IDS Enable the Financial Industry to Have TRUST(S) through Data Sovereignty

by Nina Popan­ton

Data mar­kets offer a varie­ty of pos­si­ble solu­ti­ons to cur­rent social and eco­no­mic chal­len­ges, not only when it comes to per­so­nal data but also when there’s par­ti­cu­lar­ly much poten­ti­al in using indus­tri­al and com­mer­cial data for busi­ness opti­miz­a­ti­on and deve­lo­ping sus­tainab­le and suc­cess­ful ser­vices or plat­forms.

The TRUSTS rese­arch pro­ject is based on this idea. In addi­ti­on to the added value that results from the pro­ject, the main aim is to estab­lish trust in data mar­kets. For this pur­po­se, a legal and ethi­cal frame­work has been estab­lis­hed wit­hin “TRUSTS Trus­ted Secu­re Data Sharing Space” pro­ject (EU Grant No. 871481). The visi­on of this pro­ject is to ser­ve not only as a pan-Euro­pean, GDPR-com­pli­ant data mar­ket but also as a fede­r­a­tor bet­ween exis­ting data mar­kets. The con­si­de­ra­ti­ons and results are tes­ted in three use cases for their prac­ti­ca­bi­li­ty and rele­van­ce.

Use cases for a secu­re data sharing space in finan­ce

In a live ses­si­on, orga­ni­zed by the TRUSTS con­sor­ti­um and IDSA, the spea­kers focu­sed on the finan­cial use cases, which are Anti-Money Laun­de­ring Com­pli­an­ce, Agi­le Mar­ke­ting through data cor­re­la­ti­on, and impro­ve­ments in Cus­to­mer Sup­port Ser­vices by Data Acqui­si­ti­on. TRUSTS coor­di­na­tor, Alex­an­dra Garat­zo­gi­an­ni, Head of Know­ledge and Tech­no­lo­gy Trans­fer (TIB,, Coor­di­na­tor of EU pro­jects at Leib­niz Uni­ver­si­ty Han­no­ver, said in this con­text: “Our visi­on is to crea­te an envi­ron­ment that is trans­pa­rent and fair, and holds all sta­ke­hol­ders accoun­ta­ble – but also fur­ther spurs the growth of our Euro­pean eco­no­my.“

Anti-Money-Laun­de­ring Com­pli­an­ce (AML)

The lead part­ner of the Anti-Money-Laun­de­ring (AML) Use Case is eBOS Tech­no­lo­gies Ltd. eBOS pro­vi­des its exis­ting tech­no­lo­gy, a sta­te of the art suite of soft­ware solu­ti­ons for enter­pri­ses Wise­BOS Enter­pri­se Resour­ce Plan­ning to cla­ri­fy the requi­re­ments for com­pli­an­ce in the con­text of AML. The ille­gal move­ment of money to hide its ori­gi­nal source (money laun­de­ring) has inten­si­fied over the recent years and has tur­ned into a glo­bal con­cern that calls for smar­ter pre­ven­ti­on and con­trol approa­ches. “TRUSTS adds a new data approach to AML prac­ti­ces that radi­cal­ly redu­ce fal­se posi­ti­ves by 95 per­cent via new arti­fi­cial intel­li­gence and machi­ne lear­ning skills, while the detec­tion of finan­cial crime and AML gets way fas­ter”, con­tri­bu­tes Gian­na Avgous­ti, R&D Pro­ject Mana­ger at eBOS Tech­no­lo­gies Ltd., to the IDSA Live Ses­si­on.

Impro­ve Cus­to­mer Sup­port Ser­vices by Data Acqui­si­ti­on

Ano­t­her soft­ware ser­vice used wit­hin the pro­ject comes from Rela­tio­nal FS, who are main­ly respon­si­ble for deve­lo­ping busi­ness intel­li­gence solu­ti­ons, such as Aro­TRON™. Chris­tos Rou­pas, Direc­tor for EU pro­jects at Rela­tio­nal, exp­lai­ned: “Relational‘s main con­tri­bu­ti­on to Use Case 3 (Impro­ve Cus­to­mer Sup­port Ser­vices by Data Acqui­si­ti­on) is an impro­ve­ment in anony­miz­a­ti­on, and human-com­pu­ter inter­ac­tion as well as rising the poten­ti­als of chat­bots for cus­to­mer inter­ac­tion.“ The goal in this con­text is to gene­ra­te ser­vices which sup­port finan­cial insti­tu­ti­ons in under­stan­ding and (re)using data.

Poten­ti­al of data mar­ket­pla­ces for finan­cial ser­vice pro­vi­ders

Geor­ge Kos­to­pou­los from Pirae­us Bank, Greece’s lar­gest bank, sta­ted: “Every bank dis­po­ses a lot of data, bet­ter said Big Data. Rea­li­ty is that data in such a busi­ness con­text only ser­ve the pur­po­se of more effi­ci­ent repor­ting or mar­ke­ting cam­pai­gns.“ For finan­cial ser­vice pro­vi­ders like banks, data mar­ket­pla­ces bear huge poten­ti­als but also risks, main­ly due to the use of per­so­nal data, accom­pa­nied by regu­la­ti­ons and legis­la­ti­ons that limit busi­ness opti­ons. Data sel­ling is defi­ni­te­ly far away to be used by banks and other finan­cial insti­tu­ti­ons, but data sharing is and will be rele­vant in the near future as com­bi­ning data of two orga­niz­a­ti­ons bears fruit­ful results with regard to good busi­ness decisi­ons or mar­ke­ting cam­pai­gns. Still, the­re are too many open ques­ti­ons left for banks con­cer­ning anony­miz­a­ti­on and effi­ci­ent use of data. This is a poten­ti­al out­put of TRUSTS: bet­ter ser­vices for com­pa­nies with Big Data.

IDS archi­tec­tu­re as a base for sov­er­eign data exchan­ge

“Data sov­er­eig­n­ty is a huge suc­cess fac­tor for data sharing but has not been well deve­lo­ped yet. It is not clear for many actors how to achie­ve this data sov­er­eig­n­ty“, said Ben­ja­min Heit­mann, post­doc­to­ral rese­ar­cher at Fraun­ho­fer FIT. He fur­ther exp­lai­ned that data exchan­ge as a ser­vice bears huge poten­ti­als in various forms of opti­miz­a­ti­on for com­pa­nies in the finan­cial sec­tor and that data sov­er­eig­n­ty is abso­lute­ly necessa­ry for a secu­re and trust­worthy exchan­ge of data. The IDS archi­tec­tu­re builds a good base for sov­er­eign data exchan­ge with focus on usa­ge con­trol and usa­ge enfor­ce­ment. Still, the­re is a given depen­den­cy on the par­ti­cu­lar eco­sys­tem or com­pa­ny, which is imple­men­ting them. This is whe­re TRUSTS’ con­tri­bu­ti­ons are nee­ded: focu­sing on cryp­to­gra­phic and sta­tis­tic approa­ches, ana­ly­tics, and data intel­li­gence. As a result, stan­dar­di­z­a­ti­on and inter­ope­ra­bi­li­ty is gua­ran­te­ed.

Check out the ent­i­re live ses­si­on here or on You­tube.