Moving from predictionto decision:Automating decision-making in the financial services risk and compliance arena

The financial industry is being driven by the opposing forces of regulatory pressure and rapid, global expansion

Financial Institutions

Revenue deflation

Increased regulatory pressure

Unknown market risks

Trade Finance Industry Complex

relationshipsRapid

expansionGlobal scale

As organizations rapidly expand, manual risk and compliance processes become embedded and growth becomes a function of headcount

Manual processes introduce a number of risks to risk and compliance organizations

Low adaptability

Inconsistent application or

execution

Introduction of cognitive biases

Absence of feedback

mechanisms

Automation can be employed to control risks and focus employees on high value activities

Data gathering,75%

Data transforma-tion,15%

Investigation, 10%

Data gathering, 5%

Data transformation, 5%Investigation,

90%

In a manual process, analysts spend only 10% of their time in the key decision-making phase (investigations)

With automation, analyst attention is now focused upon understanding the data and drawing a conclusion

By automating clear-cut decisions, expert resources are enabled to concentrate on making difficult decisions

Fully automate

Fully automate

Partially automate

Predictive Analytics

Customer Profiling

Network Analysis

SuspiciousNot Suspicious

In the risk and compliance space, automated decisions should be based upon a hybrid of policy and business- and analytics-generated hypotheses

Pol

icy

driv

enH

ypot

hesi

s dr

iven

Policy identification

Business hypothesis generation

Analytics hypothesis generation

Iterative analysis and review

Requirements definition and development

App

rova

l and

Impl

emen

tatio

n

Automated decisions

Where manual intervention is still required, analytics can enable improved decision-making through presentation of curated and relevant information

Network analysisEntities and networks are risk-scored to provide a holistic and risk-based

view of a client relationship, enabling analysts to pinpoint transactions with previously identified suspicious or high risk parties

Location-based analysisGeographic indicators may provide significant insight into a

transaction’s potential to be associated with criminal activity In some businesses, such as trade finance, the geographic

information associated with ancillary parties, such as a shipping vessel may be highly relevant

Behavioral profiling analysisProfiling of a customer against historical norms and peer activity can aid in identifying or confirming the presence of suspicious activity

Key considerations in using network analysis to inform decisions

How reliable is your entity resolution?

How many degrees of separation should be considered?

What relevant historical events should be considered?

How does risk of the network factor into risk of the individual?

Key considerations in using location-based analysis to inform decisions

What level of detail in geographic information is available consistently across your organization?

What locations are relevant to a transaction’s risk?

What external sources can be used to enhance or cross-reference geographic information?

Key considerations in using behavioral profiling analysis to inform decisions

How should customers and accounts be segmented?

What aspects of a customer are available for profiling?

How will a deviation be defined from both a policy and analytics standpoint?

About the presenterCarl Case is a Senior Manager in the Financial Services Organization of Ernst & Young LLP (EY). Carl is a Certified Anti-Money Laundering Specialist and specializes in data analytics, predictive modeling, model validation, and risk management in the regulatory compliance and financial crimes space.Carl's recent experience involves supporting global financial services institutions in enhancing and transforming their financial crimes monitoring programs through the use of advanced analytics and robotic process automation, specifically withinthe areas of AML monitoring and investigation.  He has facilitated numerous examinations and instructional sessions with federal regulatory agencies on the topic of AML monitoring and tuning.

Carl also serves on the steering committee of the EY Veterans Network, a national network of more than 800 EY professionals dedicated to strong leadership principles and devoted to professional development through networking with companies that share a commitment to veterans and community service.Carl completed his undergraduate studies at the United States Naval Academy and MBA at Columbia Business School. Prior to joining EY, Carl served in the Global War on Terrorism as an officer in the U.S. Navy.

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