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Can Fraud Alerts Raise Customer Loyalty?Stop fraud faster while building trust by better managing the customer experience

For most people, being contacted by a bank about potential fraud isn’t a wonderful experience—

but it can be if it’s managed in a timely, personalized manner. In fact, customers of a UK bank

consistently point to fraud intervention as a “golden moment” of customer service in the

organization’s quarterly surveys.

Mobile devices and electronic channels are enabling banks to engage customers, using the media

of their choice, in intelligent automated dialogs that stop fraud in its tracks. With no increase in fraud

management personnel expense, banks are stopping fraud faster, while building customer trust and

loyalty in ways that drive account usage and spending. And by constantly feeding back to analytics

the results of these customer interactions, they’re improving the accuracy and adaptability of fraud

detection systems.

This white paper discusses how leading banks are driving gains by managing individual customer

experiences as part of fraud intervention. We’ll share some of the results they’re seeing in terms of

better fraud detection, increased efficiency and higher customer satisfaction.

The paper also reveals how industry leaders are:

•  Stopping fraud earlier before losses mount.

•  Finding more fraud without annoying customers.

•  Overcoming channel/product silos for customer-level intervention.

•  Making detection and action smarter by closing the loop between them.

•  Adapting faster to changing fraud patterns.

Number 64—December 2012

www.fico.com Make every decision countTM

Learn how one bank resolved 250% more fraud cases with 30% fewer declines, 95% customer satisfaction and zero FTE increase

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91%happy with auto-resolution 94%

would recommend it to family & friendsBank 1

87%

willing to receive contacts in future 78%

agree strongly the technology has improved the overall level of servicethey’re experiencing

Bank 2

84%

find auto-resolutioneasy to use 89%

said auto-resolution hasincreased their confidence in using card

Bank 3

It’s been called a “moment of truth.” When a bank contacts a customer to check on a possible

fraudulent transaction, the experience can be a negative or positive one for the relationship.

In fact, customers regularly characterize such moments as “golden” in one UK bank’s quarterly

customer service surveys. This demonstrates how much opportunity there is to turn what could

be an annoyance into a valued service.

Timeliness and personalization are critical to better managing the customer experience. When

a suspicious transaction is detected, banks must be able to reach customers where they are,

through the best means for that individual given the circumstances. That means being able

to make contact not only through calls to landline phones, but through calls, emails and text

messages to mobile phones, tablets, laptops and other devices.

It also means engaging customers in an efficient automated dialog. For card transactions, instead

of customers receiving a one-way communication, hours or days later, requesting they call the

fraud line, most cases can be resolved within minutes, some in seconds. Instead of a legitimate

transaction being declined, customers immediately confirm they are the one using the card,

and can continue spending. And for online banking, instead of banks having to choose between

letting a risky funds transfer go through and meeting regulatory requirements for processing

times, they can quickly check with the customer before releasing the funds.

When banks leverage such auto-resolution capabilities, customers can resolve suspected fraud

cases on their account themselves, often simply by pressing a key on their phone or computer

(see Figure 1). While there’s always the option of talking with a fraud analyst, they don’t have to

because they can interact with a virtual analyst—able to perform the same functions, including

accessing records and updating the account—in a direct, immediate and discrete manner.

Customer feedback has been extremely positive for banks that have implemented this approach.

At the UK bank mentioned above, 76% were highly satisfied with its auto-resolution service, 84%

found the service easy to use and 89% said they had increased confidence in using their card

again. Other banks report similar or even higher customer approval rates, as shown in Figure 2.

» Turning “Moments of Truth” into Gold

43% of consumers surveyed want their bank to engage with them more on account updates, potential fraud and other non-marketing matters.

—FICO research, 2012

Figure 1: Speedy fraud case resolution by SMS

Figure 2: Strong customer approval of auto-resolution—survey results from three FICO clients in the UK

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This heightened customer satisfaction and loyalty aren’t earned by punching out messages to

customers with cookie-cutter contact strategies. They come from assessing multiple factors

about the situation and the customer to form and execute an individualized strategy for

contacting that customer in the right way with the right timing.

