As a fraud and risk professional, you may feel as though your organisation walks a tightrope, balancing minimal customer friction with maximum risk mitigation.
By Doug Clare, vice-president: fraud compliance and security solutions at Fico
The challenge is magnified in today’s fast-paced multi-channel environment, where, for example, a customer may be asked to verify a point-of-sale card transaction flagged as fraudulent, only to be forced to jump through multiple authentication hoops when they check their mobile banking app immediately afterward, just to make sure their credit card is OK.
You’re not alone. Billions of these friction-filled moments occur daily, as financial organizations of all kinds—from traditional banks to fintechs and telecommunications providers—contend with making millisecond-quick decisions that can comprise elements of fraud protection, authentication, identity proofing, know your customer (KYC) and compliance, combined with the overarching need to make all interactions as seamless and convenient as possible.
As we look to our mobile devices to make transactions fast and easy, the mix of underlying data has become incredibly complex. That’s the challenge that contextual intelligence promises to help cut through.
At its most elemental, contextual intelligence provides the answer to a bank’s question, “What answer, to what question, do I need to know, at what moment in time in the customer journey, to make sure the transaction is legitimate?”
In the converged world we now inhabit, we have an abundance of data in raw format. Through the lens of the customer journey, we may need to combine a fraud decision and an authentication decision, or identity proofing and know your customer compliance decisions. Increasingly, in any of these decisions, a bank needs to make, they need to use data from both outside and within their organization.
The sea of data that is available — such as geolocation, type of mobile device, card transaction history and point of last ATM withdrawal — is meaningless in and of itself. We have to work out, which questions do we have of that data, and what are the answers we want to know?
Contextual intelligence is putting the right amount of data into the appropriate context, at specific moments in the customer journey. FICO builds contextual profiling variables and features, which pose the questions and determine the correct answers to questions. Otherwise, we are just drowning in data with no answers.
Let’s say a customer goes on holiday in Thailand. She wants to access her online banking to pay a bill but didn’t bring her laptop on the trip, and her phone has run out of battery. She goes to the computer in the hotel lobby to log into her online banking. Contextual intelligence can drive the following sequence, to simultaneously ensure security and a streamlined customer experience.
- This is a new device. In isolation, it appears risky. The customer is asked to authenticate via an email link since, at the moment, she can’t accept a text on her phone.
- The customer logs in, and it’s immediately apparent she’s a long way from home, on a computer she’s never used before. It’s appropriate to step up her authentication; she is presented with challenge questions that are successfully answered, and she pays the bill.
Here’s a twist on that scenario: A half hour before logging on, she made a withdrawal at the ATM in the hotel lobby using her debit card. The stepped-up authentication above would have been bypassed because, although the customer is logging in from a new device and is in Thailand, we know:
- She withdrew money at an ATM in Thailand at the same geolocation 30 minutes prior.
- That appeared suspicious, so an agent from the bank’s fraud desk called the customer to verify that she was indeed making the withdrawal. The customer verified the transaction, and then her phone ran out of battery.
Therefore, when the customer logged on to online banking from the hotel lobby, contextual intelligence would have dictated that, since the customer has verified she is in the same geolocation and had used her card, no further authentication would be required to pay a bill. Adding friction to this low-risk activity would be unpleasant for the customer — but if she decides to do a high-risk online banking activity, such as send a wire transfer or a large P2P payment, the system will ask to authenticate further.
To sum it up, different transactions require different questions and different answers —and different contextual intelligence.
Banks and financial institutions can use contextual intelligence by shifting to a contextual approach that maps to the customer journey, customers’ experiences will simply be better — less friction, fewer false positives, higher detection rates of actual frauds and scams, Better experiences translate into greater customer loyalty and ultimately, more profits.
At a strategic level, contextual intelligence allows banks to truly maximize the value of their investments in converging fraud and compliance infrastructures, systems and processes. On top of this more efficient, integrated foundation, contextual intelligence provides a decision framework that can be applied to multiple customer journeys: account opening and KYC, retail banking money transfers, person-to-person (P2P) transfers, credit applications; anything that requires the orchestration of data from multiple sources to answer point-in-time questions.