“big data” meets river / gulf vessel risk management...“big data” meets river / gulf vessel...
Post on 05-Sep-2020
3 Views
Preview:
TRANSCRIPT
“Big Data” Meets River / Gulf Vessel Risk Management MARTIN MCCLUNEY, MARSH MARINE PRACTICE STEVEN JONES, MARSH GLOBAL ANALYTICS
MARSH
Goals of today’s
discussion
• Trends in River & Gulf Vessel
Risk Management
• Qualify Meaning of “Big Data”
• Risk Transfer Decision
Framework
• Understanding Your Company’s
Risk Tolerance
• Assessing Loss Potential
• Evaluating Efficiency of Insurance
Coverage
1
MARSH
A Volatile River & Gulf Vessel Industry Commodity pressure is increasing focus on operational efficiency
1. For OSVs and Shipyards, reduced oil prices have impacted activity and
pressured operating margins.
2. Diverse portfolios are faring better with improving economic activity.
Single industry operators, in a variety of segments, are either doing well
or doing poorly.
3. Crew Claims continue to occur, despite safety programs.
4. Inflexible Insurance Costs increasingly erode precious working capital.
2
MARSH
Common Risk Management Responses A majority of clients are seeking price and coverage reductions
1. Company wide S&GA cost reductions
2. Risk managers are seeking insurance rate and premium reductions
wherever possible including breaking continuity. Also receiving mid-term
cancel/rewrite penalty credit from new insurance company.
3. Risk Managers are seeking alternatives to retrospective premium credits
for reduced activity, e.g., eliminating prepayment of navigating activity.
4. Risk managers are reducing coverage in “discretionary” risk issues, e.g.,
looking to increase attachment / deductibles and reduce limits or hull
insured values on many of their policies.
5. In recognition of the suffering of member / vessel operators in many
sectors some international group P&I clubs (having achieved record
surpluses) are moderating inflationary increases and sometimes deferring
full calls.
3
MARSH
By The Way, What Is Big Data? Concept is more important than the definitions
4
“most data professionals didn’t know
the definition of big data before it no
longer had meaning” - Steve Jones ’14
“data is big when data size becomes
part of the problem.” - Mike Loukides ’10
Gartner’s 3 Vs to define “Big Data”
1. Volume
2. Velocity
3. Variety
“big data refers to using complex
datasets to drive focus, direction,
and decision making within a
company or organization.” - Jessica Kirkpatrick ’14
MARSH
AM I EXPOSING MY COMPANY TO TOO MUCH RISK?
ARE ALL MANDATORY INSURANCE COVERS TAKEN IN ALL GEOGRAPHIES?
ARE KEY RISKS OF MY BUSINESS INSURED OR TRANSFERRED?
IS MY RISK MANAGEMENT MOST EFFECTIVE?
DO WE EVALUATE OUR “TOTAL” COST OF RISK?
HOW MUCH RISK CAN MY COMPANY COMFORTABLY RETAIN?
Strategic Decision Making and Vessel Risk Management Questions clients are asking….
REGULATORY & COMPLIANCE
GLOBAL/LOCAL BENCHMARKING OF COVERS AND LIMITS PURCHASED
PORTFOLIO APPROACH TO RISK
BEST PRICING
BEST COVERAGE TERMS AND STRUCTURE
RISK TOLERANCE
DO I GET THE BEST RETURN ON RISK INVESTMENT? OPTIMAL PROGRAM
STRUCTURE
5
MARSH
• How much risk can your company tolerate?
• Is your company adequately protected against risk?
• Is your company getting the expected value from its
insurance purchase?
Risk Transfer Decision Process Purchase what is necessary, validate what is discretionary
Why buy insurance at all?
• Regulatory and contractual obligations?
• Balance sheet protection?
• For those at the company’s discretion, evaluate the risk and
financial benefit of purchasing insurance
What ?’s to answer to confirm your decisions?
Why?
How?
6
MARSH
Evolution of Risk Transfer Decision Capability Decisions support tools available to Risk Managers
BENCHMARKING ACTUARIAL
POINT ESTIMATES iMAP
7
MARSH
Key Analytics Questions for Risk Management
1 How much risk can your company tolerate?
• What are your company’s sources of capital and how do you
prefer to deploy those resources to deal with unexpected losses?
• Is there agreement and “buy-in” from leadership on the risk
tolerance for the company?
Where do you draw the line in the sand?
8
MARSH
Developing a Corporate Risk Tolerance Three Perspectives
Liquidity
Cash Ratio
• Measure of companies
ability to meet short term
obligations
• Evaluate company‘s ratio
and determine capacity to a
predetermined minimum
(e.g, 1:1)
Debt Coverage
The Bondholders’ View
• Emphasis on interest or
coverage ratios.
• Looks at debt covenants
and evaluates capacity to
infringe on a required
leverage ratio.
• Could look at credit ratings
through a very similar lens.
Key Performance
Indicators (KPIs)
Qualitative View
• KPIs are selected from:
– Balance sheet.
