2025年3月14日 星期五

國帑流失之思辨步驟

 

國帑流失之思辨步驟

一、識不欲之果(UDE):

  • 不欲之果:英倫福利欺詐與失誤致納稅人巨額財損(二零二三至二零二四年估計八十六億鎊)。

二、建當前現實樹(CRT):

  • 依現有資訊及常識假設,構初步現實樹,以探核心問題。
  • 簡化現實樹結構如下:
    • (甲)福利欺詐與失誤致納稅人巨額財損。
    • (乙)福利支出超付率高。(自甲)
    • (丙)超付中欺詐成分甚巨。(自乙)
    • (丁)超付中失誤成分甚巨。(自乙)
    • (戊)虛報收入乃欺詐與失誤之要區。(已知)
    • (己)自僱申領者比例增。(已知)
    • (庚)自僱收入難驗。(依戊、己之假設)
    • (辛)自僱收入驗證程序不足。(自庚)
    • (壬)福利申請程序過繁。(假設;或致無意之誤)
    • (癸)欺詐偵查與預防資源不足。(假設)
    • (子)福利欺詐罰責不嚴。(假設;或不足以阻詐)
  • 或有之根本原因:自僱收入驗證程序不足(辛),兼以福利申請程序過繁(壬),復以欺詐偵查資源不足(癸),或因罰責不嚴(子)而加劇。

三、識核心衝突(蒸發雲):

  • 核心衝突似在:
    • 甲:提供便捷及時之福利。(以助弱勢個人與家庭)
    • 乙:防範欺詐與失誤。(以護納稅人財)
  • 衝突:欲供便捷及時之福利,需減驗證時,速審申請。然欲防欺詐與失誤,需嚴驗證程序,或需更繁審核。此二需現被視為相悖。

四、注釋(破衝突):

  • 傳統之法,乃於收緊管制(緩福利)與放寬管制(增欺詐)間搖擺。吾等需一法,可兼顧便捷與減欺詐。
  • 注釋:基於風險與預測分析之針對性驗證。
    • 非對每份申請均施同等審核,系統應:
      • 建風險評估模型:用數據分析識高風險申請與申領者。因素或包括:
        • 自僱狀態(特指新自僱申領者或收入波動者)。
        • 申領者歷史(前有欺詐或失誤)。
        • 申領福利之類。
        • 人口因素(若統計顯著)。
        • 已知虛報率高之特定行業。
      • 行針對性驗證程序:依風險分數,申請受不同驗證等級。高風險申請受更嚴審核(如收入驗證、審計、實地考察),低風險申請則速審,驗證極簡。
      • 投資科技與數據整合:行科技方案,精簡數據蒐集分析,自動化驗證程序,促政府各部門(如稅務局、商業登記處)間之溝通。
      • 教導申領者,簡化申請程序:創清晰簡潔之申請表,供全面指導,助申領者明其義務,避無意之誤。行線上工具與資源,使申請更易便捷。
  • 此注釋如何應對根本原因:
    • 應對驗證不足(辛):風險評估模型可針對性驗證自僱收入及他高風險區。
    • 應對程序過繁(壬):簡化申請程序減無意之誤,使申領者更易守規。
    • 應對資源不足(癸):專注資源於高風險申請,使有限資源之效最大化。
  • TOC之要旨:
    • 專注:針對性驗證於最需之處(高風險申請)。
    • 系統思維:認知福利系統乃複雜系統,一區之干預可致他區之意外後果。
    • 持續改進:持續監測風險評估模型與驗證程序之績效,並作必要調整。
  • 總結:此基於TOC之法,超越簡化之“收緊管制”或“放寬管制”心態。藉數據分析與風險評估,系統可兼顧合法申領者之便捷,減欺詐與失誤,終供英倫更高效之福利系統。要旨乃針對制約!

Significant financial loss to taxpayers due to benefit fraud and error in the UK

Thinking Process steps

1. Identify the Undesirable Effect (UDE):

  • UDE: Significant financial loss to taxpayers due to benefit fraud and error in the UK (estimated at £8.6 billion in 2023-2024).

2. Build a Current Reality Tree (CRT):

a preliminary CRT based on the available information and common assumptions. The goal is to uncover the core problem.

Here's a simplified CRT structure:

  • (A) Significant financial loss to taxpayers due to benefit fraud and error.

  • (B) High overpayment rates in benefit expenditure. (From A)

  • (C) Significant fraud component in overpayments. (From B)

  • (D) Significant error component in overpayments. (From B)

  • (E) Misrepresentation of earnings is a significant area of fraud and error. (Given)

  • (F) Increase in proportion of self-employed claimants. (Given)

  • (G) Difficult to verify self-employed earnings. (Assumption based on E & F)

  • (H) Inadequate verification processes for self-employed earnings. (From G)

  • (I) Overly complex benefit application process. (Assumption; could contribute to unintentional errors)

  • (J) Insufficient resources allocated to fraud detection and prevention. (Assumption)

  • (K) Weak penalties for benefit fraud. (Assumption; may not deter fraud)

Possible Root Cause: Inadequate verification processes for self-employed earnings (H), combined with an overly complex benefit application process (I), coupled with insufficient resources dedicated to fraud detection (J), all potentially exacerbated by weak penalties (K).

3. Identify the Core Conflict (Evaporating Cloud):

The core conflict seems to be between:

  • A: Providing Accessible & Timely Benefits: (To support vulnerable individuals and families).

  • B: Preventing Fraud and Error: (To protect taxpayer money)

The Conflict: To provide accessible and timely benefits, we need to minimize verification time and process applications quickly. However, to prevent fraud and error, we need thorough verification processes and potentially more intensive processing. These needs are currently seen as opposing each other.

