A single data point is often misleading. In fact, looking at data in isolation is the fastest way to make a bad business decision.
We see this problem constantly in risk, fraud, and customer management. You have a customer record in your sales system. You have a different record in your support system. And you have a third record in your risk database.
To your team, these look like three different people. To the customer, they’re one person getting a disjointed, frustrating experience.
The problem isn’t that you lack data. It’s that your data lacks context.
The Mechanics: How We Connect the Dots
Connecting these points requires a process called Entity Resolution. This isn’t just a buzzword. It’s a complex engineering challenge that sits at the core of Decision Intelligence.
Data’s messy. In one system, a customer is “J. Smith” living at “123 High St.” In another, they are “John Smith” at “123 High Street, Flat 2.”
A standard database query sees those as two different people. It misses the connection.
We build algorithms that use fuzzy matching and probabilistic logic to stitch these records together. We look at the strength of the links. Do they share a phone number? Has that device ID been used with this email address before?
When we resolve these entities, we create a Golden Record. This is a single, trusted view of the truth that spans your entire organisation.
The Benefit 1: Stopping the False Positives
Most businesses think about risk management as blocking bad people doing bad things with their data. But the hidden cost of a bad risk strategy is blocking good customers doing the things you want them to do.
We’ve all had it happen. You try to buy something online, and your card gets declined. The bank’s system saw a single data point, maybe a foreign IP address, and panicked. It lacked context.
With Decision Intelligence, the system sees the whole picture. Yes, the IP is foreign, but you bought a plane ticket to that location last week using the same device. The risk score drops, the transaction goes through, and you keep the revenue.
That’s the difference between a dumb rule and an intelligent decision.
The Benefit 2: Finding the Hidden Risk
The flip side is also true. A fraudster knows how to pass a simple checklist. They have a valid address and a clean credit score.
But a graph database, which maps the relationships between data points, might see that this “clean” customer shares a mobile number with a known money launderer. Or that their “home address” is actually a mail drop used by fifty other shell companies.
You can’t see that risk by looking at the row in the spreadsheet. You can only see it by looking at the network.
The Commercial Reality
This isn’t just about security. It’s about efficiency.
If your team has to manually review thousands of flagged transactions, that’s expensive. By connecting the data points automatically, we can automate the easy decisions, approving the obvious good customers and blocking the obvious bad actors.
This leaves your human experts to focus on the grey areas, where their experience actually adds value.
Don’t settle for disconnected data. It’s costing you money in lost sales and wasted time.
To discover how we can help you make more sense of your data, book a one to one session with our CEO, Kevin Hurd, for free! Visit our Data Triage page for more details.
