Towards intelligent data insights in central banks

Roma, 24th Feb 2017

Luigi Bellomarini, IT Department

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Challenges and opportunities for declarative languages

WHATINSIGHTS

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• Credit and credit risk data & Institutional Units register• Securities Holdings Statistics & Securities register• Monetary Financial Institutions Balance Sheets Statistics• Monetary Financial Institutions Interest Rates Statistics• Balance of Payments• National Accounts• Single Supervisory Mechanism• Regulatory frameworks

THEDATAPRODUCTIONPROCESS

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BA

NK

S IN

PU

T L

AY

ER

BanksOperational

SystemsB

AN

KS

OU

TP

UT

LA

YER

PR

IMA

RY

REP

OR

TIN

G

Transformations by banks

NA

TIO

NA

L ST

AT

IST

. PR

OD

UC

TIO

N

SEC

ON

DA

RY

REP

OR

TIN

G

SUP

RA

NA

TIO

NA

L

ST

AT

IST

ICA

L P

RO

DU

CT

ION

Transformations by central banks

Transformations by international institutions

STANDARDIZATION

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• Of processes, models and languages• Guide the process in the banks• Extract the data into harmonized models• Standardize the transformations• Validation & Trasformation Language (VTL)

GSBPM

Information ModelProcess ModelVTL

Operand Operand

Expression

Result

VTL:ASTANDARDLANGUAGE(FROMSDMXINITIATIVE)

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High-level and business oriented• Fully declarative approach• Logic and functional paradigms

Mathematical functions are first-class objects

• VTL manipulates data as mathematical functions• Based on operators (higher-order functions)

Sector

City

Reference Date

Loans = 9.876.543Deposits = 10.234.567

Loans value type = measuredDeposits value type = estimated

Naples

Private

31 Dec 2010

Dimensions Measures Attributes

City Reference Date

Sector Loans DepositsLoans value type

Deposits value type

Naples 2010 12 31 private 9.876.543 10.234.567 measured estimated

Naples 2010 12 31 public 543.210 654.321 measured measured

Naples 2009 12 31 private 9.210.876 10.987.654 estimated estimated

Naples 2009 12 31 public 876.543 1.654.123 measured measured

… … … … … …

Rome 2010 12 31 private 1.234.567 1.546.897 measured measured

… … … … … … ,,,

VTL– AGRAPHOFTRANSFORMATIONS

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Banks & OFIs reports …

D1D2

D3 D4D5

T1

T3T2

D10D12

D13D15

D17D16T13

T12T14

Other data sources

D51D52

T53T52

T51Economic research models

D54D53

T54

C.C.R.

D21D22

D23D24T22

T21

D60D61

Statistical bulletinT60

T61Statistical products

D70T71

T70T72D71 D72

D41T42

T41D42

Supervision models

D4 = get ( D1_LOANS_FLOW, keep (DATE, BANK, AMOUNT), sum (AMOUNT))

D5 = get ( D2_LOANS_STOCK, keep (DATE, BANK, AMOUNT), sum (AMOUNT))

D6_CHECK = check( D5 = lag(D5, -1) + D4)

It’s a DAG!

EXECUTIONPLATFORMS- @BankofItaly

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VTLRGDP := PQR * RGDPPC

tmp <- merge(PQR,RGDPPC,by=c("q","r")) tmp$i <-tmp["p"] * tmp["g"]

TGDP <- tmp[-c("p","g")]

Rgdp = get_tab(pqr * rgdppc)INSERT INTO RGDP(Q,R,P)

SELECT C2.Q AS Q, C2.R AS R, C1.P*C2.G AS PFROM PQR C1 , RGDPPC C2

WHERE C1.Q = C2.Q AND C1.R = C2.R

PQR(q,r,p), RGDPPC(q,r,g) à ∃𝑧RGDP(q,r, z)

User specification

Logical representation

IT implementation

INFOSTAT

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FROMASETOFRULES...TOWARDSAKNOWLEDGEBASE

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Metadata-driven systemDeclarative representationActive dictionaryIntegrated approachNO INFERENCE

• Knowledge base generation

• First Order Languages

REASONING

AICognitive Computing

CREDITS

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• SDMX TWG and VTL task force (www.sdmx.org)• Statistical Data and Concept Representation

The Banca d’Italia’s Active Statistical Metainformation System, Modelling Levels in the Statistical Information System of Bank of Italy, The “Matrix” Model: unified model for statistical representation and processing, Vincenzo Del Vecchio, Fabio Di Giovanni et al. (https://www.bancaditalia.it/statistiche/raccolta-dati/sistema-informativo-statistico/index.html)

• BIRD project (http://banks-integrated-reporting-dictionary.eu)• GSBPM (http://www1.unece.org/stat/platform/display/GSBPM/GSBPM+v5.0)

https://creativecommons.org/licenses/by-nc-sa/3.0/