4. The Injection (Breaking the Conflict):

The traditional approach is to swing the pendulum between tightening controls (slowing down benefits) and loosening controls (increasing fraud). We need a solution that simultaneously improves accessibility and reduces fraud.

Injection: Targeted Verification Based on Risk & Predictive Analytics.

Instead of applying a uniform level of scrutiny to every application, the system should:

  1. Develop a Risk Assessment Model: Use data analytics to identify high-risk applications and claimants. Factors might include:

    • Self-employment status (specifically new self-employed claimants or those with fluctuating income).

    • Claimant history (previous instances of fraud or error).

    • Type of benefit being claimed.

    • Demographic factors (if statistically significant).

    • Specific sectors are known for high rates of misrepresentation.

  2. Implement Targeted Verification Procedures: Based on the risk score, applications would be subject to different levels of verification. High-risk applications would undergo more thorough scrutiny (e.g., income verification, audits, site visits), while low-risk applications would be processed quickly with minimal verification.

  3. Invest in Technology and Data Integration: Implement technology solutions that streamline data collection and analysis, automate verification processes, and facilitate communication between different government agencies (e.g., tax authorities, business registries).

  4. Educate Claimants and Simplify the Application Process: Create clear and concise application forms and provide comprehensive guidance to help claimants understand their obligations and avoid unintentional errors. Implement online tools and resources to make the application process easier and more accessible.

How this injection addresses the root cause:
  • Addresses Inadequate Verification (H): The risk assessment model allows for targeted verification of self-employed earnings and other high-risk areas.

  • Addresses Overly Complex Process (I): Simplifying the application process reduces unintentional errors and makes it easier for claimants to comply with requirements.

  • Addresses Insufficient Resources (J): By focusing resources on high-risk applications, the system can maximize the impact of limited resources.

Key TOC Principles:

  • Focus: Targeting verification efforts where they are most needed (high-risk applications).

  • System Thinking: Recognizing that the benefit system is a complex system and that interventions in one area can have unintended consequences in other areas.

  • Continuous Improvement: Continuously monitoring the performance of the risk assessment model and verification procedures and making adjustments as needed.

In conclusion: This TOC-based approach moves beyond a simplistic "tighten controls" or "loosen controls" mentality. By leveraging data analytics and risk assessment, the system can simultaneously improve accessibility for legitimate claimants and reduce fraud and error, ultimately delivering a more efficient and effective benefit system for the UK. The key is to target the constraint!

論國帑流失

 

論國帑流失

「噫!此事甚堪玩味,非耶?皆論官府與錢財。君等納稅,冀其行大事,修坦途,或購戰艦(若今猶為之)。然耳聞流言,謂其未盡其用。

英倫諸君,似陷困境,所謂『福利欺詐與失誤』。似有人失手覆茶,歸咎於貓,非耶?然若論數十億鎊之流失,則非覆茶之小事。

謂本欲助人之財,終……另有所歸。非其所欲,此乃定論。有民似未盡言其收入,尤以自營者為甚。復有誤算,謬誤。以今之電腦與文書,豈不能算清乎?不然。

此令吾憶及本地之況。吾等耗巨資於官府文書,一度竟達百五十億美元,可信乎?或疑此文書是否真能助人,抑或僅使眾人忙於傳遞。且勿論官府合約。以重金聘私企作研究,然報告竟無其名。豈不疑其錢財去向?

似為人之本性,非耶?總有人欲從官府多取,少予。吾等甚至有蜂農謊稱蜂死,以求官府補助。或合律法,然仍令人費解。且若其揮霍者乃君之財,豈不更怒?

故,英倫之財流失,似鄰人盜取君之牛乳。非僅錢財之損,乃原則之失。君等勤勞納稅,冀其善用,而非因人言不盡實,或官吏算數不精,而化為烏有。

豈不疑,是否有人真正在看管錢櫃乎?」

All this talk about government and money

Here's something to chew on, isn't it? All this talk about government and money. You hand it over, thinking it's going off to do grand things, build a proper road or, I don’t know, maybe buy a battleship if we still do that sort of thing. But then you hear whispers, don’t you? Whispers about it not quite getting where it's supposed to.

Now, you folks over in the UK have got yourselves in a bit of a pickle, it seems, with what they call "benefit fraud and error." Sounds a bit like someone’s dropped their teacup and blamed it on the cat, doesn't it? But when you start talking about billions of pounds disappearing, it's more than a spilled cuppa.

They say that a fair whack of the money meant to help people ends up… well, somewhere else. Not where it was intended, that's for sure. You've got folks apparently not being entirely truthful about what they're earning, especially if they're their own boss. And then there's just plain old mistakes, errors. You'd think with all the computers and forms they have these days, they could get the sums right. But no.

It reminds me a bit of how we do things over here. We spend a fortune on government paperwork, fifteen billion dollars a year at one point, if you can believe it . You wonder if all that paper is actually helping anyone, or just keeping a lot of people busy shuffling it around . And don't even get me started on government contracts. Paying private companies a fortune to do studies, and you can't even find their name on the report. Makes you wonder where all that money's going, doesn’t it?

It seems like human nature, doesn't it? Some folks will always try to see if they can get a bit more out of the government than they're putting in . We even had beekeepers claiming their bees had died to get a bit of government help . Perfectly legal, maybe, but still makes you scratch your head . And it makes you madder, doesn't it, when it's your own money they're being a bit careless with .

So, all this money going astray in the UK, it’s a bit like finding out the bloke down the road has been helping himself to your milk. It’s not just the cost, it’s the principle of the thing. You work hard, you pay your taxes, and you expect that money to be used properly. Not vanishing into thin air because someone’s been a bit… economical with the truth, or because someone in a government office can't add two and two.

Makes you wonder, doesn't it, if anyone is really keeping an eye on the till ?