As depicted in Figure 3, banks today need to couple intelligent, automated fraud detection with

intelligent, automated decision making for customer experience management. And they need

to be able to perform these functions, when appropriate, at high volumes in real-time.

Closing the loop between detection and action makes both smarter.

Action is smarter: When assessing whether action is required, an auto-

resolution solution can consider an overall fraud score from a multichannel/

multiproduct detection system, or look at multiple scores and data from different

channel- or product-specific systems. It may perform additional checks, such as

looking to see if the telephone numbers and email addresses on the account

have ever been associated with suspicious activity in the past or match those

on a fraud watch list. Banks can also, of course, create any number and variety of

case generation/management rules to guide auto-resolution.

To decide what action to take, the solution considers the customer’s contact

preferences and contact history (e.g., has she responded better to SMS or

a phone call?). It looks at the time zone of where it appears the customer is

currently located. It selects the right channel or combination/sequence of

channels, avoiding any that may have been compromised. A good system, for

instance, will check to see if there’s been a change in a mobile phone SIM card

since the last transaction or if an inbound caller ID has been altered.

Detection is smarter: The resulting interventions generally resolve fraud cases

swiftly, with results fed back to detection in a closed loop. That’s a powerful

» Managing Individual Fraud Experiences

What else do we know about this customer and this situation? Which communication channels are available and secure?

Identify the best treatment for this customer, in this situation, at this point in time.

Contact strategy executed across one or more channels. Results monitored and strategy adjusted as needed.

Legitimate or fraudulent transaction confirmed. Customer assisted. Results fed back to analytics to improve detection.

Assess Decide Intervene Resolve

Customer transactions

How risky is this transaction? (Single score across channels/products or multiple scores from different detection systems)

Detection

Score

Action

! ✖LOW HIGH

✓

✓

Real-time feedback

Figure 3: A closed loop between detection and action makes both smarter

within30 secs

Most customercontacts made

15 secs(from 20+ mins)

Improvement inaverage time-to-case

50%Reduction in averagecontact time

67%Cases resolvedwithin 20 mins

Figure 4: Auto-resolution speed metrics—typical results from FICO clients worldwide

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advantage if the detection system includes an adaptive model able to use this feedback to

adjust in real time to changing fraud patterns and customer behavior.

This closed-loop approach also enables banks to deliver each customer a planned, managed

experience that’s dynamic and fully responsive to what is happening with the customer and

in the production environment. As the possible fraud scenarios depicted in Figure 5 show, the

delivery of this experience is a communication-enabled business process that extends across

channels and products. Customers get a consistent experience because the virtual analyst

works round-the-clock and covers all touchpoints. If a customer receives a contact through one

channel and chooses to respond through another, the virtual analyst still knows who they are

and everything that has transpired on the case.

Other recent transactions in this country on other accounts? Changes to SIM card since last transaction? What time is it at transaction location and customer home location?

If other transactions and no SIM change, unblock immediately. If no transactions, contact customer via SMS (customer- preferred method). If SIM change, send email and leave voicemail on landline. Adjust strategy based on time zones.

SMS inquiry to mobile phone sent within minutes of transaction denial.

Customer confirms legitimate. Retried transaction approved. Uses card confidently during rest of trip.

Assess Decide Intervene Resolve

High-risk transaction for large amount with merchant outside of country, not purchased from before. No notation about travel on file. Transaction declined.

Detection

Score

Action

! ✖LOW HIGH

✓

✓

Faster Payments regulations apply, but transaction is high risk. Are payer/receiver account owners the same, or are there known relationships between them? Have there been any SIM card changes since last transaction?

Put transfer on hold while using all available and secure channels to contact customer.

Customer contacted simultaneously via smartphone app and voice calls to mobile and landline.

Customer confirms fraud via smartphone app, so payment is released for settlement. Customer is provided with reassurance and next steps for re-establishing account security.

Wire transfer attempt looks like coming from customer (correct IP address, HTTPS certificate, one-time passcode, etc.), but behavior pattern is unusual. Malware may have intercepted and receiver account values changed.

