CAPM Efficient Frontier Curve for PowerPoint...• Applying cash to outstanding balances • Analysing and processing disputes • Creating reports (eg, accounts-receivable aging,

Advanced analytics and the Finance functionXavier Fernandes

AgendaWhat is AI?

How is it affecting the insurance industry?

How is it affecting the finance function?

What it means for you

My background

• Defence industry – command & control systems – development & design

• Technology consulting

• M&A advisory – due diligence & post-merger integration

• Analytics director at Metapraxis – application of advanced statistical & machine learning

What is AI?

We humans keep moving the goalposts as soon as a machine achieves an outcome:

• Winning a game of chess against a Grandmaster

• Understanding speech

• Driving a car

What is AI?

AIArtificial Intelligence: exhibits behaviour which appears intelligent

MLMachine learning: enables programs to learn through training, instead of being programmed with rules

DLDeep learning: emulates the way animals’ brains learn subtle tasks

AI as “idiot savants”

• Learning from vast sets of historical data

• Seeing patterns in data

• Basic reasoning

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Machine learning… how does it work?

AI and the (current) insurance value chain?

• Compile & process richer sets of customer data

• Detect non-linear patterns in data

• Project outcomes with greater accuracy & precision

Risk assessment

• Reduce claim processing costs

• Analyse images and classify claims

• Predict settlement costs

Claims processing

• Assess individual claims for fraud indicators

• Identify networks of fraudulent activity

• Inform risk assessment & quotation stage

Fraud detection

• Chatbots utilise NLP to direct customer requests

• Automated responses in natural language

• 24/7, scalable solutions

Customer services

AI as a disruptor to the insurance value chain• Privately-owned cars = convenience, spontaneity, and comfort

• But the average car spends > 95% of time parked

• Autonomous vehicles + transportation-as-a-service = radical change …?

Global insurance premium

42% Car insurance

87% Personal lines

~40% Personal lines

How is AI affecting the finance function?

Robotic process automation (RPA) uses existing IT systems to mimic the actions of human experts –but tirelessly, and with consistency

Accounting

• Automating complex journal entries

• Performing and documenting account reconciliations

• Calculating and applying allocations

• Maintaining fixed-asset accounts

Accounts payable

• Entering nonelectronic-data-interchange invoices

• Performing 2- and/or 3-way invoice matches

• Processing expense-approval requests

• Completing audits (eg, duplicate supplier payments)

Accounts receivable

• Generating and validating invoices

• Applying cash to outstanding balances

• Analysing and processing disputes

• Creating reports (eg, accounts-receivable aging, credit holds)

Financial planning and analysis

• Building standard management reports

• Consolidating and validating budget and forecast inputs

• Gathering and cleaning data for analysis

Payroll

• Flagging time-sheet errors and omissions

• Auditing reported hours against schedule

• Calculating deductions• Harmonising data across

multiple timekeeping systems

Other

• Preparing external-reporting templates

• Conducting transaction audits of high-risk areas

• Preparing wire-transfer requests

Data analytics and the FP&A function

• Less straightforward to automate are activities that finance functions undertake to support strategic decision-making and – tracking

• But finance teams can still take advantage of analytics techniques to augment their own skills and experience

Complexity

Val

ue

Descriptive Analytics

What happened? Diagnostic

Analytics

Why did it happen?

Predictive Analytics

What will happen? Prescriptive

Analytics

How can we make it happen?

Data analytics and the FP&A function

Analytics type Answers … Tools used When to useDescriptive analytics What happened? Data aggregation Summarising business results

Diagnostic analytics Why did it happen? Data mining Drill down to root cause Uncover hidden variance Identify and isolate outliers

Predictive analytics What will happen? Statistical models Simulations Visualisations layering

historical, actuals & forecast

Educated estimates of the future

Prescriptive analytics How can we make it happen? Value driver models

Optimisation models

Strategic decision modelling Complex or time-sensitive

decisions When you have the ability to

change (some) drivers

Value of data and analytics

TRUST

in data authenticity and in analysis quality

LITERACY

of your workforce in data and analytics

COMPLEXITY

of data collection and timely response

DIVERSITY

of data sources, algorithms and skills

Any questions?

CAPM Efficient Frontier Curve for PowerPoint...• Applying cash to outstanding balances • Analysing and processing disputes • Creating reports (eg, accounts-receivable aging,

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