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Algorithmic Contract Types Unified Standards

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96:. They describe the need for software that turns natural language contracts into algorithms – smart contracts – that can automate financial processes using blockchain technology. Financial contracts define exchanges of payments or cashflows that follow certain patterns; in fact 31 patterns cover most contracts. Underlying these contracts there must be a data dictionary that standardizes contract terms. In addition, the smart contracts need access to information representing the state of the world and which affects contractual obligations. This information would include variables such as market risk and counterparty risk factors held in online databases that are outside the blockchain (sometimes called "oracles"). 103:'s definition of smart contracts dates back to 1994. However, it is highly relevant for blockchains or distributed ledgers and the concept of smart contracts. Brammertz and Mendelowitz argue in a 2019 paper that without standards, the chaos around data in banks today would proliferate on blockchains, because every contract could be written individually. They further argue that of the four conditions set by Szabo, blockchains will usually fulfill only one, namely observability. 159:
fundamental algorithmic contract type patterns. These incorporate the parts of the data dictionary that apply to a given contract type. Finally, the reference code in Java which calculates the cash flow obligations which are established by the contract so they can be accurately projected, analyzed and acknowledged by all parties over the life of the contract.
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ACTUS has been implemented as a set of royalty-free, open standards for representing financial contracts. The standards combine three elements. First, a concise data dictionary that defines the terms present in a particular type of financial contract. Second, a simple but complete taxonomy of the
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Providing an open standard for the data elements and algorithms of contracts provides consistency first within financial institutions and second when sharing data among organizations in the finance industry. This data may be used to consolidate the views of product lines within a firm, to manage
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The authors argue that the adoption of a standard for smart contracts and financial data would reduce the cost of operations for financial firms, provide a computational infrastructure for regulators, reduce regulatory reporting costs, and improve market transparency. Also, it would enable the
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These ideas led to the ACTUS proposal for a data standard alongside an algorithmic standard. Together, these can describe most financial instruments through 31 contract types or modular templates. The ACTUS Financial Research Foundation and the ACTUS Users Association develop the structure to
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still might be captured in various ways in fields that might be labeled ‘nominal value,’ ‘current principal,’ ‘par value’ or ‘balance’. Standardization of data would improve internal bank operations, and offer the possibility of large-scale financial risk analytics by leveraging
28:, is an attempt to create a globally accepted set of definitions and a way of representing almost all financial contracts. Such standards are regarded as important for transaction processing, 99:
The idea of the standardized algorithmic representation of financial contracts, however, is independent of and predates blockchain technology and digital currencies. In fact, also
484: 709: 470: 76:. However, while these data warehouses physically integrate different sources of data, they do not conceptually unify them. For example, a single concept like 115:
implement the ideas. The also control the intellectual property and development approaches. Specifications are developed, maintained, and released on GitHub.
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to a database run by the Office of Financial Research, an arm of the US Treasury. ACTUS is being used to help define five asset classes (
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The difficulty of defining and analyzing financial data were described by Willi Brammertz and his co-authors in a 2009 book,
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obligations between institutions, or to meet reporting obligations set by regulators. In addition, ACTUS can assist in the
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paper, “Modelling metadata in central banks”. This cites the issue of how financial institutions have tried to overcome
45: 33: 790: 684: 29: 175:(DeFi) using blockchain. For example, ACTUS contracts have been coded in the Marlowe smart contracts language. 661:"OFR Expands Its Financial Instrument Reference Database to Help Identify Inconsistencies in Financial Terms" 785: 660: 172: 65: 41: 235:
2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT)
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Smart Contracts, Distributed Ledgers, and the Need for an Algorithmic Financial Contract Standard
420: 257: 570: 531: 510:"From digital currencies to digital finance: the case for a smart financial contract standard" 464: 365: 344:"From digital currencies to digital finance: the case for a smart financial contract standard" 292: 247: 197: 135: 562: 521: 447: 355: 284: 281:
Financial Analysis and Risk Management: Data Governance, Analytics and Life Cycle Management
239: 139: 131: 69: 146:(FIX) messaging standard, was added a year later. In 2023 ACTUS became a liaison member of 216: 77: 233: 168: 73: 37: 409:
Datengrundlage und Analyseinstrumente für das Risikomanangement eines Finanzinstitutes
142:) in the OFR's financial instrument reference database (FIRD). A third reference, the 779: 108: 413:
Data founation and analysis tools for the risk management of a financial institution
261: 44:(DeFi) using blockchain technology. ACTUS is used as a reference standard by the 755: 228:
Kurt, Stockinger; Heitz, Jonas; Bundi, Nils; Breymann, Wolfgang (December 2018).