What time is it at customer location (odd hour for banking)? Have there been any recent SIM card changes or a different inbound caller ID from previous interactions?

Monitor account while contacting customer.

Customer contacted via email. If contact not made within 24 hrs, also attempt via voice call to landline and mobile phone. Block any subsequent high-risk purchases or fund transfer attempts.

Customer confirms new user is not authorized before fraudster has opportunity to break out and empty funds.

New authorized user has just been added to debit account. Could be first sign of account takeover. Several unusual small online purchases raise risk level.

Credit/debit card transaction

Online banking

Nonmonetary transaction

Figure 5: Auto-resolution examples, possible fraud scenarios based on best practices

Real-time feedback

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Resource constraints and concern about annoying customers with false positives have

traditionally discouraged banks from generating cases for transactions in midrange

fraud scorebands.

Auto-resolution eliminates both resource and false positive

constraints. While an expert analyst is often able to resolve fewer

than 20 cases per hour, a virtual analyst can resolve an unlimited

number with no staffing increase and while keeping customers happy.

By reaching deeper into scorebands, banks catch more fraud. As

shown in Figure 6, the incidence of fraud is lower at a score of 450

than it is at a score of 850. Nevertheless, fraud is still present at this

level, even with a lower detection rate, so the benefit to detecting

fraud in this range is significant.

FICO clients across the globe are reaping the benefits of digging

deeper: One UK bank that implemented auto-resolution is resolving

250% more fraud cases—achieving 30% fewer declines and 95%

customer satisfaction—with zero FTE increase. Another UK bank has

reduced the average number of transactions per fraud found from 5

to 3. A US bank reduced net fraud losses by 75%.

Banks vary in how they’re assigning this expanded range of

fraud cases to human and virtual fraud analysts. Some write case

management rules that continue to direct the highest-risk cases

to their most experienced analysts, while directing midrange risk

cases to auto-resolution. Some prefer to put auto-resolution on the

high-risk cases first, since at this level, speed-to-contact and rapid

resolution are most crucial for keeping losses down.

Some banks are even opting to deploy auto-resolution across

the entire score range, freeing their expert analysts to investigate

confirmed fraud and interact with customers on very complex and

high-value cases. Best-in-class auto-resolution solutions include easy-

to-use business rules management and workflow management tools

that enable fraud department managers to experiment with different

approaches, and quickly capture and compare results metrics.

» Stopping More Fraud Faster

Normalcall center

focus

Additionalautomation

capacity

Frau

d ris

k sc

ores

Typical false p

ositive : fraud ratios

850 10 : 1

55 : 1450

Figure 6: Reaching deeper into scorebands to catch more fraud and minimize customer impact

50%Fraud loss per case

70%Unrecovered fraud losses

35%Overall fraud losses

Figure 7: UK banking group reduces losses with auto-resolution

60% (–30% FTE)Cases worked

300% (same FTE)Cases worked

Figure 8: US and UK banks use different auto-resolution strategies—both achieve major efficiency gains

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Can Fraud Alerts Raise Customer Loyalty?

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Another way auto-resolution helps banks stop fraud faster and reduce losses is through the

feedback to detection analytics. This feedback comes in quicker with auto-resolution. If the bank

is using auto-resolution to probe down into midrange scorebands, there’s also more feedback

to work with. And if the bank has online and mobile apps that customers can use to quickly

confirm multiple transactions, as shown in Figure 9, the volume of data coming back to

analytics is even greater.

Fraud detection systems can leverage this incoming data in several ways.

Fraudulent online authentication attempts, for instance, are highly predictive of

account takeovers. But when fraudsters fail authentication, they never get to the

transaction step, so fraud detection systems don’t generally receive any data. Auto-

resolution systems, however, can immediately pass data on confirmed fraudulent

authentication attempts to detection systems.

Incoming auto-resolution data can also be used by detection analytics to self-adjust in

real time to changing fraud patterns and customer behaviors. This is a unique capability

of FICO® Falcon® Fraud Manager.

