Conduct Risk - Changing the Game

Risk Solutions Practice, Spring 2016

Conduct Risk.Changing the game.

Delivering Advanced MI & Predictive Analytics.

©Advanced Capability Solutions Limited

Conduct Risk – Overcoming the Challenge

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The Challenge for FI’s:

• Overcoming outdated approaches that incorporate inflexible, history focussed metrics.

• Developing the advanced MI and predictive analytics insight needed to support, evidence and predict conduct risk outcomes.

• How to demonstrate positive organisational conduct to the regulator.

• Harnessing the opportunity to capitalise on increased revenues by driving the conduct agenda through the customer lens.

Introduction:

Financial institutions (FI’s) are grappling to operationalisemeaningful MI that allows them to effectively manage theirconduct agenda.

ACS have developed a smart, practical approach fordelivering conduct MI that links predictive analytics andforward looking metrics back to specific, granular underlyingconduct drivers.

Our approach will:

• Realise IMMEDIATE conduct risk value.

• ACCELERATE the operationalisation of your conduct risk

strategy, frameworks and policies.

• Deliver REAL CONDUCT INSIGHT through predictive

analytics capabilities.

• Satisfy the regulator and drive revenues by viewing

business through the eye of the customer.


The Solution – A Smart Approach to Operationalistion

ACS have created a smart, practical approach and set of management practices that:

1. Realise immediate conduct risk value2. Accelerate the operationalisation of your conduct risk strategy, frameworks and policies3. Deliver Advanced MI / Predictive Analytics insight that satisfies the regulator and drives revenues and performance.

Our approach will help you in multiple ways:

3©Advanced Capability Solutions Limited

Improve regulatory confidence by demonstrating pre-emptive evidence of a positive organisation culture

Accelerate understanding of your existing data and delivering Advanced MI / Predictive Analytics quick wins

Deliver insight that protects reputation, enhances customer outcomes and also drives business performance

Align all MI to the purpose, values and target conduct risk outcomes of an organisation

Identify your organisation’s conduct risk touchpoint's and the MI metrics to evidence and predict conduct outcomes

✓Quickly benchmark your conduct risk progress against industry peers and the FCA’s conduct supervision principles

Harness strong knowledge of state-of-the-art, leading and bleeding edge technologies that deliver enhanced insight

✓

✓

✓

✓

✓

Harness the diverse skills required to deliver integrated thinking across customer, culture, people, process, data and technology


PROTECTIVE Reporting that prevents conduct breaches

Rogue TradingPrice FixingMissellingFinancial Crime

Bank OperationsUnstructured

(Text, Audio, Video, Email, Messaging)

Externally HostedStructured

(Live Feeds)

Multiple Structured & Unstructured

(Global Big Data)

Structured Advanced Analytics Layer(prescriptive, descriptive and predictive analytics)

Conduct Risk Data Flow – ‘The Art of the Possible’3

Lin

es

of

de

fen

se

PRE-EMPTIVEReporting to the Regulator (Culture)

Bank OperationsStructured

(Transactional, Customer, Reference)

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Finance

Customer drivenWhat the customer wants, how they want itRetain / build out customer base

Customer sentiment drivenProvide supporting evidence to Regulator of a positive culture and Treating Customers Fairly

Protecting Reputation

• Bribery / Corruption

• Negligence• Customer

Exploitation

PERFORMANCEReporting that drives better business

Risk Mgt.

Treasury

CRMTrading Desks

Product Control

HRMarketing Purchasing

Customer Insight

Product Insight

OperationalInsight

MarketInsight

EmployeeInsight

FinancialInsight

Voice of the customer

Employee behaviour


The starting point for focussing effort could involve any of the highlighted general areas of conduct concern, referenced back through the customer journey.

Depending on the area of focus, a range of technical components and data assets are required to deliver the MI / Analytics solution.

Example components are shown for ‘Treating Customers Fairly’.