288: 685:"Financial Instrument Reference Database (FIRD) | Office of Financial Research" 229: 566: 276: 100: 20: 574: 535: 526: 509: 369: 360: 343: 243: 550: 147: 119: 441: 230:"Large-Scale Data-Driven Financial Risk Modeling Using Big Data Technology" 451: 82: 612: 485:"Nick Szabo -- Smart Contracts: Building Blocks for Digital Markets" 123: 730: 127: 118:
In October 2021, ACTUS was added as the second reference after
636: 415:] (in German). Zurich: Dissertation, University of Zurich. 588: 111:
by directly quantifying the interconnectedness of firms.
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technology. Key to this is the idea of "contract types".
383: 318:"Smart Contracts Were Around Long Before Cryptocurrency" 194:
Unified Financial Analysis: The missing links of finance
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Unified Financial Analysis: The missing links of finance
277:"The Office on Financial Research and Operational Risk" 217:
https://www.ecb.europa.eu/pub/pdf/scpsps/ecbsp13.en.pdf
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Brammertz, Willi; Mendelowitz, Allan I. (2018-01-01).
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Brammertz, Willi; Mendelowitz, Allan I. (2019-04-01),
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Brammertz, Willi; Mendelowitz, Allan I. (2018-01-01).
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Brammertz, Willi (2010-01-01). Clacher, Iain (ed.).
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The simplicity of the problem is described in an 275:Brammertz, Willi (2013), Lemieux, Victoria (ed.), 167:of financial instruments, and the development of 88:The concepts were expanded upon by Brammertz and 36:of financial instruments, and the development of 283:, Berlin, Heidelberg: Springer, pp. 47–71, 710:"OFR'S Financial Instrument Reference Database" 708:Office of Financial Research (November 2022). 555:Journal of Financial Regulation and Compliance 8: 21:Algorithmic Contract Types Unified Standards 469:: CS1 maint: location missing publisher ( 525: 359: 446:(SSRN Scholarly Paper), Rochester, NY, 184: 462: 418: 407:Brammertz, Willi (December 13, 1991). 637:"ACTUS Financial Research Foundation" 7: 14: 144:Financial Information eXchange 16:System for financial contracts 1: 425:: CS1 maint: date and year ( 665:Office of Financial Research 72:by building enterprise-wide 46:Office of Financial Research 32:, financial regulation, the 514:The Journal of Risk Finance 348:The Journal of Risk Finance 289:10.1007/978-3-642-32232-7_3 812: 754:FRF, ACTUS (2020-06-08). 689:www.financialresearch.gov 613:"Technical Specification" 567:10.1108/13581981011019624 192:Brammertz, Willi (2009). 527:10.1108/JRF-02-2017-0025 361:10.1108/JRF-02-2017-0025 244:10.1109/BDCAT.2018.00033 796:Cryptocurrency projects 94:Journal of Risk Finance 92:in a 2018 paper in the 717:financialresearch.gov/ 551:"Risk and regulation" 173:decentralized finance 48:(OFR), an arm of the 42:decentralized finance 452:10.2139/ssrn.3373187 238:. pp. 206–207. 