an intelligent, modular ecosystem that centralizes all financial-crime-related events, decisions, and insights into a single platform and system of record. Its architecture hinges on a personalized Command Centre (a daily landing page) offering unified visibility over onboarding, KYC, screening, monitoring, an

​Summary / Context Data migration and remediation are critical steps in transitioning to Fenergo. This article provides an overview of a structured approach to migrating data from existing systems, including key entities, documents, related parties, reference data, and other critical domain data.  The article examines leveraging different remediation approaches depending on volume, impact, and complexity. It also incorporates guidance on selecting the appropriate migration tools or methods (Manual UI, Bulk Load, Custom APIs/Ingress, ETL) based on volume, complexity, and operational requirements to ensure successful migration and minimal disruption.Common Challenge or Scenario Many institutions face challenges in migrating large data and documents from existing systems to Fenergo.   Typical issues include duplicate records, incomplete datasets, misaligned entity mappings, missing documents, unclassified documents, incorrect related party relationships, and inconsistent reference data.  

The Fenergo AI Governance Whitepaper presents Fenergo’s structured approach to ensuring trustworthy, transparent, and compliant use of AI across its SaaS platform. Executive Summary: Fenergo emphasizes the importance of trustworthy AI built on transparency, accountability, and ethical safeguards. Its SaaS AI Control Framework translates these principles into operational requirements that help clients deploy AI capabilities confidently Regulatory Landscape: The framework aligns with global standards including: EU AI Act – covering system classification, conformity assessments, and post-market monitoring. U.S. NIST AI Risk Management Framework and Executive Orders on trustworthy AI. UK’s principles-based framework emphasizing transparency, fairness, and accountability. Singapore’s FEAT principles and related MAS, PDPC, and IMDA guidance. Hong Kong’s OGCIO and PCPD guidelines on ethical AI and privacy compliance SaaS AI Control Framework: Over 30 controls addre

The Fenergo Screening Agent is an intelligent, autonomous capability that modernizes how financial institutions manage entity screening by automating match resolution, improving decision accuracy, and ensuring full audit transparency. Traditional screening processes are often slow, inconsistent, and heavily dependent on manual review. The Screening Agent addresses these challenges by applying advanced decision rules that process third-party provider results in real time, automatically resolving false positives and confirming true matches where appropriate. Any hits requiring additional attention remain open for analysts, enabling efficient triage without compromising oversight or governance. The Screening Agent evaluates match summaries using structured decision logic, drawing on detailed entity information such as identifiers, addresses, aliases, related parties, and contextual data. Each automated or manual decision is supported by a clear, explainable rationale recorded directly wit

Fenergo Transaction Monitoring – Real-Time Detection of Risk, Smarter Investigations, Enhanced EfficiencyThe financial services industry faces mounting challenges as the explosion of digital payments fuels a parallel rise in financial crime. Despite greater compliance spending and stricter regulations, such as successive AML Directives and PSD2/PSD3 within the EU, many institutions still rely on siloed and outdated transaction monitoring tools. These legacy systems struggle to detect complex money-laundering patterns, often generating excessive false positives that overburden compliance teams.Fenergo Transaction Monitoring provides a next-generation solution designed to accurately detect suspicious activities in real-time, while dramatically reducing false positives. Built as a SaaS, multi-tenant, API-first platform, it offers high scalability and performance even under heavy transaction volumes. The solution integrates KYC and transaction data to form a unified, 360° client view—enabl

Summary: Agentic KYC – Clearing the Periodic Review Backlog and Maintaining ControlFenergo’s Agentic KYC introduces a transformative, intelligent, and proactive approach to periodic KYC (Know Your Customer) reviews, addressing inefficiencies caused by traditional, manual, and fragmented processes. As financial institutions face increasing regulatory scrutiny and client expectations for faster onboarding, Fenergo’s solution integrates automation, data orchestration, and embedded risk intelligence to deliver continuous compliance and agility.The legacy challenge lies in outdated methods driven by static schedules, data silos, and manual reviews that create delays, backlogs, and rising compliance costs. In contrast, Agentic KYC leverages intelligent agents that automate every stage of the review lifecycle—from profile data retrieval and validation to screening, risk assessment, and case completion—while providing full oversight through Fenergo’s Review Manager and Command Centre.Fenergo’s