Focus on Advanced Analytics and Conduct Risk

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Documents

Instant MessagingInternet

Procedures

Physical mail

Email

System Activity

Past events

Social Network

Sensors

Voice

Staff Role

Transactions

Systems Security Clearance

Facial Recognition

GEO Location

Machine learning

Training

Policy

Internet of Things

Anti Competitive Behaviour

Sanctions

Insider Trading

MarketAbuse

Cyber

Due Diligence

Disclosure

Regulatory Reporting

Customer Fraud

MoneyLaundering

Financial Crime

Treating Customers

Fairly

Rogue Trading

Information Security

Record Keeping

Code ofEthics

Unapproved Purchasing

Risk Management

ComplaintsSegmentation

InappropriateAdvice

Customer Experience

Pricing

Customer Satisfaction

Training

Talent Management

Negligence

Communication

Employee Fraud

Employee Performance

Conflictof interest

Bribery & Corruption

Culture

Compensation & Incentives

Overcharging

Financial Control

MarketStatements

Taxation

Product Performance

Complaints Handling

Product Design

Misselling

Sales Processes

Purchasing

Customer Service

Claims


Conduct Risk Touch Points and The Customer Journey

CO

ND

UC

TCustomer Accepts Offer

Customer Requires a Retail Product

Reputation


Corporate Behaviours

Code of Practice

First Mortgage Payment

Product Account Opened

Compliance (KYC)

Robust Systems

Internal Controls

Regulatory Compliance

Customer Requests Mortgage “Top Up”

Risk Assessment

Product Selection

Employee Behaviours

Product Design

Pricing

Sales Process

Business Model

Customer Lodges a Complaint

Customer Services

Complaints Process

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“Best Fit” Product Offered

The image outlines a customer journey for a mortgage product, drawing out example conduct touch points across the organisation, identifying relevant components for analysis and measurement.


Progression of Focus – Linking Concerns (e.g. Financial Crime)

Customer Employee Operations

Complaints

1

Customer Experience / Satisfaction

2

TreatingCustomers

Fairly

3

Customer Fraud

4

Culture

1

Employee Performance

2

Employee Action

3

Conflictof Interest

4

Negligence

5

Financial Control

15

Due Diligence

17

Training

1

Talent Management

8

Export Controls

6

HR

14

Disclosure

5

Risk Management

9

Sales Practices

4

ProductDesign

3

Segmentation

18


2

MoneyLaundering

1

TerroristFinancing

2

3rd PartyReliance

11

Fraud

4

Market Abuse

5

Reporting

7

8

Sanctions& Fines

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Linking Conduct Concerns

Areas of concern can be viewed logically across customer, employee, operations, market, legal and regulatory dimensions.

Direct linkages can be drawn out across relevant areas or components. This helps contextualise the concern amongst the relevant end to end components involved, prioritise MI focus and drive out a roadmap for delivery with impact. An example has been outlined for the outcome ‘Financial Crime’.

Systems &Controls

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InappropriateAdvice &

Mis-selling

5

Market, Legal and Regulatory

Code of Ethics

6

Product Approval& Review

11

Cross borderActivities

10

10

CustomerService

6

Exploitation

6

Bribery &Corruption

3

Complaints Handling

12

19

Product Performance

Terrorist Financing

Fraud

Market Abuse

Money Laundering

Bribery & Corruption

Conflicts of Interest

Financial Crime

Primary Components

9

1

Claims

13

7

InformationSecurity

7

Record Keeping

20

Pricing

2

3

5

4

4

AnticompetitiveBehaviour


Driving out MI (e.g. Financial Crime – specifically Fraud)

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Training


Secondary Connections

Primary Connections

Product Design

Sales Practices

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Negligence

6

11

9

Risk Management

11

Product Approval& Review

2

158

17

Due Diligence

20Record Keeping

Conflicts of interest

4

3

Employee Action

Systems& Controls

4

16

3

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FCR Scorecard: Fraud

# Whistleblowing and Audit incidence

# of incidents

Average size of loss

Loss by type, product, BU, geography

Example Metrics Example Source Data

o

CustomerSatisfaction

Example indicators:

• Complaints • Customer Reviews• Mystery Shopping• Customer Usage• Loss reduction

Score

Category

Loss Actual

Loss Actual

Loss Actual

Loss Actual

FCR - Fraud

3.7

Weighted Average

Financials

Example indicators:Loss measurement• Actual

• Projected

• Recovered

• prevented

• Spend/ Cost

Score

Management Practices

Example indicators:

• Governance• Sales Practices • Product design • Complaints Handling • Product Risk

Score

Organisation & Learning

Example indicators:

• Training • Culture & Leadership• Communication• Employee Performance• Code of conduct

Score

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Mapping primary and secondary components of conduct concern informs the relevant conduct scorecards needed, respective data sources and appropriate metrics for measurement. A sample (only) of drivers are shown below.

