Compliance teams are under increasing pressure, managing continuous regulatory changes, fragmented data sources, and limited visibility into trading activities. They are swamped with false positives, stuck with rigid tools, and often waiting on IT just to tweak an alert or chase down a trade.
In this blog, Vivek Pathak, COO, BroadPeak, breaks down why most surveillance solutions miss the mark, and what firms really need to stay sharp, agile, and in control.
Managing global operations, regulatory compliance, and solution transitions without overloading IT is a challenge. How does BroadPeak streamline these processes?
BroadPeak is intuitive, flexible, and globally scalable which means it not only adapts to your existing infrastructure but allows your teams to manage change themselves.
First off, most of our clients go for a hybrid model. We handle the heavy lifting while your teams gradually learn the solution. The UI is so simple that even someone with no technical background can use it. You’ve got the raw source message on the left and a clean, normalized version on the right, mapped to your internal standards. So when someone from audit, legal, or compliance asks about a trade, you just enter the trade ID and there it is. No more chasing down people or spreadsheets. That responsiveness gives you a serious competitive edge.
Regulators appreciate this transparency too. I meet regularly with enforcement teams, and they’re candid. They want firms to succeed and are supportive of tools that help you do the right thing more easily.
Now, if you’re operating globally, say in London, Singapore, the U.S., and Europe, BroadPeak’s architecture is built for that. We tag every legal entity and bring it into the solution. We’ve integrated with exchanges and clearing firms around the world, and if there’s something new, we can add it. We also handle multi-jurisdictional requirements like position limits and reporting obligations. If you’re transitioning from one vendor to another, no problem, we can switch data sources mid-flight with no downtime.
We’ve also eliminated a lot of the typical IT bottlenecks. For example, if a new group starts trading under a different firm ID, you can simply update it in the UI. No code, no dev cycles. You can also onboard new asset classes or products with just a few clicks. As long as it’s in the risk solution, it’ll flow. Your BAs can do the mapping and push it downstream to surveillance, your risk solution, or wherever it needs to go.
When regulatory rules change, like with the CFTC rewrite, our clients were able to make the adjustments in a few hours. For most firms, that would be a month-long project. The difference? Good tooling. If someone wants to add a field or change a report, it shouldn’t require rewriting a bunch of code or a full-blown IT project.
You can even reroute historical data to a new solution with ease. Want to test out a new vendor? Take six months of existing data, point it to the new endpoint, and go. Your team is in control. This isn’t just more efficient, it’s a fundamental shift in how firms manage change.
How does BroadPeak manage complex, volatile, or non-standard trades without creating an IT burden?
That’s a great point as it’s where solutions often fall apart. The happy path is easy. However, the real test is when you’re dealing with something like intraday UK or EU power trading which is volatile, complex, and less standardized.
BroadPeak is built for that. Underneath our surveillance solution is a generalized data model, it’s not rigid, it’s not one-size-fits-all. Think of it like a smart starter pack that supports everything from physicals to swaps, options, orders, all structured in a way that makes them unified and queryable, but not crammed into the same mold.
The solution is highly configurable, so when something new comes along i.e. a new trade type, field, or reporting attribute, you don’t need a developer sprint. Your analysts can update the schema. That means you’re equipped to handle outliers without an IT project.
Furthermore, if you’re pushing that data into something like Snowflake for analytics, it stays consistent end-to-end, from raw trade through to reporting. We work closely with clients to make sure it all stays in sync. The core economic data remains in a flat, flexible structure that plugs in wherever it needs to.
As one of our clients said, “the fewer IT projects and the more configurable workflows, the better”. That pressure on IT and resourcing hasn’t changed, but BroadPeak is designed to relieve it. It’s a big win for businesses under strain.
What steps can firms take to avoid delays when managing time-sensitive, granular market events in fast-moving, high-frequency scenarios?
BroadPeak is built to handle precisely that level of detail. Whether you need to analyze a market spike, a trade anomaly, or any specific event down to the finest granularity, our solution supports it. You can easily drill into the exact sequence of events before, during, and after any given timestamp.
Our tools are designed to support complex, time-sensitive scenarios. You can see detailed insights of every order, every fill, and every interaction tied to your trades in real time.We’ve set up alerts for specific events, like order placements, and you can replay these events to analyze the entire history tied to that order, even down to partial fills.