– Income statement.
– Access to other funds.
• Flexibility allows for
reflection of company
culture.
1 How much risk can your company tolerate?
Cash & Cash Equivalents
Current Liabilities
9
MARSH
Assessing Adequacy of Protection
Is your company adequately protected against risk?
• Are your company’s limits and deductibles appropriate?
• Does your insurance structure reflect corporate risk tolerance?
2
P&I
Hull
D&O
Other Casualty
Other Lines
P&I
Hull
D&O
Other Casualty
Risk Tolerance
COST OF RISK BEFORE INSURANCE
COST OF RISK AFTER INSURANCE
OPTIMIZATION
Other Lines
10
MARSH
1 How much risk can the company tolerate?
Exploring Loss Potential Company & Industry Loss Data 2
Is your company adequately protected against risk?
• Potential considerations for P&I
Fleet size
Crew statistics
Cargo (e.g., types, quantities, values)
Geographies, routes and distances
Black swan events/scenarios
• Potential considerations for Hull
Fleet size
Vessels characteristics
Geographies, routes and distances
Additional operating costs in event of loss
Vessel finance obligations
Market for replacement vessels
Black swan events/scenarios
11
MARSH
1 How much risk can the company tolerate?
Exploring Loss Potential “Simulating” loss outcomes for the company 2
Is your company adequately protected against risk?
12
Building a Loss Distribution
0 10 20 30 40 50 75 100
in Millions
Loss Type Loss Number Loss Amount
Crew Injuries 1 6,000$
2 22,000$
3 150$
4 100,000$
5 -$
Cargo Liab./Salvage 1
2
Pollution 1
2
Collision/Allision 1
2
Fines/Legal Costs 1
2
Total Annual P&I Losses 1 128,150$
% F
req
ue
ncy
Building a Loss Distribution
0 10 20 30 40 50 75 100
in Millions
% F
req
ue
ncy
Loss Type Loss Number Loss Amount
Crew Injuries 1 15,000$
2 34,000$
3 1,000$
4 25,000$
5 150,000$
Cargo Liab./Salvage 1 250,000$
2
Pollution 1
2
Collision/Allision 1 100,000$
2
Fines/Legal Costs 1
2
Total Annual P&I Losses 1 575,000$
Iteration 2
Building a Loss Distribution
0 10 20 30 40 50 75 100
in Millions
% F
req
ue
ncy
Loss Type Loss Number Loss Amount
Crew Injuries 1 25,000$
2 45,000$
3 500$
4 105,000$
5 -$
Cargo Liab./Salvage 1
2
Pollution 1 2,500,000$
2
Collision/Allision 1
2
Fines/Legal Costs 1 250,000$
2
Total Annual P&I Losses 1 2,925,500$
Iteration 3
Building a Loss Distribution
0 10 20 30 40 50 75 100
in Millions
% F
req
ue
ncy
Loss Type Loss Number Loss Amount
Crew Injuries 1 20,000$
2 400$
3 150$
4 24,000$
5 -$
Cargo Liab./Salvage 1 400,000$
2
Pollution 1
2
Collision/Allision 1 7,000,000$
2
Fines/Legal Costs 1 50,000$
2
Total Annual P&I Losses 1 7,494,550$
Iteration 4
Building a Loss Distribution
0 10 20 30 40 50 75 100
in Millions
% F
req
ue
ncy
Loss Type Loss Number Loss Amount
Crew Injuries 1 8,000$
2 15,000$
3 150$
4 100,000$
5 -$
Cargo Liab./Salvage 1 4,000,000$
2
Pollution 1 20,000,000$
2
Collision/Allision 1 25,000,000$
2
Fines/Legal Costs 1 5,000,000$
2
Total Annual P&I Losses 1 54,123,150$
Iteration 5
Building a Loss Distribution
0 10 20 30 40 50 75 100
in Millions
% F
req
ue
ncy
Iteration Total Loss Amt
1 128,150$
2 575,000$
3 2,925,500$
4 7,494,550$
5 54,123,150$
6 27,650$
7 -$
8 130,300,150$
9 15,560,000$
10 4,736,100$
MARSH
Assessing Efficiency of Insurance Coverage Quantifying volatility “in the tail”
Is your company getting the expected value from its insurance purchase?
• Cost of retaining risk vs. cost of transferring risk (premium)?
• Whose capital is cheaper: your company’s or your insurance carrier’s?
3
13
MARSH
Key Statistics Before Insurance Retained After Insurance (Cost) / Benefit
Average Annual Losses 5,506,858 3,780,731 314,487
Standard Deviation 23,875,866 13,111,817
Coefficient of Variation 5.30 3.40
1 in 1.33 Years 25% Perc 0 3,020,342 -3,020,342
1 in 2 Years 50% Perc 0 3,020,342 -3,020,342
1 in 4 Years 75% Perc 0 3,020,342 -3,020,342
1 in 10 Years 90% Perc 1,619,223 3,270,342 -1,651,119
1 in 100 Years 99% Perc 85,679,570 3,520,342 82,159,228
1 in 250 Years 99.6% Perc 151,915,728 34,936,070 116,979,658
Assessing Efficiency of Insurance Coverage Using Economic Cost of Risk
Evaluating the trade-off regarding retaining risk on your company’s balance sheet as
compared to paying a premium to transfer the risk, e.g., insurance. Similar approach
used in other hedging strategies.