FCR Scorecard: Bribery & Corruption

FCR Scorecard: Anti Money Laundering

FCR Scorecard: Market Abuse

FCR Scorecard: Conflicts of Interest

o

Financial Control

Code of Ethics

Culture

Talent Management

3rd Party Reliance

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Fraud


Hypothesis Free

Advanced Analytics and The Customer Journey

Discovery Validation

Hypothesis Driven

Experiment with your Data

The key to predictive analytics success is the right people, asking the right questions through the right lens – the eye of the customer.

Look at where the customer journey has touch points with the organisation and ask a question that challenges your purpose, values and conduct outcomes.Formulate hypotheses and develop testable predictions against the hypothesisStarting with known data sets, test and validate your predictionsRefine, expand and develop your hypotheses and predictions and and data sources to build out modelsDo not restrict yourself to ‘human intelligence’. Initiate technology driven hypothesis free data analysis to find relationships that you didn’t see to help drive new questions, hypotheses and predictions

Design / ExperimentData AcquisitionData AnalysisBuild Model

Analysing the Question

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Example Use Case - Product Oversight (Pricing)

A simple use case could pose the following question and resulting hypothesis from its data assets:

QUESTION: Do our mortgage products create a significant reputational risk by exploiting a segment of our customers?HYPOTHESS: Mortgage fees and pricing unfairly exploits certain customer segments creating negative market sentiment.

Potential Data Sources

Finance(Margins)

Complaints(CRM Text

Record)

Ombudsman(Complaint - pdf)

Social Media(Twitter)

Customer(Demographic)

Risk(Assessment

Metric)

Comparison Websites(Which?)

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Validation Analyses highlighted that existing customers within 5 years of retirement age

are potentially being exploited when looking to re-mortgage. 30% of complaints are about price 10% are about switching barriers, and 25% are

about access to most competitively priced products.

Hypothesis FreeNo Prediction: Are there any interesting relationships within the data

(financials, risk assessment, customer demographics, online comparison websites and Financial Ombudsman Complaints)?

Hypothesis DrivenPrediction: There will be a positive correlation between risk adjusted profits and negative customer sentiment across certain customer segments (first-time buyer / retired / single / joint mortgage / new & existing customer).

DiscoveryTwitter sentiment is an example of an early indicator of ombudsman

complaint volume. Ombudsman complaints are generally logged two weeks after social media sentiment is posted - can Ombudsman fines now be

avoided?

Outcomes that InspireRedefining commercial success.


ACS Conduct Risk Offering

Accelerated Outcomes(Strategy & Benchmarking)

MI / Analytics Quick Wins(Existing Technology)

Developing use cases that ask the right questions of internal and external data sources within the context of ‘the art of the possible’.

Identification of data sources, appropriate metrics and advanced technology components required to deliver a proof of concept that validates the questions being asked.

Delivery of POC thereon including leading edge MI / Predictive Analytics / Big Data / Machine Learning technology as appropriate.

Protective or pre-emptive reporting to the Regulator.

‘Art of the Possible’ POC(New Technology)

End to end programme delivery of business, data and technical architecture that provides the insight to drive enhanced business performance, customer experience and regulatory confidence through advanced predictive analytics / MI capabilities.

Remediation of existing analytics capabilities.

Protective conduct risk monitoring MI capability and pre-emptive MI reporting to the regulator that demonstrates a positive cultural elements.

Provision of a flexible foundation to cope with future change.

Programme Delivery(Multiple Technologies)

Values audit and gap assessment against the MI / Insight. Pin-pointing the exact areas that need to be improved with the aim of driving congruence with purpose and values, renewing customer trust, increasing staff engagement and driving business performance.

Working with your customer and HR / talent teams to drive operational and cultural change including:

Review of staff engagement systemsRe-engineering of customer experienceCultural & behavioural workshops across organisational teams.

What to do with MI Results?

Discovery session to identify quick wins. Draw out a plan to solutionise and deliver the quick win across business and technology based on a pre-defined requirement.

This will require us to understand your existing process, data and technology architecture and the culture and values of your organisation.