IntroductionA huge part of implementing any process orientated platform, is designing the conditional logic which gets applied at programatic junctions. This is responsible for directing and controlling the flow of logic in an application, reacting dynamically to user or API interactions. The most effective way to implement such requirements is to employ a "Rules Engine" that can apply that conditionality in a standard, reusable way.Business Rules as they apply to an evolving regulatory landscape, introduce a lot of diversity. In short, rules will change frequently and rapidly. Our goal was to make our implementation flexible and customizable, allowing the end-user to set rules without the need for any code modification or deployments, whilst we also wanted to ensure the performance met the SLA commitments we adhere to for clients. The rules engine in our SaaS application is designed to meet numerous functional use cases across the platform, from controlling the visibility of data fiel

IntroductionDeploying code to production automatically, often, and quickly is a principle we follow for our Fenergo SaaS CLM Platform. It brings with it many benefits, but also demands that a certain set of standards are followed to ensure it is done successfully.Continuously Deploying for Continuous ValueThe reason we deploy to our production environments often is to release value (via enhancements and new features) to our customers as soon as it becomes ready. The architectural decisions we made around how our platform is implemented, facilitate the release of independent autonomous enhancements to parts of the application instead of broad holistic full release. The larger the release, with a high volume of updates, require longer delivery cycle which package multiple changes. Clients get no value from a feature until it is first available, and then actively being used by them, and there is no opportunity for iterative improvements which come from making tighter, smaller, incremental

The ChallengeHow can you tell when you've shipped production code? Some like dashboards, some check release notes, others still prefer to subscribe to alerts. All three groups look to me in confusion when I say you can do it with baked goods.HistoricallyBack in 2017, when I joined Fenergo, we were averaging three releases of our core product a year. Each new version was a struggle through merge conflicts and manual testing: time consuming events that added little in the way of client value. Success called for a celebration, and those celebrations often involved donuts. If all other markers of a new version passed a member of staff by we could depend on the presence of confectionary to alert them to the change.We were aware that infrequent releases are an antipattern. I've heard it said here that releases are like flossing: do it daily and it's pain free, do it every couple of months and it's unpleasant.We've learned from those times. We've improved, and these days we're making producti

IntroductionSaaS Solution providers can live or die on the basis of availability. There is a massive shift of responsibility to the vendor, who must ensure that users along with their data are protected and safe (a massive and separate topic) but that the solution is available when the clients want to use it.This is no different to browsing Netflix only to be told "Sorry were having some technical difficulties at the moment" or "There are too many people watching that Movie right now". A SaaS product from a Fintech such as Fenergo might seem a million miles from a streaming service, but there is commonality in the target outcomes.If your platform suffers from availability issues, you will loose customers, breach SLAs and invalidate contracts. Your business will not last. The acceptable tolerance threshold for downtime is so low in our industry that meeting availability targets is only one aspect, vendors need to prove empirically that the strategy to assure availability is consistent w

IntroductionDynamoDB is the most popular NoSql database on AWS. It allows you to easily build highly performant applications, taking care of the good practices, such as: encryption, access control, high-availability, backups, etc.DynamoDB allows you to configure two types of capacity allocation: provisioned and on-demand, and it defines the capacity with read capacity units (RCU) and write capacity units (WCU). One RCU is one strongly consistent read or two eventually consistent reads for a data block of up to 4 KB. On the other hand, one WCU represents write request for a data block of up to 1 KB.When it comes to pricing, it is important to understand these two modes and pick the one that fits better for each case, so we can have tables that auto-scale without over-provisioning.In this post, we will see a real case, where picking the right mode helped to drastically reduce the cost of using DynamoDB.Provisioned modeWith provisioned capacity, you can configure the maximum RCU ans WCU o

IntroductionA discussion which comes up often with our clients is that of Single vs Multi Cloud Strategy. Its an interesting topic to dig into and whilst benefits are evident for both approaches, it largely depends on the perspective you are coming from.Lets do the TL;DR - Fenergo as a SaaS Vendor align firmly with the Single Cloud approach, partnering with AWS works exceptionally well from our perspective based on the type of software we create and in this post I'll look at why that is the case and also why some IT Professionals might favour a Multi-Cloud strategy.A Cloud is a Cloud is a Cloud - Except when it isn’tThe terms "Cloud Adoption, Cloud Migration, Cloud Deployments, Cloud Provisioning" have so much crossover that they can almost be used interchangeably. Consider a software product or technical platform that previously lived on infrastructure you own (or a private data centre you manage) and the simple objective is to have that asset provisioned from a cloud platform. In thi