Economic Cost of Risk (ECOR)
Sign Components No Insurance Current Program Option A Option B
+ Discounted Average Retained Losses 5,146,309 3,402,658 3,814,605 3,938,994
+ Premium 0 3,020,342 2,416,274 2,265,257
+ Implied Risk Charge 2,036,577 510,399 572,191 669,629
+ Collateral and Other Admin Costs 110,000 45,000 57,000 70,000
= Economic Cost of Risk 7,292,886 6,978,399 6,860,070 6,943,880
3 Is your company getting the expected value from its insurance purchase?
14
MARSH
TRANSITION SLIDE
Key Statistics Before Insurance Retained After Insurance (Cost) / Benefit
Average Annual Losses 5,506,858 3,780,731 314,487
Standard Deviation 23,875,866 13,111,817
Coefficient of Variation 5.30 3.40
1 in 1.33 Years 25% Perc 0 3,020,342 -3,020,342
1 in 2 Years 50% Perc 0 3,020,342 -3,020,342
1 in 4 Years 75% Perc 0 3,020,342 -3,020,342
1 in 10 Years 90% Perc 1,619,223 3,270,342 -1,651,119
1 in 100 Years 99% Perc 85,679,570 3,520,342 82,159,228
1 in 250 Years 99.6% Perc 151,915,728 34,936,070 116,979,658
Evaluating the trade-off regarding retaining risk on your company’s balance sheet as
compared to paying a premium to transfer the risk, e.g., insurance. Similar approach
used in other hedging strategies.
Economic Cost of Risk (ECOR)
Sign Components No Insurance Current Program Option A Option B
+ Discounted Average Retained Losses 5,146,309 3,402,658 3,814,605 3,938,994
+ Premium 0 3,020,342 2,416,274 2,265,257
+ Implied Risk Charge 2,036,577 510,399 572,191 669,629
+ Collateral and Other Admin Costs 110,000 45,000 57,000 70,000
= Economic Cost of Risk 7,292,886 6,978,399 6,860,070 6,943,880
3 Is your company getting the expected value from its insurance purchase?
Assessing Efficiency of Insurance Coverage Using Economic Cost of Risk
15
MARSH
Theme 3
Key Statistics Before
Insurance
Retained After
Insurance
(Cost) /
Benefit
Average Annual Losses 5,506,858 3,780,731 314,487
Standard Deviation 23,875,866 13,111,817
Coefficient of Variation 5.30 3.40
1 in 1.33 Years 25% Perc 0 3,020,342 -3,020,342
1 in 2 Years 50% Perc 0 3,020,342 -3,020,342
1 in 4 Years 75% Perc 0 3,020,342 -3,020,342
1 in 10 Years 90% Perc 1,619,223 3,270,342 -1,651,119
1 in 100 Years 99% Perc 85,679,570 3,520,342 82,159,228
1 in 250 Years 99.6% Perc 151,915,728 34,936,070 116,979,658
Insurance looks like only a cost when you don’t have losses
Insurance begins to pay off
Substantial benefit, multiples of premium paid
Economic Cost of Risk (ECOR)
Sign Components No Insurance Current Program Option A Option B
+ Discounted Average Retained Losses 5,146,309 3,402,658 3,814,605 3,938,994
+ Premium 0 3,020,342 2,416,274 2,265,257
+ Implied Risk Charge 2,036,577 510,399 572,191 669,629
+ Collateral and Other Admin Costs 110,000 45,000 57,000 70,000
= Economic Cost of Risk 7,292,886 6,978,399 6,860,070 6,943,880
Evaluating the trade-off regarding retaining risk on your company’s balance sheet as
compared to paying a premium to transfer the risk, e.g., insurance. Similar approach
used in other hedging strategies.
3
Optimized Program
Is your company getting the expected value from its insurance purchase?
Assessing Efficiency of Insurance Coverage Using Economic Cost of Risk
16
MARSH
Today’s
Accomplishments?
• Risk management is evaluating and
restructuring their programs
• “Big Data” is important for informing
decisions and strategy
• Use a decision framework to validate
insurance is the right purchase for
the company
• Get buy in from leadership and
finance in the company’s risk
tolerance
• Move beyond peer groups
benchmarking to evaluating your
exposure & risk
• Assess insurance with a commodity
hedge “lens”
17
MARSH
QUESTIONS & CONTACT INFORMATION
18
Steven Jones Marsh Global Analytics
O: 212.345.2711
M: 347.702.0257
Email: steven.e.jones@marsh.com
MARSH
top related