154:ACTUS implementation 90:Allan I. Mendelowitz 756:"Marlowe and ACTUS" 791:Financial software 489:www.fon.hum.uva.nl 298:978-3-642-32232-7 253:978-1-5386-5502-3 24:, abbreviated to 803: 770: 769: 767: 766: 751: 745: 744: 742: 741: 727: 721: 720: 714: 705: 699: 698: 696: 695: 681: 675: 674: 672: 671: 657: 651: 650: 648: 647: 633: 627: 626: 624: 623: 609: 603: 602: 600: 599: 585: 579: 578: 546: 540: 539: 529: 505: 499: 498: 496: 495: 481: 475: 474: 468: 460: 459: 458: 437: 431: 430: 424: 416: 404: 398: 397: 395: 394: 380: 374: 373: 363: 339: 333: 332: 330: 329: 314: 308: 307: 306: 305: 272: 266: 265: 225: 219: 214: 208: 207: 189: 811: 810: 806: 805: 804: 802: 801: 800: 776: 775: 774: 773: 764: 762: 753: 752: 748: 739: 737: 729: 728: 724: 712: 707: 706: 702: 693: 691: 683: 682: 678: 669: 667: 659: 658: 654: 645: 643: 635: 634: 630: 621: 619: 611: 610: 606: 597: 595: 587: 586: 582: 548: 547: 543: 507: 506: 502: 493: 491: 483: 482: 478: 461: 456: 454: 439: 438: 434: 417: 406: 405: 401: 392: 390: 382: 381: 377: 341: 340: 336: 327: 325: 322:American Banker 316: 315: 311: 303: 301: 299: 274: 273: 269: 254: 227: 226: 222: 215: 211: 204: 191: 190: 186: 181: 169:smart contracts 156: 74:data warehouses 58: 38:smart contracts 30:risk management 17: 12: 11: 5: 809: 807: 799: 798: 793: 788: 778: 777: 772: 771: 746: 722: 700: 676: 652: 628: 604: 580: 541: 500: 476: 432: 399: 375: 334: 309: 297: 267: 252: 220: 209: 203:978-0470697153 202: 183: 182: 180: 177: 155: 152: 107:assessment of 78:notional value 57: 54: 15: 13: 10: 9: 6: 4: 3: 2: 808: 797: 794: 792: 789: 787: 786:Data modeling 784: 783: 781: 761: 757: 750: 747: 736: 732: 726: 723: 718: 711: 704: 701: 690: 686: 680: 677: 666: 662: 656: 653: 642: 638: 632: 629: 618: 614: 608: 605: 594: 590: 584: 581: 576: 572: 568: 564: 560: 556: 552: 545: 542: 537: 533: 528: 523: 519: 515: 511: 504: 501: 490: 486: 480: 477: 472: 466: 453: 449: 445: 444: 436: 433: 428: 422: 414: 410: 403: 400: 389: 385: 379: 376: 371: 367: 362: 357: 353: 349: 345: 338: 335: 323: 319: 313: 310: 300: 294: 290: 286: 282: 278: 271: 268: 263: 259: 255: 249: 245: 241: 237: 236: 231: 224: 221: 218: 213: 210: 205: 199: 195: 188: 185: 178: 176: 174: 170: 166: 160: 153: 151: 149: 145: 141: 137: 133: 129: 125: 121: 116: 112: 110: 109:systemic risk 104: 102: 97: 95: 91: 86: 84: 79: 75: 71: 67: 63: 55: 53: 51: 47: 43: 39: 35: 31: 27: 23: 22: 763:. 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Wiley. 120:ISO 20022 465:citation 262:57764283 148:ISO TC68 136:warrants 124:equities 83:Big Data 731:"About" 150:/ SC9. 140:futures 132:options 56:History 641:GitHub 589:"Home" 573:  534:  368:  295:  260:  250:  200:  138:, and 760:ACTUS 735:ACTUS 713:(PDF) 617:ACTUS 593:ACTUS 411:[ 258:S2CID 26:ACTUS 571:ISSN 532:ISSN 471:link 427:link 366:ISSN 293:ISBN 248:ISBN 198:ISBN 171:for 128:debt 40:for 563:doi 522:doi 448:doi 356:doi 285:doi 240:doi 66:ECB 782:: 758:. 733:. 715:. 687:. 663:. 639:. 615:. 591:. 569:. 559:18 557:. 553:. 530:. 518:19 516:. 512:. 487:. 467:}} 463:{{ 423:}} 419:{{ 386:. 364:. 352:19 350:. 346:. 320:. 291:, 279:, 256:. 246:. 232:. 134:, 130:, 126:, 52:. 768:. 743:. 719:. 697:. 673:. 649:. 625:. 601:. 577:. 565:: 538:. 524:: 497:. 473:) 450:: 429:) 396:. 372:. 358:: 331:. 287:: 264:. 242:: 206:.

Index

Algorithmic Contract Types Unified Standards
risk management
tokenization
smart contracts
decentralized finance
Office of Financial Research
US Treasury
ECB
data silos
data warehouses
notional value
Big Data
Allan I. Mendelowitz
Nick Szabo
systemic risk
ISO 20022
equities
debt
options
warrants
futures
Financial Information eXchange
ISO TC68
tokenization
smart contracts
decentralized finance
ISBN
978-0470697153
https://www.ecb.europa.eu/pub/pdf/scpsps/ecbsp13.en.pdf
"Large-Scale Data-Driven Financial Risk Modeling Using Big Data Technology"

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