IntroductionEventStoreDB (ESDB) is a log stream database oriented to architectures based on event-sourcing. The data in EventStoreDB is stored into streams, and each stream contains a log of events. For this reason, ESDB is a very suitable candidate for working with event-sourcing architectures and it allows us to easily implement the CQRS pattern, where there are projections that transform the events produced by the commands into data that can be consumed by the queries.In EventStoreDB, there are three types of nodes: Leader, Follower and ReadOnly. The Leader node is the node where we write or read data and there can be only one Leader in the cluster. Follower nodes replicate the changes from the Leader node and they are not directly used for writing or reading data. However, if the Leader node is down, one Follower can be re-elected as the new Leader. For high-availability, it is recommended to have at least three nodes in three different availability zones (one leader and two follow

IntroductionThe WebSocket API is an advanced technology that makes it possible to open a two-way interactive communication session between the user’s browser and a server. With this API, you can send messages to a server and receive event-driven responses without having to poll the server for a reply.We normally use WebSockets when we want to get live updates of a particular object without having to constantly poll for new updates. In this scenario, WebSockets can be helpful as they reduce the required number of API calls and in turn the cost of our infrastructure, and if the number of request is very high, the API might apply throttling.In this article, we will review how we could use WebSockets for EverntSourcing+CQRS. You can follow the same approach for other architectures where you need to notify the clients when changes happen in a certain dataset.ArchitectureIn Fenergo we are using EventSourcing and CQRS primarily. We have commands which issue events that are then projected into

IntroductionWhen we created our SaaS solution, we needed to design an approach for the migration of data which both complements the technology and meets the requirements of our consumers. The approach challenges the norms of traditional data migrations because a SaaS platform serves multiple tenants concurrently. The software is continuously in-flight with 99.9% uptime availability, no one tenant can impede that performance and availability of another. To understand how we achieved this, we need to look at what norms do not translate to SaaS, why they do not translate and what is the right approach for loading data to a highly available, multi-tenanted software product?Data Migration ConstantsBefore we examine differences which should be acknowledged, it can be agreed that the end goal is the same for getting data onto a SaaS Platform as it is for a more traditional system.Load Data : Get data from an existing source and load it into a new platform. Align to a Target Structure / Format

IntroductionHello Everyone, As we continue to push the boundaries of innovation in the financial services industry, it's crucial that we address the compliance challenges that come with adopting cutting-edge technologies like artificial intelligence (AI). At Fenergo, we understand the importance of leveraging the power of AI while ensuring the highest standards of data privacy, information security, ethics, intellectual property protection and regulatory compliance. Today, I want to share with you our robust AI compliance framework, designed as a collaborative effort by our Fen-X Engineering and Privacy & Risk team, aimed at proactively mitigating risks associated with AI adoption in our services. The AI Compliance framework provides a standard set of criteria that are embedded in the development of all AI features by default, as well as thorough assessments being completed by the Privacy & Risk team before launch.Safeguarding Intellectual Property RightsAt Fenergo, safeguardin

IntroductionHi everyone, last week we wrapped up another fantastic Client Council where I had the chance to engage with many of our clients across a variety of topics, with one consistent topic being the methods of creating and updating Entities at scale in Fenergo and which method is best suited for particular scenarios.With that in mind, I wanted to write a small blog on how best to load Entity information into a Fenergo tenant, depending on the scenario a user might be dealing with.There a few different ways to create and update Entities within a Fenergo tenant which are:Manual Entry Bulk Upload Data Migration ETL API IntegrationsBelow, I will map out each method and what scenarios it caters for with the hope of providing more insight to users as to which method to use when they are dealing with creating or updating Entities at scale.Summary Comparison TableKey Differences Detailed Method BreakdownsIn this section, I will breakdown each method that Fenergo provide for loading Entity

Over the past year as a SaaS developer at Fenergo, I've been focused on the challenge of hosting a third-party SDK inside our AWS ecosystem. My goal was to ensure the service could run in a way that scales reliably, integrates cleanly with our existing infrastructure.To achieve this, I used Pulumi to streamline Infrastructure as Code, which made it easier to model, manage, and iterate on cloud resources as the project evolved. Wherever possible, I leveraged existing infrastructure components - such as our VPC, subnets, and security groups - instead of duplicating effort. For new requirements, I identified and provisioned the most appropriate AWS services that fit our needs, balancing performance, cost efficiency, and maintainability.A key part of the solution was building and automating CI/CD pipelines, which allowed us to provision infrastructure, deploy updates, and run validations in a consistent and repeatable way. This gave the team confidence to roll out changes quickly while kee