This week I release a discussion I had on the fundamental problems with financial systems held in Bangalore, India on April 10, 2018. To make the concept more approachable, I use personal financial examples to explain the structure of our financial data, and many of my quantitative insights about the nature of our financial systems problems.
The following is an outline of the discussion. In many respects, this discussion led to the paper I drafted a few weeks late, which I have published on my blog as here.
0:00 Introduction to the problem, Dr. William McCarthy, REA idea
1:30 Principles of Financial Data, and your personal finances as an example
4:00 Estimates of data volumes for a person’s finances over time
8:15 person’s transactions might be 1.3 million transaction
8:30 superiority of flexibility of financial reporting from transactions
9:30 possible financial analysis for an individual, and the need for balances to do those reports
11:00 Balances are duplicates of transactions
12:00 Data required for an example calculation of person’s likely financial solvency
13:50 Is a forecast a transaction or a balance and how might they be used?
15:50 Getting realistic about the amount of financial data is traditional kept for individuals
17:20 Why not keep financial data for longer periods of time, and the value of it?
21:20 History of financial systems architecture, and basic bookkeeping, and the cost of computing
22:45 cost curve based upon an example of a smart phone in 1991
23:50 How to you make expensive computers usable? Aggregation
25:10 Most financial systems constructed in 1970, through 1990s
26:15 We’re living with a very old system architecture for financial systems
28:45 How many balances can be made off of a five-attribute table?
32:00 The cost vs. data permutation graph, which is also the transaction vs. balance graph, and the response time vs update cycle graph
34:40 A worked example, and how data warehouses are typically constructed
35:55 Accuracy standard in financial systems, and the cost of reconciliation
38:00 Volumes of data in various industries
40:00 The daily Financial Cycle
42:00 The posting process
43:40 Not the customer perspective, the company perspective is required: the General Ledger
45:45 The typical problem with the General Ledger Balances, and lack of transparency
46:15 A personal example of this problem using your personal bank statement
49:30 Run the system backwards to find the details
51:40 Why do we keep multiple copies of data, and make balances? It is costs.
52:55 Data warehouse, accounting rules engines, and the impact upon this problem space
55:30 On-line transaction updates and memo updates
56:20 Concluding remarks
Watch all episodes in order on the Conversations with Kip playlist.