Historical / predictive MI and qualitative / quantitative metrics that provides the ability to measure performance against your conduct risk outcomes and demonstrates early delivery and positive progress to the regulator.

A series of intensive strategic workshops (conducted back to back or over a short period) that will draw out a strategy and plan to operationalise conduct risk strategy in the context of existing strategy and issues, customer experience, business performance and the culture and values of your organisation.

Benchmarking your conduct risk progress against your industry peers, competitors and FCA supervision principles. Production of a client specific conduct scorecard.

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Realise immediate conduct risk value

Accelerate the operationalisation of your conduct risk strategy, frameworks and policies

Deliver Advanced MI / Predictive Analytics insight that satisfies the regulator and drives revenues and performance


Our Key Differentiators – Redefining Commercial Success

Seen As

Client

Unique SMEs

Reduced Cost

Delivery

We operate a successful Smart Source delivery solution, proven to be delivering ‘right first time’ for global financial institutions.

We provide confidence and instil trust, through our people, their history, knowledge and repeatability.

Our commercial model is different. We can tie our success (fees) to your success.

Why ACS?

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1

45

6 3

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Confidence and Trust

Agile and Client

Focused

Our technology delivery centre is at the forefront of state-of-the-art analytics delivery supporting multiple technologies.Technology

Capability

We focus on doing the right thing at the right time to ensure quality and timely delivery.

We don’t behave as an external, we act like you and act in your best interests.

Outcomes Not

Outputs

Our team will impress you. We think differently and we do not deploy inexperience onsite.


Our UK Conduct Risk Practice

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Paul ForrestChairman

Data Solutions

Paul has some twenty-five years experience of helping businesses to solve complex business problems, deliver their transformation goals and to achieve tangible strategic outcomes. Paul has worked with many Global 500 businesses and major Government entities around the world including Ford Motor Company, VAG Group, BAE Systems, GSK, AkzoNobel, RBS, HBOS, Diageo, Bacardi, Wal-Mart, BA, Virgin Galactic, BT. He has recently been nominated one of the most influential people in Big Data (Data IQ 2015).

Malcolm StaitePartner Risk &

Compliance Solutions

Malcolm has a broad spectrum of experience spanning 30 years in managing enterprise scale governance, risk and compliance (GRC) functions in the Banking and Insurance sectors, financial and business control environments. transformations. Malcolm has advised and delivered at many global banks including Barclays, Lloyds Banking Group, Royal Bank of Scotland, Rabobank and Banco Santander. Malcolm is a Conduct Risk SME and thought leader in the industry.

Peter Massey Specialist Advisor

Customer Experience

Peter is a serial entrepreneur with 30 years experience in technology, outsourcing and customer experience. Working with strategic problems and delivering operational practices, he has an extensive track record and reputation across industries with blue chip clients such as Axa, Vodafone, Microsoft, M&S, eBay, HMRC and the Cabinet Office. He is managing director of specialists Budd, implementing Amazon’s growth model; chair of the Chief Customer Officer Forum and is a well known speaker and author on the subject of customers.

Ian HaconPartner Leadership &

Culture

Ian is a charismatic leadership coach, worked closely with a diverse number of board level members at a portfolio of global organisations. He has specialisms in leadership development, wellbeing and resilience, understanding corporate purpose, embedding culture, executive coaching, financial awareness, employee and other stakeholder engagement. His varied background, relaxed style and amenable personality make it easy for him to help others understand the need for, and make commitment to, positive change.

Steve MilesPartner Data /

Technology Solutions

Steve has 25 years of experience managing and delivering complex Information Delivery systems and running international Professional Services operations. Steve bridges the gap between the business and technology functions ensuring that expected outcomes are delivered. Steve specialises in Risk Management solutions, MI, Big Data and Systems Integration and has the background to ensure organisations receive the solutions they require to maintain their competitive advantage.


How to Contact Us

London Head Office60 Cannon StreetLondonEC4N 6NP

+44 (0) 207 078 1906

India Delivery Centre425, 4th Floor, Tower B-3Spaze I-Tech ParkSohna Road, Sector 49Gurgaon, India – 122018India

www.acsconsulting.com

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@ACSConsultingUK

[email protected]

www.linkedin.com/company/advanced-capability-solutionS

Conduct Risk - Changing the Game

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Transcript of Conduct Risk - Changing the Game