As shown in Figure 10, the Falcon system incorporates an adaptive model. This analytic

layer contributes a valuable additional perspective because it’s focused on and

highly responsive to what is happening in the current production environment. All

transactions the base model scores above a bank-selected “cascade threshold” go to

the adaptive model for an additional score, which is then blended with the first one.

» Leveraging Rapid Feedback for Higher Performance

Base analytics Adaptive analytic layer

Updating ofvariable weights(continuous)

Fraud/no-fraud tablesRapid feedback of fraud/no fraud confirmations

Profile Scaled profile Model

Reviewthreshold

Confirmed fraud casesfor final resolution

Cascadethreshold

Expert analystVirtual analyst

Model

Variable evaluation & replacement based on relevancy to production data(frequent intervals)

Variable candidate

pool

Transactional dataBasescore

Blendedscore

Adaptivescore êé

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Rapid feedback from auto-resolution accelerates theunique adaptive capabilities of FICO® Falcon® Fraud Manager, enabling banks to detect emerging fraud schemes and adjust to changing customer behavior faster

Figure 10: Rapid feedback increases adaptability of detection models

Figure 9: Gathering more fraud information with a smartphone app

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Can Fraud Alerts Raise Customer Loyalty?

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The adaptive model uses fraud case resolutions and data to evaluate which data variables are

proving most predictive of fraud now and in the recent past (past day, past week, etc.). For example,

are the values for the dollar amount variable significantly different between electronics purchase

transactions confirmed as fraudulent vs. similar transactions confirmed as legitimate? The adaptive

model swaps these currently high-performing variables into its fraud/no fraud tables while

swapping out those currently less predictive. It also uses the case dispositions to continuously adjust

variable weighting to the changing fraud patterns it’s seeing.

These adaptive processes improve detection of emerging fraud schemes, so banks can stop them

sooner. When combined with other dynamic analytic techniques also built into the Falcon system—

such as self-calibrating profiles that tune base model weights to changing customer behavior or

economic conditions—the result is more accurate fraud detection and reduced false positive rates

at every scoreband.

There is evidence, both from what customers say and what they do, that the experience of a timely,

dialog with a virtual fraud analyst builds loyalty. It also increases the value customers feel they’re

receiving from the bank, and influences their behavior in ways that drive revenue and profit.

The most clear cause-and-effect impact on revenue is, of course, at

the point of sale. When checkout problems arise, immediate, helpful

intervention greatly lessens the embarrassment and inconvenience that

customers may experience. It also enables more legitimate high-risk

transactions to go through. With the ability to contact customers within 30

seconds to confirm legitimacy, one UK bank has reduced declines by 32%.

And when a very high fraud score causes a bank to block or restrict a

card, faster resolution reduces the impact on subsequent transactions.

Another UK bank is able to contact 79% of its customers within 10

minutes of taking such actions. If the customer confirms the transaction

is legitimate, blocks and restrictions are removed instantly.

For online purchases, auto-resolution helps banks avoid losing

transaction fees because of failed authentication attempts by legitimate

cardholders. For example, if a customer mis-keys his 3D Secure passcode

(e.g., Verified by Visa, MasterCard Secure Code), the virtual analyst can

let him know immediately that this was the reason for the decline and

prompt him to try again.

These impacts are increasingly important to banks that are changing the way they measure fraud

management performance. A growing number of UK and European banks have expanded their KPIs

(key performance indicators) to include not only reducing fraud losses, but increasing spend per

card also.

Quick resolution can also help boost spend by increasing the customer’s confidence about using

the card again. Instead of switching to another card or curtailing shopping altogether, the consumer

is more likely to make subsequent purchases with the same card. In cases of confirmed fraud, it

reduces the odds—1 in 5, according to a 2010 Datamonitor global survey1—that the consumer will

close the account altogether.

