[Framework] Monitoring Emerging Risks with Swiss Re - Part 8 - Claims and Insurance Operations

This post covers risks from legal action precedents, personal damage compensation, big data, regulatory fragmentation concerns, and contingent reputation risks.

[Framework] Monitoring Emerging Risks with Swiss Re - Part 7 - Financial Markets

This post covers risks from inflation and bond yields, sovereign debts, underfunded infrastructure. 

[Framework] Monitoring Emerging Risks with Swiss Re - Part 6 - Life Insurance

This post covers risks from lifestyle changes, new infectious diseases, drug resistance and future medicine.

[Framework] Monitoring Emerging Risks with Swiss Re - Part 5 - Casulty Insurance 2

This post continues from previous post and covers risks from toxic substances, mobility, DIY Trends, and robotics. 

[Framework] Monitoring Emerging Risks with Swiss Re - Part 4 - Casulty Insurance 1

This post covers risks from endocrine disrupting chemicals, electromagnetic fields, nanotechnology and communication patterns.

[Framework] Monitoring Emerging Risks with Swiss Re - Part 3 - Property Insurance 2

This post continues from previous post and covers risks from nat cat exposures, social unrest and risky harvests.

Monitoring Emerging Risks with Swiss Re - Part 2 - Property Insurance 1

This post covers risk from power blackouts, cyber attacks and supply chain vulnerability.

[Framework] Monitoring Emerging Risks with Swiss Re - Part 1 - Introduction & SONAR

1. The Swiss Re introduced a Systematic Observation of Notions Associated with Risk (SONAR) to help society and the insurance industry adapt to emerging risks.

2. It functions by analysing the shifting risk landscape and examine how certain risks could impact the insurance industry in the future.  Aimed at external stakeholders, the study looks at risks such as prolonged power blackouts, cyber attacks, emerging infectious diseases and the unresolved sovereign debt crisis.

China's WMP Products and Shadow Financing

THE SITUATION
1. Local governments circumvent borrowing restrictions causing accumulation of debts into speculative investments.

2. All this is done via the proliferation of maturity mismatched WMPs (wealth Management Products).

3. Banks on the other hand are able to obscure or partially conceal credit risks info with this method.

4. The central bank forces bad debts to be rolled due to protectionism and nationalism reasons suppresses NPLs figures.

5. A rough picture can be obtained from previous post titled "China's Credit Risk Exposure"

[Misconduct] Largest Retail Fine For Poor Complaints Handling

FINED FOR  POOR COMPLAINTS HANDLING

"The Financial Conduct Authority (FCA) has issued its largest ever retail fine (£117m) to Lloyds Bank Plc, Bank of Scotland Plc and Black Horse Ltd (together Lloyds) for failing to treat their customers fairly when handling Payment Protection Insurance (PPI) complaints between March 2012 and May 2013."

"In March 2012, Lloyds issued guidance instructing complaint handlers that the overriding principle when assessing complaints was that Lloyds’ PPI sales processes were compliant and robust unless told otherwise (the Overriding Principle)"
Source: www.fca.org.uk

ARFP Risks and Concerns

To extend from previous article titled "Asset Management Opportunities in Asia". There are currently 3 investment schemes in the Asia region- CIS, ARFP and Hong Kong-China Mutual Recognition. Each with its own features and  cross-border schemes involves risks and obstacles and all schemes must avoid overlooking areas that may deter investors. Below are a few potential risks and costs of cross border investment funds as well as concerns and uncertainties. 

Asset Management Opportunities in Asia

ASIAN REGION FUNDS PASSPORT
Target Live Launch Period:-  Late 2015/ Early 2016

Participating Pilot Group Countries:- Australia, Korea, New Zealand, Philippines, Singapore and Thailand.

Subsequent potential countries still in discussions:- Hong Kong, China, Indonesia, Japan, Malaysia, Taiwan and Vietnam

[Misconduct] Libor Fixing Scandal - A Study in Greed & Failed Controls

BACKGROUND

Bankers ensure that any un-needed surplus would be deposited by the dealers towards the end of a trading day. They would place this money on overnight deposits with other banks. The benchmark for interest payment on this deposit would be the Libor (or Euribor).

Settlement rate was not determined by what rates were actually in the market. Instead, the British Banker’s Association (BBA) polled banks, asking them what the rates were. The highest and lowest quoted rates were discarded and the rest were averaged, giving the settlement rate. 

The Libor was also used as an "weather report" of what conditions were in the market that day and a rough indicative of the banks' financial condition.  

[Misconduct] Misselling of Structured Notes in Singapore - Part 1 - Background Info

BACKGROUND

This post will provide pertinent details from the Monetary Authority of Singapore's investigation report on the sales and marketing of structured notes linked to Lehman Brothers. The aim of this post is to highlight the importance of complying with regulations and guidelines on product's sale and marketing materials especially during the planning stages which no doubt has a rippling effect.

[Misconduct] Misselling of Structured Notes in Singapore - Part 2 - Key Findings, Impact, Root Causes & Views

KEY FINDING
we will look at the types and number of lapses found by MAS for each FIs. Before we delve further, here is a list of internal approval obtained in the various FIs for the distribution of the Structured Notes. . There are two distinct types of approval structures in any organization being a vertical (require higher authority approval depending on predefined policy) and horizontal (sign-off from stakeholders) with vertical structures usually being the faster route. 

Asset Management Challenges

BACKGROUND

After the financial crisis (Lehman 2008), there were substantial growth and profitability in the industry. This post will discuss the challenges & issues in the asset management industry. Below are some past performance data on AuM (Sourced from Financial Institutions and Insurance Practice Areas & BCG Global Asset Management Database)

Understanding Underwriting Risks

UNDERWRITING RISK
Ask staffs in an insurer what are risks associated with underwriting risks and chances are you will get "the risk factors when evaluating the cases underwritten" as a general statement. Here is an except from BNM's defining underwriting activities.

"Insurance underwriting deals with the principles and practices concerning the acceptance or rejection of risks, fixing of premium rates, terms and conditions, the amount of acceptance, retention and reinsurance."

China's Credit Risk Exposure

CHINA'S  NPL INCREASES TO FIVE-YEAR HIGH

Since FY 11 to FY15 Q1, NPLs in China are on an upward trend with NPL of four largest banks reaching a 5 year high.. Refer graph below for NPL trends. Source: (http://www.financeasia.com)

This post will discuss factors in addition to the increase in China's NPL. The factors are constant rollovers and credit risk carried outside of the banks potentially causing a dominos effect as assets become impaired during an economic slowdowns. Lastly we will look at how prepared the banks are by comparing their portfolio of off-balance sheet assets against their total asset.

[Framework] Managing Tail-Risk Events

BACKGROUND
Tail-risk events are extreme events such as flood, storms and market crashes which can erode an insurer's capital and profitability.Tail-risks are found at the extreme left end of bell curves. Insurers would want to minimize fat tail risks without losing out on right tail growth potentials. 

Relative Loss Ratios Using One Way Method

BACKGROUND

The pricing of a policy are highly dependent on the characteristics of the individual to whom the policy is sold. The characteristics could consist of existing conditions (inherent risks) and claims patterns from the same pool of policy holders.  An individual could consist of characteristics from different pools of data (by age, by location, by gender, etc).

To find the relationship between the various pools of claims history is the traditional way of looking at series of one-way tables to determine relativities by rating factor (either focusing on the relative risk premiums or the relative loss ratios)