Moreover, our surveillance tools are proactive. If any part of the solution goes down, our alerts trigger immediately, so you won’t miss anything critical. We’re also certified and recommended by major global exchanges, which speaks to the reliability and responsiveness of our tools. I meet with heads of trade capture at these exchanges regularly, ensuring that the data we capture is as comprehensive as possible. For instance, I personally lobbied ICE to expose previously hidden brokered trades in automated feeds, giving our clients a complete, integrated view of their data.
This transparency is key to managing risk. You need to understand whether a trade was brokered or executed electronically, as this distinction can affect your fees and risk profile. With BroadPeak, you get clear, normalized data that’s presented in a way anyone on the team can understand, without needing to be a data expert.
So, whether you’re analyzing micro-level events or broader market trends, BroadPeak allows you to explore that data with the speed and precision that modern trading demands.
How can compliance teams manage false positives in real-time trading alerts?
BroadPeak is built to give clients complete control. Compliance and surveillance alerts allow them to configure them exactly how they need to minimize false positives and focus on what’s truly important.
With BroadPeak, you can see all your orders and trades, and drill down as needed. We support customizable book structures and you can configure life events or job types to flag specific actions, like washes or layering. You can set up and modify alerts on the fly to match your trading environment, whether it’s based on product types, trade sizes, or specific market thresholds.
In a scenario where you might want to track orders over 1,000 lots, you can set that as a condition for alerts. When it comes to complex patterns like layering, where you have orders on both sides of the market, we understand that this might happen frequently in a large organization. Instead of flooding you with irrelevant alerts, we let you fine-tune the solution so you are only alerted to the trades that actually matter.
This is a game-changer because one of the biggest complaints we hear from compliance teams is the overwhelming number of false positives. We’ve met people whose entire job is just clearing these fake alerts. This is not only inefficient, but also frustrating. BroadPeak is designed to focus only on the meaningful alerts based on your specific products and risks, reducing the noise and enabling compliance teams to focus on what’s truly important.
The best part is that you don’t need to rely on us to make these changes. You can iterate, adjust thresholds, or modify date ranges yourself.
With the high volume of real-time market data, how do you manage potential stress points in the solution, like cloud servers, model performance, or daily updates?
We’ve architected our solution specifically to handle high-volume, and we operate entirely in the cloud, ensuring scalability and flexibility. The infrastructure is designed to support both small operations and large, global teams without creating stress points.
For example, we push daily updates and manage data flows to avoid any significant latency issues. Even for a large number of data points, the data is ingested and processed efficiently. We also pull order book data from exchanges at the end of the day.
Now, while there can be challenges with data passing, particularly with the timing of exchange messages or delays in market data availability, we manage these issues by using a filtering mechanism. This ensures that only relevant data gets through and processed, avoiding overload or unnecessary delays. For instance, if we were handling a huge influx of data, we can filter it to make sure you only get the data you need, preventing latency spikes and ensuring that the solution keeps running smoothly.
One of the key things we’ve learned from our clients is that many latency problems arise from improper data management, like pushing the entire trading history into the solution every day, which can slow things down. With our filters, we ensure that this doesn’t become an issue for clients.
So, while market events and data influxes can present challenges, our solution is built to manage them efficiently, giving you real-time insights without compromising performance.
What’s the approach to managing alerts and case management, and how does machine learning improve these processes?
Regarding alerts, you can create customizable alerts for any event in the solution, tailored to your specific needs. These alerts can trigger a case, allowing you to investigate the issue and track all actions taken. For example, I set up a test case from an alert I received, and it gives me full visibility into the details of the order and the actions taken.
As for case management, once an alert is triggered, you can track the investigation process over time. We also plan to leverage machine learning to analyze which types of alerts lead to cases, helping you identify patterns and providing insights for future investigations. This can be especially helpful for new hires, as it helps them understand past patterns and make informed decisions based on what has been addressed before.
When it comes to AI, we use it in focused ways, for example to drive cross-market associations across data sets. This helps tie together key reporting for commodities firms where physical vs financial market analysis is critical. We have not thrown all the data at AI and said *tell us stuff” as surveillance already suffers from too many alerts. We continue to experiment with AI and emerging technologies to refine alerting capabilities to be increasingly meaningful.