1 Consumer-Facing Fraud Prevention Strategies in Payments study, Datamonitor (Ovum), 2010

» Increasing Customer Loyalty and Account Usage

10%Active debit (spend) population +1%Number of transactions +

23%Average ticket value per spend +

Figure 11: Higher revenue—auto-resolution results from one bank’s debit portfolio

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Can Fraud Alerts Raise Customer Loyalty?

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Moreover, because auto-resolution is managing a customer-level experience, a single dialog can

confirm status and transactions on multiple cards/accounts. If fraud is confirmed on a debit card, for

instance, the customer doesn’t have to wonder if a credit card attached to her deposit account has

also been compromised; auto-resolution can ease her fears on the spot. As a result, the increased

confidence she feels, and its impact on subsequent usage, may also extend beyond a single

account, to the full relationship.

Though the numbers vary by country, the Datamonitor survey mentioned above found that half of

victims and nearly as many non-victims agreed they can “do more to protect themselves from fraud.”

While detecting and preventing fraud will continue to be the banks’ responsibility, two-way mobile

communications that enable consumers to increase their awareness and play a more active role in

the process can reduce fraud losses and help bring down the costs of using convenient payment

vehicles like credit cards.

That feeling—of being part of a valuable relationship, based on trust and characterized by good

communication—is precisely what banks are now working so hard to create with their customers.

The beauty of adding auto-resolution to fraud management is that it helps banks rise above obstacles

to this goal, such as siloed data stores that have made it difficult to manage fraud interventions

at a customer level. At the same time, it provides an ideal opportunity for initiating a dialog that

consumers perceive as aimed at their welfare, rather than “just trying to sell them something.”

Combining auto-resolution with advanced adaptive analytic detection FICO offers best-in-class fraud solutions for auto-resolution and real-time detection. When used together, the solutions enable banks to

improve fraud management and increase customer loyalty.

FICO® Fraud Resolution Manager reduces the time required for fraud resolution from hours or days to seconds or minutes. Based on fraud

output (i.e., scores, rule results) from a transactional fraud detection system, it performs high-volume, real-time intelligent assessment of

fraud cases, identifying the best contact strategy for each customer in each situation. It executes the strategy across one or more channels,

managing a customer-level experience, and feeding back data to analytic detection.

Combined with the fraud detection capabilities of FICO® Falcon® Fraud Manager, the feedback loop from auto-resolution delivers powerful

benefits. The unique adaptive analytics in the Falcon system can use information from the abundant stream of timely auto-resolution data

to adapt fraud risk scoring to changing fraud patterns and customer behaviors. The result is faster detection of emerging fraud schemes,

enabling banks to stop them sooner.

Can Fraud Alerts Raise Customer Loyalty?

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The Insights white paper series

provides briefings on research

findings and product development

directions from FICO. To subscribe,

go to www.fico.com/insights.

FICO, Falcon and “Make every decision count” are trademarks or registered trademarks of Fair Isaac Corporation in the United States and in other countries. Other product and company names herein may be trademarks of their respective owners. © 2012 Fair Isaac Corporation. All rights reserved.2930WP 09/13 PDF

For more information North America toll-free International email web +1 888 342 6336 +44 (0) 207 940 8718 info@fico.com www.fico.com

Going forward, there’s great potential for banks to boost fraud detection by further integrating

customer dialog/confirmation into self-learning analytics. There is also an opportunity to build

out fraud management dialogs in personalized ways for each customer. Some customers, for

example, want more visibility into and control over their accounts on a day-to-day basis. They might

appreciate alerts and helpful dialog about balance levels and spending pattern changes (e.g., inflow/

outflow imbalances). They might like timely ideas on how they could use their existing credit more

advantageously. Others want to know more only when there’s a problem.

As consumers become more accustomed to dialog-based services, banks will be able to encourage

them to provide detailed preferences and make a range of opt-in choices when opening new

accounts. Auto-resolution will use all of this input to shape highly personalized customer

experiences, providing many “golden moments” to grow relationships over the long term.

Learn more:

•  Download Insights white papers, which regularly cover fraud innovations and best practices.

•  Subscribe to the FICO Banking Analytics Blog for the latest fraud news, research and ideas.

» Conclusion